metal–organic framework nanoparticles for magnetic...

INORGANIC CHEMISTRYFRONTIERS

REVIEW

Cite this: Inorg. Chem. Front., 2018,5, 1760

Received 15th February 2018,Accepted 27th March 2018

DOI: 10.1039/c8qi00149a

rsc.li/frontiers-inorganic

Metal–organic framework nanoparticles formagnetic resonance imaging

Michael Peller, *a Konstantin Böll,a Andreas Zimpelb and Stefan Wuttke *b,c

Metal–organic framework (MOF) chemistry offers the unique possibility of bridging organic and inorganic

chemistry to develop hybrid crystalline porous materials and opens the door to the synthesis of highly

functional bulk- or nano-materials. A potential future field of application is their biomedical application as

a theranostic agent or simply as a new contrast agent for magnetic resonance imaging (MRI). MRI is one

of the most versatile imaging modalities in routine clinical examinations due to a wide range of usable

contrast mechanisms. This in turn leads to a variety of conceivable nanoparticle designs as an MR contrast

agent or theranostic. This review aims to integrate the state-of-the-art of MOF nanoparticles and their

use in MRI. It gives an overview of the work done so far, focusing especially on the clinical applicability.

Furthermore, it summarises the different factors for MR signal formation mechanisms important for the

development of MR active nanoparticles and provides suggestions for a better comparison between

different studies.

The subject of human health involves and moves people allover the world. Due to changes in living conditions and theincreasing life expectancy of the population, metabolic dis-

orders, cancers, and cardiovascular diseases occur more andmore frequently and thus have become a significant concernin our everyday life. New methods for prevention, diagnosisand therapy need to be developed and therefore different gov-ernment initiatives support especially transformative engineer-ing research that has the potential to contribute to thesefields. In this respect the application of nanotechnologies inmedicine gave the last two decades innovative impulses tohealth care.1–9 Their applications range from being used asanalytical tools with the capability of multimodal parallel ana-lysis (e.g. microarrays or multimodal imaging), deliveringdrugs directly to their target (e.g. nanocarriers as drug deliverysystems) or combining both therapeutic and diagnostic capa-bilities in one theranostic nanoparticle.10–22

A typical envisioned application of such a theranostic nano-particle is its use as a drug carrier for chemotherapy of solidtumours (therapeutic capability) and at the same time moni-toring the therapy process (diagnostic capability).Chemotherapy is very often applied systemically by intravenousinjection relying on accumulation in the tumour tissuebecause of its pathological ill-functional nature. The deliveryto the tumour and also the distribution of the drug within thefrequently heterogeneously structured tumour tissue cannotbe visualised instantly. Imaging as a diagnostic tool may ident-ify such a distribution pattern of the released drug in a specifictarget volume or even to quantify drug delivery in vivo for anindividual patient, thus potentially allowing further optimi-sation of the therapy. Magnetic resonance imaging (MRI)seems to be one of the most promising imaging methods forsuch a purpose as MRI is a versatile standard imaging method

Stefan Wuttke

Since 2011, Stefan Wuttke hasbeen a leader of the researchgroup “Wuttkegroup for science”,hosted at the Institute ofPhysical Chemistry at theUniversity of Munich (LMU), andat the Center for Nanoscience(CeNS) at the LMU. Currently,he is a Senior Lecturer in theChemistry School at theUniversity of Lincoln. His princi-pal focus is on the design, syn-thesis and functionalization ofMOFs and their nanometric

counterparts to target biomedical applications. At the same time,he intends to establish a basic understanding of the chemical andphysical elementary processes involved in the synthesis,functionalization, and application of these hybrid materials.

aDepartment of Radiology, University Hospital of Munich, University of Munich

(LMU), 81377 Munich, Germany. E-mail: [email protected] of Chemistry and Center for NanoScience (CeNS), University of Munich

(LMU), 81377 Munich, Germany. E-mail: [email protected] of Chemistry, Joseph Banks Laboratories, University of Lincoln, Lincoln LN6

7TS, UK

1760 | Inorg. Chem. Front., 2018, 5, 1760–1779 This journal is © the Partner Organisations 2018

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in clinics and, as described later, MRI offers a wide range ofproperties such as multiple contrast mechanisms useable indesigning new MRI active particles. From a materials perspec-tive, bridging organic and inorganic chemistries to develophybrid crystalline porous materials, as bulk- and nano-material, opens the door to the synthesis of highly functionalmaterials. In the past two decades, significant progress hasbeen made in innovative basic science of metal–organic frame-work (MOF) structures with properties unmatched by theirindividual building blocks.23–28

For a systematic approach to that field of research, thisreview focuses on a more strict definition of MOF nano-particles that is requiring highly crystalline structures. Thesymmetrical arrangement of the building blocks certifies well-ordered pores with well-defined size. Nanoparticle size is amajor issue in many aspects (as their properties are size-dependent) for MRI and biomedical applications in general. Inaddition, crystallinity ensures higher reproducibility and withthis higher quality control, which is required for clinical appli-cability. With a periodic arrangement requirement for MOFnanoparticles the number of original publications in thisminireview has narrowed down to about 25 original papers.

When comparing the original research articles investigatingMRI active MOF nanoparticles, it is challenging, if not imposs-ible, to compare MRI characteristics of these particles as theresults are presented based on differently assessed relaxivities,partly without stating the magnetic field strength, samplepreparation or the temperature at which the samples weremeasured. Most of these studies are in an early stage of basicresearch, and considering the long way to a potential use inpatients, the authors have naturally focused on a proof-of-concept showing that clinical MRI activity is present. Based onthese findings, we would like to advocate a selection of factorsthat should be considered in the characterisation of new nano-particles by MRI even at that early stage of development and todiscuss how to report these factors. By this, we hope that thiswill allow a better comparability of different nanoparticles andthus accelerate the identification of the most promising typesof nanoparticles for a clinical MRI application.

Therefore, this review summarises recent advances in thedevelopment of MOF nanoparticles for MRI applications withthe intention to provide an overview of the key aspects in thatfield. It aims at integrating the views of two different fields,i.e., MOF and MRI, to delineate the specific principles,approaches, and the novel opportunities by combining bothfields. This review is written in a comprehensive and non-exhaustive manner and it provides a critical overview for bothfields instead of just categorising everything that has beendone.

Introduction – metal–organicframeworks (MOFs)

Metal–organic frameworks, also known as MOFs, are syn-thesised in a building-block fashion from inorganic building

units (IBUs, metal-ion vertices), interconnected by organicbuilding units (OBUs, organic linker molecules) in a self-assembly process, to create highly tailorable crystallinematerials with pores of nanometre dimensions.29–31 Thehybrid inorganic organic scaffold of MOFs is controlled by thedifferent types and connectivities of the IBUs and OBUs. MOFsare known to have a high porosity (even higher than zeolites orporous carbon) and to be thermally and mechanically stablebut they have a rather moderate chemical stability (especiallyunder strongly basic conditions). Contrary to zeolites or othersolid matter like carbons and oxides, MOFs totally lack non-accessible bulk volume as they are essentially scaffolds with allor most atoms on internal surfaces, giving MOFs a recordporosity of up to 90% free volume and internal surface areasexceeding 6000 m2 g.29

Although the number of publications referring to thekeyword “MOF” has increased drastically in the last 20 years,29

the definition of the term MOF itself remains not that clear.The International Union of Pure and Applied Chemistry(IUPAC) group has published provisional recommendations onMOFs and coordination polymers (CPs).32,33 Their differen-tiation between MOFs and CPs focuses only on the periodicopen framework structure of MOFs that creates voids. But thecrystallinity of MOFs is one more characteristic that allowsdifferentiation from the open non-crystalline CPs. For theauthors the term MOF refers to crystalline porous scaffoldsthat are periodically assembled between positively chargedIBUs and negatively charged OBUs. This review will focus onlyon MOF nanoparticles that exactly meet this definition. Othercoordination (e.g. non-crystalline coordination polymers) orhydrogen-bonded networks will not be considered. The crystal-linity of the MOF materials is advantageous as it unambigu-ously defines the fundamental structure of the investigatedmaterial (e.g. knowing the exact atom positions and their con-nections resulting in knowledge of the pore morphology andsize) and for later practical purposes it can be used as qualitycontrol.

The most important characteristics of MOFs are a highsurface area that exhibits selective absorption, crystallinity,tuneable porosity, the presence of strong metal–ligand inter-actions and their structural diversity.29–31 These characteristicsallow MOFs to be very diverse when it comes to applications,since there are over 60 000 variations reported in theCambridge Structural Database (CSD).34 Importantly, thedesign possibilities of MOFs don’t end with the combinationof various IBUs and OBUs during synthesis (Fig. 1). Thescaffold of MOFs can be further modified after their synthesis.The functionalisation of MOFs by postsynthetic modification(PSM) can provide access to more sophisticated MOF materials(Fig. 1).35 PSM describes the functionalisation of the alreadysynthesised solid material. In principle two PSM approachescan be distinguished. The first strategy focuses on the IBU forintroducing functional groups (Fig. 1).36–39 Secondly, thechemistry of the OBU can be exploited to achieve chemicalmodification of MOFs (Fig. 1).40–42 Another PSM classificationconcentrates on the reaction process itself, distinguishing PSM

Inorganic Chemistry Frontiers Review

This journal is © the Partner Organisations 2018 Inorg. Chem. Front., 2018, 5, 1760–1779 | 1761

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into the categories addition, elimination, or exchange. An over-view of different PSM strategies can be found in currentreviews.35,43–45 In conclusion, the huge structural variability ofMOFs together with various possibilities to introduce function-alities inside the MOF scaffold enable material chemists tooptimise the material performance for specific applications.Storage of gases, gas/liquid purification and separation, drugstorage and delivery, catalysis and sensing are just someexamples of the numerous applications of MOF materials.

Introduction – MOF nanocarriers

Generally speaking, drug delivery systems (e.g. nanocarriers)are capable of bypassing extra- and intracellular biological bar-riers, release the active agent (e.g. drug) at the side of actionand, with this, improve the therapy effect significantly. Theyhave to fulfil diverse tasks during the delivery process, e.g.drug loading, nanoparticle sealing, cell targeting and uptake,endosomal escape, as well as controlled and triggered drugrelease.4,8

Besides the structural design and functionalisation of bulkMOF materials at the molecular level, the control of MOFcrystal size at the nanometre level results in materials whosebehaviour is no longer determined by their inner surface alonebut also by their outer surface properties due to their high exter-nal surface area-to-volume ratio. Due to the scaling-down ofMOF materials to the nanoscale, MOF specific properties alsobecome size-dependent.46–49 This lets MOFs stand out fromthose of three-dimensional infinite solids. The overall vision forMOF nanoparticle chemistry is to integrate functional mole-cular building blocks into artificial multifunctional nano-systems that are able to operate in biological environments.Therefore, the demand is to create functional hybrid nano-systems that could not be created with other material classes.

In the last few years, researchers have developed differentMOF nanocarriers and demonstrated their in vitro and in vivo

activity.50–57 In particular, recent publications report the syn-thesis of innovative MOF drug delivery systems.58–76 However,accurate knowledge of the location during transport and thequantity of the nanocarrier as well as the monitoring of thedrug delivery process are challenging but important tasks andhave so far been comparably unexplored in the field of MOFnanocarriers. Adding imaging capabilities to the new nano-carrier could overcome such limitations and could offer newopportunities to control and potentially optimise drug deliveryin an individual patient.

Introduction – magnetic resonanceimaging

Signal formation in MRI is complex and even more complexwhen MRI active particles such as contrast agents (CA) or, asin our case, MOFs are added. Therefore, a short summary ofMRI principles and MRI CAs is presented for a better under-standing of MRI effective MOFs on their way to a clinical appli-cation. Relevant factors such as image quality parameters,relaxation times, differences of MRI in research and in clinics,or how commonly used contrast agents can be characterised,are pointed out and discussed. Based on the discussion, sug-gestions for in vitro MRI measurement of MOF nanoparticleswill be deduced.

MRI is an established, non-invasive, clinically used imagingmethod with a wide range of applications such as tumourdetection or chemotherapy response assessment. MRI offersenormous 3D imaging capabilities especially for soft tissuebased on the high natural abundance of the signal givingwater protons present in human soft tissue.77,78 It is importantto note that CA or MRI active nanocarriers are only indirectlydetected through their influence on the signal of waterprotons in the near surrounding. Besides that, MRI also allowsassessing functional tissue parameters such as tissue per-fusion and diffusion and can visualise CA enhancement or

Fig. 1 Schematic drawings of the different modification approaches used to endow a MOF scaffold with additional functionality. These approachescan be classified into two main concepts: in the first one, at least one building block is modified before MOF synthesis (left), while in the secondapproach, the structure is synthesised first and then subjected to further post-synthetic modifications (PSM, right).

Review Inorganic Chemistry Frontiers


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drug delivery.79,80 To evaluate such time dependent processes,consecutively repeated image acquisition is necessary. This is,in contrast to other standard imaging methods such as com-puted tomography (CT), easily justifiable in MRI because ofthe absence of potentially harmful ionising radiation.

The complex signal and image generation process asdescribed later is offering a broad spectrum of image contrastsbut requires, in return, also optimisation of the imaging para-meters in order to gain good image quality.

MRI image quality can be characterised by spatial resolu-tion and contrast (= difference in signal intensity betweendifferent tissues or organs compared to the overall signalintensity) in relation to noise, which is also always present inan image to some degree (additive to the MR-signal, character-ised by the signal-to-noise ratio, SNR). Secondary quality para-meters related to the application can be acquisition time.Acquisition time defines maximum achievable temporal resolu-tion for instance in characterizing a dynamic process such asCA enhancement. Acquisition time is also a limiting factorbecause with increasing acquisition time the risk of imagedegradation due to patient motion increases. Improving one ofthe factors may lead to degrading of another quality para-meter. For example, improving spatial resolution will lead tolower SNR as explained later. That in turn could be overcomeby more signal averaging, which will result in longer acqui-sition times and thus will increase the risk of motion artifacts.

MRI as a method is also prone to image artifacts again inpart because of the complex imaging process. One majorcharacteristic of MRI in this context is that the geometry of theimaged object may not be preserved in the image, dependingon the imaging methods and settings used. This is in contrastto CT, for instance, which is geometry preserving and hastherefore become a standard imaging method for radiationtherapy planning.

An important feature of MRI is being able to use almost thesame MRI methods in clinics, preclinical research or even inbasic research and allowing in principle the translation of newmethods to clinical use and vice versa. Constraints for trans-lation of methods and results can be related to the differentsafety issues or imaging settings such as the typically highermagnetic field strengths (B0) used in preclinical imaging. Ahigher field strength, for example, results in higher energydeposition in humans (∝B02)81 requiring other or low powerradio-radiofrequency (RF) pulses for safety reasons. Anotherconsequence of a higher than clinically used field strength isthat the relaxivity of a CA may change.82,83 Relaxivity is a para-meter describing the contrast changing effectiveness of a CAin MRI (see the section Contrast agents). Typical clinicallyused field strengths are in the range of 1.5 T to 3 T whereas inresearch, higher field strengths such as 7 T for the imaging ofhumans or even higher for preclinical imaging are used.

MRI principle

Clinical MRI is primarily based on the nuclear magnetic reso-nance (NMR) effect of water protons present in the humanbody. As NMR is a common analysis method in chemistry, the

authors assume that the principles of NMR are familiar to thereaders and therefore only major differences are pointed outin a generalised way with a focus on image quality parameterssuch as spatial resolution, contrast and noise.

Comparing MRI to NMR, one obvious major difference isthat spatial signal encoding is required to calculate an image.This is made possible by using additional magnetic field gradi-ents that are superimposed to the main magnetic field B0 inthe x-, y- and z-directions (of the order of 20–80 mT m−1 in aclinical MRI system). These gradients have to be switched onand off before and during echo formation to impress spatialinformation into the signal. In one dimension an additionallinear gradient varies the Larmor frequency of the waterprotons along this gradient in a known linear way. Analysingthe sample echo by Fourier transformation allows identifyingthe origin of a specific signal by its frequency along this gradi-ent. In three dimensions, the gradients in the x-, y- and z-direc-tions superimpose and the signal echo from a single experi-ment would deliver ambiguous spatial information. To solvethis problem, several echoes have to be recorded each withor after systematic variation of the encoding gradientsstrength. In this way a set of signal echoes can be collectedthat allows calculating the origin of signals also in 3D. Themore variation steps are performed the higher is the achievedspatial resolution. The spatial resolution, typically of the orderof 1 mm3, is limited by the total acquisition time needed toimage a specific body part and the concomitant risk of motionartifacts. The minimum size of such a volume element (voxel)is related to the decreasing signal intensity compared to signalnoise as the number of water protons contributing to thesignal intensity of this voxel is decreasing in proportion to thedecreasing voxel volume.81 The possibility of varying thetiming, duration and strength of RF-pulses, gradients or thetime points of signal sampling leads to a nearly endless list ofpulse sequence types81 and sets of possible parameter selec-tions to influence and optimise the image contrast (twoexamples are presented in Appendix 1). Instead of optimi-sation, there is at the same time a risk of degrading the signalintensity by choosing a less than optimal parameter set.

The resulting signal intensity of a specific voxel in an MR-image is an effective signal originating from all tissues withinthis voxel and is determined by the abundance of the waterprotons (commonly called “proton density” or “nuclear spindensity” in clinical MRI) and their polarisation (see eqn (1)),the local magnetic properties of the tissue (longitudinal/spinlattice T1 and transverse/spin–spin T2 relaxation time for spin-echo pulse sequences or T*

2 relaxation time for gradient echopulse sequences) and the pulse sequence type with its para-meter settings (such as flip angle α, repetition time TR or echotime TE). Other factors such as flowing protons in a bloodvessel can also affect signal intensity. All these factors contrib-ute to the signal intensity of one voxel and the variationbetween voxels makes up the contrast in an image. By modify-ing, for instance, TR and TE in a classic spin echo pulsesequence one of the characteristic tissue parameters such asT1 can predominately determine the image contrast (short TR



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and short TE using a spin echo pulse sequence see Eqn 2). Inthat case the image is called T1-weighted or with other settingsaccordingly PD-, T2- or T*

2 -weighted (Fig. 5). T*2 describes the

transverse relaxation process induced by a combination ofspin–spin interaction and additional dephasing by magneticfield inhomogeneities that is seen with gradient echo pulsesequences (eqn 3).81,84 T*

2 is sensitive to experimental con-ditions81 such as susceptibility variations within the imagedobject, field homogeneity and voxel size and thus determi-nation of T*

2 is more challenging.Besides tissue and pulse sequence parameters, also the

system adjustments performed before the pulse sequencestarts will contribute to the absolute signal intensity. That con-tribution may change between two measurements acquired atdifferent time points. In consequence, for a quantitative com-parison between distinct measurements T1- or T2-relaxationtimes should be determined instead of comparing simplysignal intensities because these relaxation times should beindependent of factors such as system adjustments for aspecific measurement.

When translation of the results from preclinical MRI orNMR research to clinical MRI is considered, this means typi-cally reducing the magnetic field strength from maybe 9 T to 3T. A change in field strength is accompanied i.e. by a changein tissue related parameters (magnetisation, T1, etc.), in theapplicable imaging techniques (pulse sequence settings, safetyconstraints) and the effectiveness of CA to modify image con-trast (see following paragraphs).

Imaging at higher field strengths is typically related to ahigher risk for artifacts caused by susceptibility effects. Buthigher sensitivity for susceptibility effects in return may alsooffer a higher sensitivity for the detection of particles that“disturb” the susceptibility in their near vicinity. If the CA con-centrations are very high or the particles have a strong mag-netic moment, then the susceptibility effects or the relaxationtime shortening can be so strong that no signal is technicallydetectable anymore. In other words, there is a technicallybased reasonable upper limit for the amount of CA that can beused besides toxicity effects. If the volumes of susceptibilitydistortions increase to a macroscopic level, this will lead alsoto distortions or allocations in 3D and thus can affect severalimage slices.

Manipulating the MR image contrast allows to differentiatebetween different tissues and pathologies. One way to gaindifferent contrasts has been described already above: tochoose different combinations of pulse sequence parameters(TE, TR, α; see eqn (2) and (3)). In this way, one of the tissuespecific parameters (M0, T1, T2, T*

2) is dominating the contrastof the image (Fig. 5). Another way to modify contrast could beby manipulating the tissue specific parameters (M0, T1, T2, T*

2)themselves. The water proton spin density of a tissue is hardlychangeable. Instead, M0 may be increased by choosing ahigher field strength B0 (see eqn (1) in Appendix 1). Also verycommon in clinical practice is manipulating the relaxationtimes (T1, T2, T*

2) by adding a so-called CA. Depending on theapplied pulse sequence type and the type and the concen-

tration of the CA, this will lead either to increased or decreasedsignal intensity at the site where the CA is added. Beyondthese basic techniques to control image contrast, other moreadvanced techniques can be exploited for contrast manipu-lation or for assessing tissue parameters such as diffusion ormagnetisation transfer.

Contrast agents

MRI CAs approved for clinical use are magnetically active sub-stances typically of paramagnetic or superparamagneticnature.85 A CA becomes indirectly visible in water protonbased MRI by reducing the relaxation times of the waterprotons in its close vicinity. This is a major difference fromCAs of other imaging modalities where the CA itself is visiblesuch as by attenuating the X-ray radiation in CT. The indirectsignal mechanism and the multiple parameters contributingto this signal complicate quantification but also allow optimis-ing the CA induced signal change for a specific type of CAsuch as emphasising either the T1 shorting or T2 shorteningcapabilities.

MRI CAs in clinical routine are commonly based on para-magnetic gadolinium (e.g. Gd3+) embedded in a chelate (Gd-CA).82,83,85 Less frequently used CAs are based on Mn2+

embedded in a chelate or superparamagnetic nanoparticlesbased on Fe2+ or Fe3+-oxides (i.e. superparamagnetic iron oxidenanoparticle (SPION) and ultrasmall superparamagnetic ironoxide USPIO).83,85–87

CA induced shortening of T1 will result in a signal increasein a T1-weighted image as long as the concomitant T2 shortingeffect is not more effective (see eqn (2)). In a T2- or T*

2

-weighted image signal intensity is typically reduced.Optimisation of the imaging technique is necessary to obtaina maximal signal intensity change by adding a CA. A signalincrease is mostly preferred compared to a signal decreasebecause a decrease could make detection and evaluation of CAenhancement more challenging. That is, a CA induced signaldecrease in a tissue with an inherently low signal will not beeasily detectable (further darkening in a dark tissue) andbecause a signal decrease may have other causes besides theapplication of a CA such as blood flow changes or artifacts.

The ability of clinically used MRI CA to shorten relaxationtimes and thus to influence image contrast is dependent onthe magnetic field strength, size and mobility of the CA andtherefore also on binding to larger molecules in blood, andchange of the environment or the temperature.82,88 This abilityis commonly described quantitatively by the so-called relaxivityri (i = 1,2; eqn (5)) that is the induced change of the relaxationrate (1/Ti, i = 1,2) normalised to the concentration of the mag-netically active metal ions or of particles [i.e. ref. 89].

It is important to note that the definition of relaxivity perparticle or metal ion is the same in typical metal chelatesbecause there is only one MRI effective metal ion (Gd3+, Mn2+)per coordination complex, whereas in the case of nano-particles a single particle can consist of several active metalions. Thus it should be stated if relaxivity refers to the concen-tration of metal ions or the concentration of nanoparticles to



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allow for a comparison of different nanoparticles or CAs[i.e. ref. 90]. Relaxivity (r1, r2 or r*2) values should be presentedstating the magnetic field strength, the range of concen-trations, medium/solution, temperature and other potentiallyrelevant parameters such as pH for a comparison of differentparticle types (Appendix 2) (Fig. 2).

The range of typical relaxivities for common CAs were pre-sented, for example, by Rohrer et al.83 comprising Gd3+, Mn2+,and iron oxide based CA. These CAs prepared in different solu-tions such as water, plasma or blood at 37 °C were character-ised at clinically used field strengths of 1.5 T and 3.0 T andbeyond that at 0.5 T and 4.7 T. For example, the Gd-based CAGd-DTPA (Magnevist®, 3 T, 37 °C, in plasma) shows a r2/r1value of 5.2 L mmol−1 s−1/3.7 L mmol−1 s−1, whereas a SPIOnanoparticle such as Ferucarbotran (Resovist®, 3 T, 37 °C, inplasma) offers a r2/r1 relation of 160 L mmol−1 s−1/3.3L mmol−1 s−1. The authors demonstrated also the effect ofprotein binding on relaxivities of Gd-BOPTA (Multihance®,3 T, 37 °C) when the solution is changed from water to plasma.The r2/r1 of Gd-BOPTA changed from 4.7 L mmol−1 s−1/4.0L mmol−1 s−1 to 11.0 L mmol−1 s−1/5.5 L mmol−1 s−1, indicat-ing also how choice in medium or change in size can influencerelaxivities. These relaxivities of common CA are of the sameorder as those reported for MRI active MOFs (Table 2). Basedon this and the difficulties found when summarising theresults of MRI active MOF-nanoparticles in this review it issuggested to additionally analyse a commonly used, commer-cially available CA as a reference allowing for a better assess-ment of the multifactorial signal formation and to comparethe results of different particles and between different studies.

CAs are frequently classified according to their ability todecrease T1 in relation to their ability to decrease T2-relaxationtimes. Gd-CAs typically show a ratio <2 as just described abovefor Gd-DTPA. This means that these Gd-CAs can induce a signalenhancement in a T1-weighted MRI and hence are also calledpositive CAs. Negative CAs such as the superparamagnetic CAFerucarbotran (Resovist®, Bayer Healthcare), on the otherhand, are showing a much stronger T2-shortening effect com-

pared to the T1 shortening effect. Discussing the theory of thesignal mechanism of MRI CA here is beyond the scope andaim of this review and is described elsewhere indetail.85,89,91–94 The processes leading to the macroscopicallyvisible reduction of the relaxation times are also, especiallywith new and larger particles, a matter of ongoing discussion(e.g. ref. 88, 89, 94 and 95).

One important factor of interaction between CA and waterprotons is the fluctuating field that the magnetic active CA iscreating by its motion in the fluid (e.g. tumbling and rotation)affecting also the moving water molecules in the near sur-rounding. As motion is a major determinant, for instance, ofhow many water molecules are able to interact with the CA inthe time of the MR measurement, all experimental factorsrelated to motion may be of importance for the characteris-ation of MRI active MOF nanoparticles and should be statedwhere possible (see Appendix 2). Such factors could be the sizeor shape of the particle, and for larger particles, microstruc-ture, viscosity of the medium or the temperature of thesample.82,83,88,95

Typically, new nanoparticles are investigated by preparingsamples of these CAs in solutions of water, buffer or saline,and relaxivities, assuming a linear relationship of CA concen-tration and change of relaxation rate, are determined tocharacterise their MR activity (see eqn(5)). But going fromsuch a comparatively simple sample characterised in a con-trolled environment to a more complicated in vitro or even invivo object, one major difference will be that the particles arenot anymore homogeneously distributed in a single voxel and/or in a complete sample. A voxel will then comprise differentcompartments showing differing accessibility for the CA anddiffering water exchange rates between these compartments.Both factors will affect the signal because of the indirect signalmechanism of a CA in MRI. How the presence of compart-ments can affect relaxivities was described recently forexample by Knobloch et al.96 Knobloch et al. found linearbehaviour of relaxation rates in relation to the concentration ofthe USPIO ferumoxytol in saline or plasma allowing determi-

Fig. 2 Illustration of Appendix 2 “Suggestions for preparation, characterisation and for in vitro MRI measurements of MOF nanoparticles”.



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nation of relaxivities as described before but already non-linearbehaviour if examined in blood.96 Another potential biologicalfactor is the presence of proteins that can affect relaxivities asalready mentioned when the proteins, for example, bind to theCA.83,88 For in vivo applications coating/shell/surface functiona-lisation of a nanoparticle is necessary to avoid opsonisation ofthe particle by the immune system but the coating will alsoaffect the MRI properties (e.g. ref. 87 and 90) of the nano-particles because it modifies the access of water protons to theCA or simply changes the size of the particle.

The size of the CA-nanoparticle is a major determinant forthe MRI-capabilities of the CA in solution and of course in vivoconsidering the pharmacokinetics and the biodistribution ofthe particle affecting the accessibility of the particles todifferent tissue compartments (e.g. intravascular space as withlarge particles or extracellular space as with Gd-DTPA) orexcretion. Such determinants for drug transport and strategiesto enhance drug delivery were recently reviewed by Dewhirstand Secomb97 for the transport of drugs from vessels totumour tissue. Such determinants are related to the physicalmass transport with diffusional processes, transport in vessels,transport across vessel walls or penetration into tissue. As canbe seen in Table 3 the primarily envisioned biomedical appli-cation of MOF nanoparticles is also their use as a carriersystem to transport drugs to tumours.

Defining a future medical application of a MOF nano-particle may help to choose the appropriate MOF scaffold outof the 60 000 different crystal structures and functionalisationsthat can be added to these structures (Fig. 3). One of the mostimportant questions will then be related to patient safety.Safety issues as seen with currently available CA98,99 may limitthe range of possible MOF structures for clinical use consider-

ing potential toxicities. For example, standard clinical CAsbased on gadolinium are currently a matter of discussion. Thisis related to the leaching of Gd ions from the chelate complexduring their application especially when the CA cannot beexcreted fast enough, e.g. by patients with seriously impairedkidney function (e.g. ref. 98–100). Such safety issues demon-strate the need for alternative CAs (e.g. ref. 96 and 101) or newMRI methods that are more sensitive and hence reduce theamount of required Gd-based CA.

Three generalised concepts of MRI active MOF nano-particles were reported in the literature (Fig. 3) and will be dis-cussed in the following sections. Concepts are generalised interms of possible variations such as that there are multiplecores in one particle in concept II or could be located off-centre (Concept II, Fig. 3).102 Detailed information on MRIactive MOF nanoparticles is displayed in Tables 1–3.

MRI active MOFs

The metals in the inorganic building block unit of MOFs havebeen used to create MRI active MOF bulk and nanomaterials(Concept I, Fig. 3). From a material based perspective, theideal nanoconstruct is built from parts that fulfil a dedicatedfunction themselves.103 An example of this is a MOF nano-particle based on MR active IBU and an OBU with a thera-peutic function. However, MRI-CAs as mentioned above areusually based on metal chelates. Such complexes are chemi-cally extremely stable (probably more stable under biologicalconditions than any kind of MOF structure), minimising metalleakage in the body. In addition, deposition of the complexesin the body is highly unlikely after an intravenous injection,which is, on the other hand, a challenge with nanoparticles.Therefore, the use of toxic metals (e.g. gadolinium or manga-nese) for the construction of MOF nanoparticles may lead tobiocompatibility issues. Based on this fact it is believed thatMOF nanoparticles constructed from rather toxic metals willhave no medical application. However, the study of theirphysicochemical properties from a fundamental perspectiveproves to be highly interesting.

Gd-based MOFs

The majority of the clinically used MRI CAs are based on Gd3+

ions because of their large magnetic moment and therefore itis a natural approach to use also Gd-based MOF structures. Asmentioned above the key drawback of using Gd is its potentialhealth risk because of leaching of Gd ions in patients withseverely impaired kidney leading to prolonged circulationtime. Such risk found with Gd-CA may be also a major concernwith Gd-based MOFs. High relaxivities with low amounts ofGd would thus be a desirable goal.

Research on Gd-based MOFs already addresses a widerange of properties that are potentially relevant for MRI asmentioned above. Different nanoparticle shapes (block likeparticles,104 nanorods,104–108 thin plates,106,107,109,110 octa-hedral,104 and spindle-like108 nanoparticles) were achieved byvariation of linker molecules and synthesis methods (Table 1).

Fig. 3 Schematic illustration of the different (CA-)MOF NP conceptsand their MRI active centre(s) as reported in the literature. (I) Metalcentres of the MOF are responsible for MRI contrast. (II) The MOF shellis grown on MRI active nanoparticles. (III) MOF nanoparticles are func-tionalised with MRI active metal oxide nanoparticles on their externalsurface.



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Table 1 MRI active MOF nanoparticle formulations listed by reference with their characteristic properties relevant for relaxivity measurement (Table 2).The available information has been taken as stated from the references or has been deduced from graphs or instrumental information

(l) length; (w) width; (d) diameter; (t) thickness. aMeasured MOF was assumed to be Gd-BDC as the reference is missing an exact depiction (onlyreferred to as “Gd-MOF” for MRI). CA–MOF nanocomposites, Mn-MOFs, Gd-MOFs, and Fe-MOFs.



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Table 2 MRI active groups of the nanocomposites listed in Table 1 together with their r1 or r2 relaxivities and relevant experimental parameters. Thecolumn “No. ’/∼” refers to the numbers used in Table 1 indicating the different formulations and how relaxivities were calculated. The available infor-mation has been taken as stated from the references or has been deduced from graphs or instrumental information



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Hatakeyama et al. created four different MOF nano-particles based on the two linkers 1,4-BDC and 1,2,4-BTCwith average lengths between 24 nm and approximately1000 nm and studied the relaxivities (see Tables 1 and 2) ofthis collection of particles with respect to their sizes. Theauthors assumed cylindrical shapes when calculatingvolumes and surface areas except for the smallest particles,which were cube-like. Although different types of particleswere used, MR measurements in xanthan gum showed a clearsize dependence of the r2 values with the smallest particlesleading to the highest r2 value of 105.4 mM−1 s−1. Similarly,

r1 values increased with decreasing particle sizes but dis-played a peak for the second smallest particle at 83.9mM−1 s−1 and a lower value of 70.1 mM−1 s−1 for the smallestparticle. Thus, both r1 and r2 relaxivities increased with decreas-ing sizes of the cylindrically shaped particles. The r2/r1 ratio wasbetween 1.2 and 1.5 and thus similar to that of Magnevist® butwhen comparing relaxivities to the clinically used Magnevist®relaxivities were considerably higher (Table 2). The highestamount of Gd3+ per particle in the largest particle was notrelated with the highest r1 or r2. These findings emphasisethe importance of controlling size with respect to relaxivities.

′(per) metal ions/metal cluster; ∼(per) nanocomposite. aMagnetic field strength was identified by the type of MRI system (MesoMR60). bMediumwas extracted from graphics. c Calculated per mM Mn(II). dCalculated per mM Fe(III) + Co(II). eMagnetic field strength and relaxivities wereextracted from reference graphics. CA–MOF nanocomposites, Mn-MOFs, Gd-MOFs, and Fe-MOFs.



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Looking at the two smallest particles the trend seems lessclear and may indicate that more factors have to be con-sidered to explain the signal mechanisms. Promising is thatnot necessarily the largest particles with the highest amountof Gd3+ ions are the most effective MRI-CAs, leaving room tooptimise particles regarding increased relaxivity with a phar-macokinetically sensible size but without the need for highamounts of potentially harmful Gd3+.

Carné-Sánchez et al. studied the effect of field strength, pHand temperature on the relaxivities of [GdCu(DOTP)Cl]·4.5H2OMOF in physiological saline solution (0.9% w/w)112 (Table 2).Their work demonstrates how sensitive relaxivity is to chan-ging the magnetic field strength and emphasises why newMOF particles should be characterised with conditions asclose as possible to the intended future application. Forcurrent clinical use of MRI this would be 1.5 T or 3 T. Theauthors reported that their particles showed the highest r1(r1 ∼ 15 mM−1 s−1 at ∼1 T) at the range of clinical fieldstrengths. The effect of changing pH on r1 relaxivity was small

with no clear trend within the chosen pH range (pH 4–9). Anincrease of temperature seemed to increase r1. Changing tem-perature was considered a potential tool to investigate thesignal MRI mechanism.

Additionally to MRI, some of the work was also focused onthe preparation of the nanoparticles offering capabilities formore than one imaging modality in order to overcome thelimitations of a singular imaging method. Rieter et al. used Gd(BDC)1.5(H2O)2 nanorods doped with Eu3+ and Tb3+ foradditional luminescence imaging after excitation with UVlight106 and Tian et al. modified the surface of Gd(BDC)1.5(H2O)2 with poly(acrylic acid) chains for deposition ofgold nanoparticles for CT.107 Kundu et al. utilised the MOFsfor additional fluorescence imaging without modifying theMOFs by employing fluorescent linker molecules.108

Generally, the stability of nanoparticles is an importantaspect for their application and is especially important forgadolinium-based MOF nanoparticles. This issue wasaddressed by the work of Rowe et al., Carné-Sánchez et al. and

Table 3 Particle characterisation methods as well as additional biomedical relevant investigations on the nanocomposites are listed by reference

CA–MOF nanocomposites, Mn-MOFs, Gd-MOFs, and Fe-MOFs.



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Kundu et al. Rowe et al. stated that less than 1.12 µmol Gd3+

leached from the unmodified nanoparticles and less than0.07 µmol leached from polymer-modified MOF within12 hours in saline solution.110 Carné-Sánchez et al. observed amaximum leaching of 1.7% within 30 hours in saline solutionat pH 9 and 37.5 °C.112 At lower pH, lower Gd3+ leaching wasobserved. Kundu et al. used an MTT assay with their two typesof MOF nanoparticles and stated a cellular viability of 76%and 88%.108

Mn-based MOFs

Manganese (25Mn) is similar to Gd a potential candidate asIBU for MOF as it has also been used as CA Mn-DPDP(Teslascan®).85 Also similar to using Gd ions is that free Mnions can be toxic and thus leaching is also a matter ofconcern.

Applying the high crystallinity specification of MOF, therewas only one publication found using Mn ions as IBU. Thestudy by Taylor et al. covered two types of Mn-based MOFs: Mn(BDC)(H2O)2 nanorods and Mn3(BTC)2(H2O)6 as blocklike par-ticles or nanorods which exhibited r1 values up to 7.8mM−1 s−1 and r2 values up to 141.2 mM−1 s−1 at 3 T.113 Inparticular, r2 was therefore higher than the reported relaxi-vities for the Mn-CA Teslascan® at 3 T.83

Silica coated Mn3(BTC)2(H2O)6 were functionalised withRhodamine B and c(RGDfK) for optical imaging and cancertargeting, respectively.

A leaching test revealed that Mn3(BTC)2(H2O)6 released upto approximately 90% Mn2+ over the course of 30 hours andthat a surface coating with silica reduced the leaching to amaximum of less than 70%.

Fe-based MOFs

Iron-based MOF nanoparticles, where iron ions are the IBU ofthe MOF scaffold, can act as an alternative to Gd-based CAswith many opportunities for improvement because iron is anessential element that is present in abundance within thehuman body, and thus potential leaking of iron from MOFsseems less critical. Advantageously, most iron-based MOFs canbe synthesised in water or ethanol as opposed to possiblyharmful solvents, thus further eliminating the danger of poss-ible toxicity in the final material. Due to these attributes, iron-based MOF nanoparticles hold the potential to be used for awide range of biomedical applications.114

A range of different iron-based MOF nanoparticles havebeen studied with regard to their MRI properties (Table 2).

The various factors contributing to signal formation usingMRI-active nanoparticles can be very complicated and thus tounderstand these processes and as a requirement for optimi-sation, a comparison of different nanoparticles seems veryimportant to find out if specific modifications such as surfacefunctionalisation will result in a related change of MRI pro-perties. MIL-100(Fe) seems to be currently the only candidateto allow such a comparison as this MOF nanoparticle has beenstudied by 3 groups with characterisation of MRI properties(Table 2).90,114,115 The reason for the repeated use of

MIL-100(Fe) is that it is considered the most promising MOFnanocarrier.114

All three groups, Horcajada et al.,114 Zimpel et al.90 andSene et al.,115 studied unmodified MIL-100(Fe) nanoparticleswith similar sizes 200 nm, 130 ± 45 nm, and 155 nm (Table 1).Although the same type of MOF nanoparticles with similarsizes were investigated, relaxivities varied considerably(Table 2). Horcajada et al. reported an r2 value of 73 mM−1 s−1,Zimpel et al. 2.12 mM−1 s−1 mmol−1 of Fe3+, and Sene et al.10 ± 1 mM−1 s−1 mmol−1 of Fe3+. Similar variations can befound for r1 (Table 2). Apart from different nanoparticle sizesand different definitions for relaxivities, also other experi-mental settings can play a significant role potentially affectingrelaxometry. Thus, to allow comparability one prerequisite isthat experimental factors (Appendix 2) should be stated,allowing differences to be recognisable to others. One obviousdivergent experimental parameter here is that Horcajada et al.chose a 9.4 T apparatus, Sene et al. 4.7 T whereas Zimpel et al.used a clinical MRI system with a field strength of 1.5 T fortheir investigation. Furthermore, all three publications statedthe use of different solutions for MRI.

The nanoparticles of different types (Fig. 3) are even moredifficult to compare due to the additional variety in coatingsand cores. Furthermore, different measurement parameterswere utilised, making a comparison of the results difficult(Table 2).

The versatility of possible MOF functionalisation wasproved by creating a new type of nanoparticle that is visible inmultiple imaging modalities at the same time. Li et al.achieved near-infrared excited upconversion luminescencecapabilities by using a rare-earth-doped upconversion nano-particle core in a MIL-101_NH2 shell.102 Another example waspresented by Shang et al. who created composite nanoparticlesby growing a MIL-88A MOF shell layer on gold nanorods,allowing photoacoustic imaging (PAI) and CT.116

Besides functionalisation of the MOF scaffold itself, otherfunctions can be alternatively loaded or attached modalities(e.g. by adding dyes, CA, and tracer) to the porous nanoparticle.Shang et al.,116 for instance, reported loading of MIL-88A with afluorescence dye and Gao et al.117 reported loading of Fe-MIL-53-NH2 with a fluorescence dye. Zimpel et al. used differentsurface modifications on MIL-100(Fe) for fluorescence imagingas well as for targeting of KB cells.90

MTT assays in different cell lines were utilised in all publi-cations and no significant cytotoxicity of the nanoparticles wasfound, confirming the premise that these nanoparticles maybe safe for biomedical application.

In vivo MRI experiments on tumour bearing micewere performed by four groups using two differentapproaches.102,116–118 The two groups Gao et al. and Zhanget al. injected the nanoparticles directly into the tumour forsubsequent MR imaging. Whereas the groups Shang et al. andLi et al. injected the nanoparticles intravenously showing anaccumulation in tumours with CT, MRI and PAI in the formerand upconversion luminescence (UCL) together with MRI inthe latter.



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Contrast agent–MOF nanocomposites

One less commonly reported strategy to create MOF basednanoparticles with MR imaging capabilities presents the com-bination of already known CAs with MOF nanoparticles. In thefollowing text these CAs in combination with MOF are calledCA–MOF nanocomposites.

The approach allows for well-defined nanocarriers that canprovide both, the advantages of highly MRI active substancesfor imaging purposes as well as porous storage capacity byMOFs adjusted for the delivery of therapeutic drug molecules.As both components remain largely unmodified within thenanocomposite (neglecting interactions between the twospecies at their interface), their beneficial properties, like highrelaxivities for CAs or high drug loading capacities for specificMOFs, respectively, can be retained. Hence, CA–MOF nano-composites represent very promising candidates for appli-cations in the rather new field of medical theranostics.119

The formation of such CA–MOF has been achieved so far bytwo different ways (Concept II and III, Fig. 3). One approach(Concept II, Fig. 3) is growing a MOF on an MRI active metaloxide nanoparticle by immersing the particles in a metal salt/organic linker mixture under defined reaction conditions. In2015 three groups reported successful coating of pre-formedSPION cores with MOF shells.120–122 SPIONs (e.g. Fe3O4,γ-Fe2O3) were chosen because of their well-known good bio-compatibility and their significant influence on relaxationtimes, especially on T2.

87 In recent years, different coatings ofSPIONs based on metal–organic compounds have been investi-gated. Chowdhuri et al., for instance, focused their workon amorphous metal–organic shells.123,124 Concerning crystal-line MOF coatings, ZIF-8,120–122 UiO-66,125 ZIF-90,126 andMIL-100(Fe)127 MOFs were assembled onto spherical Fe3O4

nanoparticles, resulting in SPION-MOF nanocomposites withdifferent sizes (50 nm–250 nm) and shapes (Table 1). Theirmeasured transversal relaxivities (r2 ≈ 35 mM−1 s−1 to352 mM−1 s−1) were determined in vitro to be in good agree-ment with uncoated iron oxide based nanoparticles in clinicaluse, e.g. Feridex®/Endorem® or Resovist® (the literaturevalues: ≈40 mM−1 s−1 to 180 mM−1 s−1 in H2O

83).Comparison of the SPION-MOF nanocomposites (Tables

1–3) turned out to be difficult as their relaxivities were notequally defined and/or were not determined under the sameexperimental conditions such as magnetic field strength,temperature and medium (Table 2). Some of these core–shellparticles were further modified by adding functionalities,e.g. for a combination of more than one imaging modalityor for theranostic drug delivery (Table 3). Such additionalimaging properties included capabilities for e.g. in vivoMRI,120,122,125,127 CT121 or fluorescence imaging.120–122,127

Regarding functional drug delivery, the porous MOF scaffoldof the nanocomposites was loaded with an anti-cancer agent(i.e. doxorubicin120,121,125,126 or dihydroartemisinin127) and theparticles showed successful and significant tumour treatment(Fig. 5). Furthermore, all SPION-MOF nanocomposites weretested on cytotoxic effects of the particles themselves in vitro

and/or in vivo, respectively. In general, all nanocompositesshowed no cytotoxicity unless addition of chemotherapeuticswas performed (for a summary of additional investigations,see Table 3).

Fang et al. expanded the “CA–MOF core–shell approach”using gadolinium oxide (Gd2O3) as a core instead of SPION andmeasured the influence on longitudinal relaxation times (T1) toallow for a positive T1 contrast effect.

126 Qianwang Chen’s groupcoated Prussian blue or Mn3[Co(CN)6]2 (“C-MOF”) nanocubeswith different MOF shells (ZIF-8 or MIL-100(Fe), respectively) formultimodal imaging purposes and drug delivery.128–130 Theysuccessfully created nanocomposites which could be loadedwith drug molecules (doxorubicin, artemisinin/artesunate) andshowed significant therapeutic effect for cancer treatment.Furthermore, the nanocomposites provided good in vitro MRIproperties (Table 2). All three studies were able to follow the bio-distribution of the nanoparticles by T1- and T*

2 -weighted in vivoMRI, showing aggregation of the particles after 24 h in tumourtissue as well as e.g. in the liver or spleen. However, no damageto healthy tissue could be observed by histological analysis ofthe mice’s major organs.

Internalisation of CAs into the MOF is an interestingconcept for the fabrication of smart theranostic nanocarriers.Their ability to store drug molecules in the porous scaffold aswell as the possibility for further functionalisation of the exter-nal surface of the MOF shell by PSM combined with good MRIproperties of the CAs provides great potential in this field.Furthermore, the chance to stabilise less robust but good per-forming CAs inside a rigid MOF may also become anotheradvantage. On the other hand a reduced access of water to theCAs inside the MOF after loading with additional drug mole-cules and additional external surface functionalisation mightlead to new challenges. These are open questions and need tobe addressed in future.

A second strategy is the PSM on the external surface of MOFnanoparticles with CAs (Concept III, Fig. 3). Very recently, Seneet al. came up with this approach to create CA–MOF multi-functional nanoparticles. They decorated pre-synthesisedMIL-100(Fe) on their outer surface with USPIOs (maghemite;γ-Fe2O3) by simply mixing stable nanoparticle dispersions(MOF and iron oxide, respectively) under conditions wherethey exhibit different surface potentials. This resulted instrong electrostatic binding between the two species and, fur-thermore, a porous nanocomposite with high r2 relaxivities(Table 2). These good MRI properties were then used to followthe particle distribution in vivo after intravenous injection. T*

2

-weighted images of a mouse liver and spleen revealed a 50%signal intensity decrease right after the injection of the par-ticles, showing the feasibility for MRI.115 This type of compo-site particles were also loadable with the standard anti-tumourdrug doxorubicin forming a potential theranostic agent, butthe in vivo therapeutic efficacy together with in vivo toxicity ofsuch composites has not yet been fully tested.

Compared to the CA-shell/MOF-core approach discussed inthe upper part of this chapter, the attachment of CAs onto theMOF nanoparticles might lack some of the advantages. The



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stabilising effect on the CAs and the possibility for furtherfunctionalisation of the external surface of the MOF arethereby reduced. In contrast, diffusion of water molecules tothe MR active centre at the particle surface is facilitated, whichmight lead to an enhanced imaging contrast in vivo.

Both approaches provide interesting opportunities andshould be considered further in prospective research projectsin the field.

Conclusion and outlook

Three basic design concepts (Fig. 4) have been used to syn-thesise MRI active MOF containing nanoparticles showingconsiderable relaxivities. Despite defining MOF nanoparticlesmore strictly concerning crystallinity, the versatility of possiblenanoparticle designs is still impressing. This variety originatespartly from the versatility of usable MRI contrast mechanismsaiming, for instance, at a signal increase (T1) or a signaldecrease (T2 or T*

2) for a better detection. But transferringthese MRI active MOF materials to the clinical context isstill in an early stage with first encouraging in vivo studies(Fig. 5).

Comparability between different studies is currently a keychallenge. In order to improve comparability, one greaterobjective of this review was to establish general guidelines and

recommendations investigating the MRI activity of MOF nano-particles. As shown in this review the correlation of differentstudies is not straightforward because the factors that influ-ence MRI such as shape, size, agglomeration state, coating,MOF structure, and solvent are mutually connected. Therefore,it is difficult to vary individual properties in a MOF nano-particle while keeping the others constant. Detailed protocolson how MRI characterisation was done should form an inte-gral part of every investigation.

The authors believe that the most promising direction inthe future will include using the inherent properties of theMOF structure (e.g. their organic–inorganic hybrid nature,high surface area, biodegradability and potential MRI capabili-ties) and making use of selective functionalisation in theMOF’s scaffold for the synthesis of multifunctional MOF nano-particles. From the reviewed literature, there is already onefocus on iron-based MOFs such as MIL-100(Fe), which areregarded as very promising. The MRI active modality is an inte-gral part of the MOF scaffold and hence additional capabilitiesfor other imaging modalities and/or the transport of activeagents (e.g. drugs) are feasible. However, adding more func-tionality to a MOF nanoparticle leads to a more complex for-mulation that may be challenging to translate into a clinicalapplication.

This review suggests that besides making more MRI activeMOF nanoformulations, future efforts should also intensify

Fig. 4 TEM images of the different (CA-)MOF NP concepts for MRI which are shown schematically in Fig. 3. All TEM images were adapted with per-mission from references cited above. Copyright 2016129 and 2017115 Elsevier; Copyright 2008,113 2011,111 and 201690 American Chemical Society;Copyright 2016125 The Royal Society of Chemistry.



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investigations of the physicochemical parameters affecting theMRI signal. Monodisperse MOF nanoparticles with MRI activemetal as IBU seem to be the best model in which propertiessuch as shape, size, agglomeration state, coating, and solventcan be systematically varied.

Abbreviations

[CA] Concentration of CA5-FAM 5-Carboxyfluorescein5-FU 5-FluorouracilAES Atomic emission spectroscopyART ArtemisininAS ArtesunateB0 Magnetic induction field or magnetic flux (com-

monly called “magnetic field strength” in MRI)CA Contrast agentCLSM Confocal laser scanning (fluorescence)

microscopyCP Coordination polymerCpG-ODN Unmethylated cytosine–phosphate–guanine

oligonucleotidesCSD Cambridge Structural DatabaseCT Computed tomographyCy5 Cyanine 5 dyeDd Double distilledDLS Dynamic light scatteringDMEM Dulbecco’s modified Eagle’s mediumEDS/EDX Energy-dispersive X-ray spectroscopyEELS Electron energy loss spectroscopyEM Electron microscopyFA Folic acid

FBS Fetal bovine serumFM Fluorescence microscopyFOI Multicolor fluorescence optical imagingGRE Gradient echo sequenceGRGDS Glycine-arginine-glycine-aspartate-serineIBU Inorganic building unitICG Indocyanine greenICP Inductively coupled plasmaIR Infrared spectroscopyIUPAC International Union of Pure and Applied

ChemistryMOF Metal–organic frameworkMR Magnetic resonanceMRI Magnetic resonance imagingMS Mass spectroscopyMTX MethotrexateNMR Nuclear magnetic resonanceOBU Organic building unitPAA Poly(acrylic acid)PAI Photoacoustic imagingPB Prussian bluePBS Phosphate-buffered salinePD Proton densityPDMAEA Poly-(2-(dimethylamino) ethyl acrylate)PEG Polyethylene GlycolPFMA Poly(fluorescein O-methacrylate)PHPMA Poly[N-(2-hydroxypropyl) methacrylamide]PNAOS Poly(N-acryloxysuccinimide)PNIPAM Poly(N-isopropylacrylamide)PPEGMEA Poly(((poly)ethylene glycol methyl ether) acrylate)PSM Postsynthetic modificationPSty PolystyreneRF Radio frequency

Fig. 5 Two examples of in vivo MRI studies at 3 T applying MRI active MOF nanoparticles to tumour bearing mice. Study I demonstrated the in vivoantitumour efficacy of Fe3O4@UiO-66-DOX nanoparticles125 I(a) shows MR images of tumour bearing mice at different time points before and afterintravenous injection of either Fe3O4@UiO-66-DOX nanoparticles in the upper row of images or in a control group using PBS below. The red circlesmark the tumour regions. I(b) shows volumes of tumour collected from both groups of mice on day 30. Study II investigated PB@MIL-100(Fe) forin vivo MRI.129 II(a) and II(b) show T1 and T*

2 weighted images acquired at different time points before and after intravenous injection of PB@MIL-100(Fe)nanoparticles. Figures adapted with permission from ref. 125 and 129. Copyright 2016 The Royal Society of Chemistry and Copyright 2016 Elsevier,respectively.



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ri Relaxivity for T1 (i = 1) or T2 (i = 2)Ri Relaxation rate (1/Ti, i = 1,2)RT Room temperatureSEM Scanning electron microscopySI Signal intensitySNR Signal-to-noise ratioSPION Superparamagnetic iron oxide nanoparticleSTEM Scanning transmission electron microscopyStp10-C Succinoyl-tetraethylene pentamin-10-cysteinT TemperatureTEM Transmission electron microscopyTGA Thermogravimetric analysisTPF Two-photon fluorescence imagingUCL Upconversion luminescenceUCNP Upconversion nanoparticlesUSPIO Ultrasmall superparamagnetic iron oxideXPS X-ray photoelectron spectroscopyXRD X-ray diffractionZeta Zeta-potential measurementsα Flip angle (RF-pulse) by which the magnetisation

is tilted from the z-direction into the xy-planeγ Gyromagnetic ratioΔBinhom Magnetic field inhomogeneity across a voxel

Conflicts of interest

There are no conflicts to declare.

Appendix 1 | MRI principle – selectedequations

Approximate macroscopic magnetisation:

M0 ffi NIðI þ 1Þℏ2γ2B0

3kTð1Þ

N denotes nuclear spin density of water protons, I spinquantum number, γ gyromagnetic ratio, B0 magnetic fluxdensity (commonly called “magnetic field strength”), kBoltzmann constant, and T temperature.

MRI-signal intensity equations for two basic pulse sequences:81,92

MRI-signal intensity equation of a spin echo pulse sequence(SE):

SISE ¼ M0ð1� e�TR=T1Þe�TE=T2 ð2ÞMRI signal intensity equation of a spoiled gradient echo pulsesequence (GRE):

SIGRE ¼ M0sin α � ð1� e�TR=T1Þ1� cos α � e�TR=T1

e�TE=T*2 ð3Þ

TE denotes echo time, TR repetition time, α flip angle, T1longitudinal, and T2 or T*

2 transverse relaxation time in SE andGRE, respectively.

Signal-to-noise ratio (SNR):81

SNR/ ðvoxel volumeÞ �ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiacquisition time

pð4Þ

Contrast agent relaxivity ri:

Ri ¼ 1Ti

¼ 1Ti0

þ ri ½CA� ð5Þ

Ri denotes relaxation rate (= 1/relaxation time Ti, i = [1,2]) afteradding the contrast material of concentration [CA] whereasTi0 is the respective relaxation time without the CA. [CA]may refer to the concentration of the MRI active metal ion/particle cluster or to the concentration of the particle. In equi-valent calculations for T*

2 , relaxivity should be named accord-ingly as r*2.

Appendix 2 | Suggestions for thepreparation, characterisation andin vitro MRI measurements of MOFnanoparticles

Both the wide range of MR parameters and the physiochemicalproperties of the MR active nanoparticles require a detaileddescription of the measurement settings as well as descrip-tions of the nanoparticles, including their synthesis, functio-nalisation, and characterisation. In order to improve the com-parability between different studies (e.g. the results of differentand/or similar nanoparticles) the following details arerecommended:

Synthesis

The preparation of monodisperse colloidal stable nano-particles is a key challenge in nanoscience. However, as nano-particle properties are size-dependent the precise control oftheir size proves difficult but vital when ensuring reproducibleresearch results. The synthesis of the reference or controlsamples along with a comparison of the new experimentalvalues (e.g. MRI values) with reference data is advised.

Characterisation

After synthesising nanoparticles the importance of a compre-hensive characterisation should not be underestimated. Inorder to elucidate size determination, a comparison of theresults from different solid-states (e.g. scanning electronmicroscopy (SEM) and transmission electron microscopy(TEM)) and dispersion-based methods (dynamic light scatter-ing (DLS)) of every new nanoparticle batch combined with thereference samples is advised.47 Obtaining similar results forsize distribution and morphology from different nanoparticlebatches and reference samples should ensure the productionof reproducible results for further work.

Agglomeration or decomposition

Sample stability is a major concern regarding nanoparticlecharacterisation and application. A simple test with MRI



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would involve the consecutive imaging of the sample with afast imaging method, investigating signal intensity changesover a period of time which is relevant to the actual MR charac-terisation, i.e. the determination of the T1 and T2 relaxationtimes, of the sample that can last several minutes. Anotherapproach would be the application of a fast pulse sequence atboth the beginning and at the end of the MRI measurements.By comparing signal intensities, changes would indicatesample degradation.

Coatings and surface modification

Ideally unmodified nanoparticles should be characterisedtogether with the modified particles under the same con-ditions. Agglomeration of the unmodified nanoparticles (e.g.in body fluids) is typically a major (if not the main) challenge.The embedment of nanoparticles in gels offers a way of charac-terising both unmodified and modified nanoparticles underthe same experimental conditions.

Solution

The used solution should be stated because the solution typecan change the MRI results and even affect different nano-particles in a variety of ways. It is therefore useful to character-ise a sample containing only the solution without the nano-particles as a reference. Furthermore, the temperature, pH andviscosity of the solution may also affect the relaxivities.

Reference

Reference substances are useful to judge whether experimentalconditions are comparable regarding different experimentsand different batches. A clinically approved, commerciallyavailable CA is suggested to allow for an assessment of thequality of MRI experiments.

Concentration range of CA/nanoparticle

Determination of the relaxivities in MRI assumes a linearrelationship of concentration and relaxation rates. For highconcentrations, this may not be valid anymore and thus therange of concentrations should be stated.

MRI protocol/measurement

Typically, relevant parameters include: the type of system, fieldstrength, receive coils used, type of pulse sequence togetherwith the relevant parameter settings (e.g. bandwidth, TR, TE,inversion time, flip angle, and temporal/spatial resolution)and other acquisition parameters such as applied interp-olation, sampling techniques or parallel imaging. Informationon postprocessing procedures may also be valuable.

Relaxivity

If relaxivities are determined, it should be stated whether theywere calculated with respect to the molar concentration ofnanoparticles or the MR active metal ions. Ideally, both valuesshould be stated because they highlight different aspects ofthe MRI signal mechanism.

Reproducibility/repeatability of the experiment

Due to the difficulties in sample preparation and the limit-ations of the precision in MRI, repeated measurements andrepetitions of the full procedures give an insight into therepeatability of the experiments.

Acknowledgements

The authors are grateful for financial support from theDeutsche Forschungsgemeinschaft (DFG) through DFG-projectWU 622/4-1 and PE 925/3-1, the Excellence ClusterNanosystems Initiative Munich (NIM) and the Center forNanoScience Munich (CeNS). Furthermore, we thank Prof.Dr Olaf Dietrich, Dr Martin Hossann, Dr Michael Ingrisch,and Dr Barbara Kneidl for their help and for discussion.

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