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In Vivo Visualization of Alzheimer’s Amyloid Plaques by MRI in Transgenic Mice Without a Contrast Agent 1 Department of Radiology and MR Research Laboratory, Mayo Clinic College of Medicine 2 Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School 3 Molecular Neurobiology Laboratory, Departments of Neurology, Neuroscience, and Biochemistry/Molecular Biology, Mayo Clinic College of Medicine *Corresponding Author: Clifford R. Jack Jr., M.D., Mayo Clinic, Diagnostic Radiology, 200 First Street SW, Rochester, MN 55905, Phone: 507-284-8548 FAX: 507-284-2405 4Present Address: Department of Biomedical NMR and National Bio-NMR Facility, A.I. Virtanen Institute, University of Kuopio, Kuopio, Finland The publisher's final edited version of this article is available at Magn Reson Med. See other articles in PMC that cite the published article.Abstract One of the cardinal pathologic features of Alzheimer’s disease (AD) is formation of senile, or amyloid, plaques. Transgenic mice have been developed that express one or more of the genes responsible for familial AD in humans. Doubly transgenic mice develop “human-like” plaques, providing a mechanism to study amyloid plaque biology in a controlled manner. Imaging of labeled plaques has been accomplished with other modalities, but only MRI has sufficient spatial and contrast resolution to visualize individual plaques non-invasively. Methods to optimize visualization of plaques in vivo in transgenic mice at 9.4 T using a spin echo sequence based on adiabatic pulses are described. Preliminary results indicate that a spin echo acquisition more accurately reflects plaque size, while a T2* weighted gradient echo sequence reflects plaque iron content not plaque size. In vivo MRI – ex vivo MRI – in vitro histological correlations are provided. Histologically verified plaques as small as 50 μm in diameter were visualized in the living animal. To our knowledge this work represents the first demonstration of non-invasive in vivo visualization of individual AD plaques without the use of a contrast agent. Keywords: MR microscopy, Alzheimer’s Disease, Magnetic Resonance Imaging, Transgenic mice Introduction Alzheimer’s disease (AD) is a slowly progressive neurodegenerative disorder with an insidious clinical onset. Above 65 years of age, AD increases in incidence exponentially with age and is therefore poised to become a leading public health problem as the population ages (1). At this time, no diagnostic biomarker exists. The antemortem diagnosis as well as longitudinal assessment of disease progression are based on clinical and neuropsychometric measures (2). Due to the anticipated arrival of useful therapeutic interventions for AD, improved methods of diagnosis and measures of disease progression are needed (3). Recent evidence in genetics and cell biology have led to general acceptance that the initiating event ultimately leading to clinical AD is disordered metabolism of amyloid in the brain (4). Amyloid precursor protein (APP) is a normal transmembrane protein found in cells throughout the body. Amyloid β peptide (Aβ) is one of the products of normal metabolic turnover of APP in the brain. Aβ is a major component of extracellular senile (or amyloid) plaques, and, aggregation of extracellular Aβ fragments are thought to be the initiating event in plaque formation. Soluble Aβ polymers are neurotoxic. While plaques themselves may or may not be directly neurotoxic, plaque burden is a measure of the antecedent biochemical events ultimately leading to clinical AD. The three known types of mutations associated with early onset, familial AD all directly effect amyloid metabolism (4). Murine models of AD have been created by inserting one or more of these human mutations into the mouse genome (5, 6). These transgenic mice display extensive plaque formation, whereas plaques are not found in wild type mice. Amyloid reduction in humans has recently been identified as a major therapeutic objective (7). Alzheimer’s transgenic mice allow controlled study of this phenomenon and enable testing of anti-amyloid interventions that might be useful in humans. Direct imaging of amyloid in the brain is feasible. Plaque binding scintigraphic probes label plaques in animal and human specimens in vitro, and in vivo in mice (8–11). Klunk et al (12) have successfully visualized plaque burden with positron emission tomography (PET) in living human Alzheimer’s patients using the “Pittsburgh-B” compound. Optical imaging of individual probe labeled plaques has also been demonstrated (13). Despite this success with other modalities, several groups have pursued imaging of amyloid plaques with MRI (14–19). A major motivation for this effort is that, unlike other modalities, MRI theoretically can resolve individual plaques noninvasively. Typical plaques in human AD subjects range from 2 μm to 200 μm in diameter which is beyond the spatial resolution of PET. Beneviste et al (14) demonstrated individual plaques on in vitro human tissue slices using MR microscopy. This was accomplished at 7 T at a spatial resolution in the range of 40 μm × 40 μm × 40 μm (~ 6 × 10 −5 mm3). Plaques appeared dark on T2*-weighted images and this was attributed to the known presence of metals, particularly iron, in plaques. This finding was not replicated by Dhenian at 11.7 T (16). However, our group (15) and later Zhang et al (19) and Helpern et al (18), did demonstrate imaging of plaques in ex vivo transgenic mouse brain specimens at 7 T without administration of an exogenous contrast agent on T2 or T2*-weighted images, thus replicating the findings of Beneviste et al (14). We also demonstrated enhancement of plaques ex vivo both on T2 and T1-weighted images following intra-venous (IV) administration of a specifically designed molecular contrast agent (15). However, imaging times in these experiments ranged from 13–15 hours which is clearly unsuitable for in vivo imaging. In this report, we discuss optimization of methods to visualize individual plaques in transgenic mice in vivo on T2-weighted images without the aid of an exogenous plaque specific contrast agent. Documentation is provided via three-way in vivo MRI - ex vivo MRI in vitro histological correlation. Methods Imaging Methods Experiments were performed with a Unity Inova spectometer (Varian, Palo Alto, CA) which was interfaced to a 9.4 T/31 cm horizontal bore magnet equipped with actively-shielded gradients capable of 300 mT/m in a rise-time of 500 μs (Magnex Scientific, Abingdon, UK). RF transmission and reception was performed with a quadrature surface coil consisting of 1 cm diameter loops (Fig 1
We took a two stage approach to in vivo imaging of individual amyloid plaques. First, several decisions about basic imaging approaches were driven by a priori specifications. Remaining methodological decisions were then made empirically. The transgenic mice employed in our experiments were doubly transgenic for human APP and presenilin mutations (APP-PS1 mice) (6). As in affected humans, plaque number and mean plaque size increase with age in transgenic mice. In these mice, mean plaque sizes are 19 μm (4 μm min, 83 μm max) at age 12 months, and 26 μm (4 μm min, 109 μm max) by age 24 months (20). Given this constraint, we predetermined an in-plane resolution of 60 μm × 60 μm for our experiments. Through-plane resolution was determined empirically. We found older APP-PS1 transgenic mice to be somewhat physiologically fragile, and thus not able to withstand excessively long anesthesia sessions. We therefore targeted an image acquisition time of 1–2 hours maximum. This approach allowed us to perform several experiments per imaging session in a single animal, with an upper limit of roughly six hours of imaging/anesthesia time per session. Given competing constraints of high spatial resolution but limited imaging time, we adopted the strategy of limited-field-of-view (FOV) imaging. As will be discussed later, we pursued long TE spin echo rather than gradient echo sequences. A single echo sequence was used in order to avoid spatial resolution blurring arising from T2 decay during a multi-echo acquisition. We performed imaging in the coronal plane for two reasons. First, this orientation lends itself well to imaging with a surface coil which improves local signal-to-noise ratio (SNR) over volume coil acquisitions. Second, images are acquired in the same orientation in which typical histological sectioning is performed. In vivo and ex vivo MR images were reconstructed with zero padding in x and y, doubling the apparent resolution in plane. Remaining MRI acquisition parameters were determined empirically using in vivo transgenic and wild type mice, as well as ex vivo fixed brain specimens of transgenic mice. To reduce the FOV in the two phase-encoded directions, “zoom imaging” was performed using two frequency-selective 180° pulses (21). Flip-angle imperfections were minimized by employing only adiabatic pulses in the 3D imaging sequence (Fig. 2
Initial attempts at in vivo imaging using the spin echo sequence with parameters from the optimization experiments above revealed that a method of cardio-respiratory triggering of the sequence was necessary (24). Although it is possible to artificially ventilate mice and acquire data during fixed expiration, we elected not to pursue this approach. In addition to being technically challenging, the physiologic fragility of older AD transgenic mice was problematic. We therefore elected to perform imaging during free breathing. We employed an MR compatible physiologic monitoring device for these experiments (SA Instruments, Inc.). Electrocardiographic (ECG) monitoring was derived from disposable surface electrode pads placed on the shaved left fore limb and right hind limb (Nicolet Biomedical). Respiration was monitored using a pressure transducer placed under the mouse’s abdomen. Triggering signals were derived from the ECG and respiratory sensors. An MRI acquisition was triggered by the first QRS complex detected after expiration. A custom made device was used to immobilize the head during imaging (Figure 1 Animal and Brain Tissue Handling Experiments were performed using both APP-PS1 transgenic and B6SLJ wild type mice. Mice were anesthetized using 1.0% – 1.5% isoflurane and O2/N2O and positioned in a custom built cradle for imaging (Figure 1 Some animals were sacrificed to perform correlations with ex vivo MRI and in vitro histology. These animals were perfused with phosphate buffered saline and fixed with neutral buffered, 10% formalin following an overdose with sodium pentobarbital (200 mg/kg, IP). The brain was removed and fixed further in formalin over night and equilibrated in 0.1 M sodium phosphate, pH 7.4 for 24 hours. The brain was embedded vertically in 2% agar in a 15 mm outer diameter. glass tube for ex vivo MRI. For histological staining, the bottom of the glass MRI tube was cut off and the fixed mouse brain embedded in agar was extruded. The agar was cut away from the mouse brain. A 5 mm thick block of agar was left attached to the posterior portion of the brain as a base for mounting to the microtome platform in order to maintain the same orientation histologically as in the MRI scan. After cryoprotecting in 10% followed by 30% sucrose in 0.1 M phosphate, pH 7.4, frozen coronal sections (30 μm) were cut with a sliding microtome throughout the whole extent of the cerebral cortex. The sections were mounted on slides, dried, and then stained with fresh, filtered, aqueous 1% thioflavin S. The thioflavin S-positive beta-amyloid plaques were visualized with a florescence microscope using filters for fluorescein isothiocyanate (FITC). In order to visualize tissue iron, the Prussian Blue reaction was performed (27). Mounted 30 μm sections were reacted with equal parts of freshly made, aqueous 10% potassium ferrocyanide and 20% hydrochloric acid for 30 min. The sections were rinsed for five minutes in three changes of distilled water, cover-slipped, and then imaged without counterstaining. Ex Vivo MRI and In Vitro Histological Correlation to In Vivo MRI Correlating anatomic features between in vivo and ex vivo MR images of the same mouse was accomplished using an image analysis software package with a linked cursor system (28). The ex vivo MRI volume was spatially matched to the in vivo volume using common anatomic landmarks, for example the ventricles, corpus callosum, hippocampal fissure, etc. The ex vivo MRI volume was re-sampled in the space of the in vivo volume using a windowed sinc interpolation algorithm. In order to correlate histological sections with MR images, images of the individual histological sections were combined to create a digitized 3D volume of the specimen. In order to match the through-plane resolution of the histological and MR images, appropriate multiples of the 30 μm histological sections were used. The digitized histological volume was then spatially matched to the ex vivo MRI volume using common anatomic landmarks as described above. A linked cursor system in the image analysis software program was then used to identify amyloid plaques common to the three spatially registered digitized datasets; in vivo MRI, ex vivo MRI, and in vitro histology. Results Variable slice thickness was evaluated with ex vivo MRI using a fixed transgenic mouse brain. In-plane resolution was held constant at 60 μm × 60 μm, through-plane resolutions were varied as follows; 60, 90, 120, 180, and 270 μm (Figure 3
We were not able to resolve individual plaques on in vivo T2 weighted images without cardio-respiratory triggering. Although cardio-respiratory triggering improved in vivo image quality, unpredictable fluctuations in respiratory depth and in the amplitude of the detected ECG signal over time led to occasional significant variation in TR from view-to-view. This, in turn, produced view-to-view variation in steady state magnetization and resulting image artifacts. The trigger desensitizing modification of the sequence proved to be an effective solution to this problem. This is illustrated with in vivo MRI - ex vivo MRI correlation in a 24 month old transgenic mouse (Figure 4
Three-way in vivo MRI - ex vivo MRI in vitro histological correlation in a 26 month old transgenic mouse reveals excellent correlation between individual plaques visualized on MRI and the thioflavin S stained plaques in the spatially registered histological sections (Figure 5
We evaluated a T2* sequence for in vivo MRI, and in the process identified several undesirable properties of this type of sequence. We noticed that the T2* weighted sequence did not resolve smaller plaques that were clearly resolved with the spin echo sequence (Fig 7
Discussion To our knowledge these results represent the first in vivo images of individual amyloid plaques without the aid of an exogenously administered contrast agent. We have shown that plaques with diameters as small as 50 μm can be successfully visualized in the living animal without a contrast agent (Fig 5 Plaque sizes in human AD tissue range up to 200 μm, which is roughly twice the maximum size observed in transgenic mice. There is no reason in principle that this approach could not be extended to humans. It would, however, require improvements in instrumentation that would permit imaging with similar contrast-to-noise, at slightly lower spatial resolution, in roughly 1/6 the imaging time used in these mouse experiments. With the growing awareness of the feasibility of human imaging at ultrahigh fields (≥ 7T) and improvements in RF coil technology, human applications of this approach may be possible in the future. We acknowledge the nonspecificity of dark areas on T2-weighted images for plaques. For example, areas of microhemorrhage, or heavily myelinated fiber tracts may also appear dark on T2-weighted images (15). We do not believe that this necessarily diminishes the utility of plaque imaging with MRI. In the context of imaging transgenic AD mice, one can be reasonably sure that most dark areas visualized do indeed represent plaques. And, imaging of transgenic mice is not performed for purposes of clinical diagnosis. In humans, however, subtle signs are often critical for early diagnosis. In this setting, diagnostic misinterpretation of microhemmorhages for plaques or vice versa may not be acceptable. The non-specificity of dark areas on T2-weighted images does motivate pursuit of plaque specific MRI contrast probes as a way to impart imaging specificity at the tissue level (15, 17, 29, 30). In addition, molecular specific probes increase the sensitivity for plaque detection. Our own data has demonstrated that while plaques are visible ex vivo without contrast, plaque to background contrast-to-noise increases roughly two times on T2-weighted images following contrast injection (15). And, plaque to background contrast-to-noise increases to nine times following contrast injection on T1-weigthed images (15). Wadghiri et al. (17) recently demonstrated MRI visualization of plaques in vivo and ex vivo at 7 T in transgenic mice after disruption of the blood-brain-barrier by mannitol and injection of a plaque specific contrast agent. They were unable to visualize plaques without a contrast agent. Plaque visualization is an application that presses the limit of the resolving capability of in vivo MRI. We believe the most likely explanation for the discrepancy between results of Wadghiri et al. (17) and our own lies with the imaging strategy employed. Wadghiri et al. (17) employed through-plane resolutions of 270 μm or greater. In vivo imaging was also done without physiologic monitoring or triggering. It may be that other aspects of the strategy we adopted - e.g., restricted FOV imaging and trigger desensitizing to minimize view-to-view B0 variation - are also helpful. We have focused efforts on T2 imaging of individual plaques without a contrast agent. The same imaging principles however can be ported directly to T1-weighted sequences. While enhancement of individual plaques on MRI with the aid of targeted contrast probes shows a promising future in this field, the ability to visualize plaques pre-contrast will be an important aspect of contrast enhanced plaque studies. Because of the demanding spatial resolution requirements, extremely accurate spatial registration between pre and post contrast images is necessary in order to accurately measure the imaging features of contrast agent behavior — for example time course, dose response, etc. Individual plaques serve as intrinsic fiducial markers which can facilitate precise registration (with the caveats outlined below) between pre and post contrast enhanced exams. The same principle holds true for spatial registration of serial MRI studies. Although many plaques in each section could be unequivocally matched between the histological and MR images (in vivo and ex vivo), some plaques visible in the histological section were not visible on MRI and visa versa. In reality perfect one-to-one correspondence between every plaque in the MRI and histological images was not possible. The histological sections were 30 μm and the MRI slices were 120 μm. Differences in partial volume averaging between MRI and histology were inevitable. In addition, the histological specimens were sliced manually. Even for a highly skilled individual, it is impossible to create sections with perfect 30-μm uniformity throughout each section. With MRI however, tissue was sectioned in a perfectly rectilinear grid, and therefore, some mismatch of within-section thickness between the MRI and histological preparation was unavoidable. Current evidence points to a T2 effect due to static microscopic field gradients from iron deposition in plaque as the primary source of MRI contrast between plaques and background tissue (14, 31). Use of a gradient recalled echo sequence to impart T2* weighting would therefore seem to be an obvious approach. In addition, a 3D gradient echo sequence would be more time efficient than a spin echo sequence. There are several reasons we decided to pursue the long TE spin echo sequence outlined in this work. First, as illustrated in Figure 7 Acknowledgments The authors wish to thank Dawn M. Gregor, B.S., for mouse breeding and genotyping, and Robert Schlentz, Ph.D. for technical assistance Grant Support: NIH AG022034, NIH RR08079, and the W.M. Keck Foundation References 1. Evans DA, Funkenstein HH, Albert MS. Prevalence of Alzheimer’s disease in a community population of older persons. JAMA. 1989;262:2551–2556. [PubMed] 2. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA work group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology. 1984;34:939–944. [PubMed] 3. Growdon JH. Biomarkers of Alzheimer disease. Arch Neurol. 1999;56:281–283. [PubMed] 4. Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science. 2002;297:353–356. [PubMed] 5. 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JAMA. 1989 Nov 10; 262(18):2551-6.
[JAMA. 1989]Neurology. 1984 Jul; 34(7):939-44.
[Neurology. 1984]Arch Neurol. 1999 Mar; 56(3):281-3.
[Arch Neurol. 1999]Science. 2002 Jul 19; 297(5580):353-6.
[Science. 2002]Science. 2002 Jul 19; 297(5580):353-6.
[Science. 2002]Science. 1996 Oct 4; 274(5284):99-102.
[Science. 1996]Nat Med. 1998 Jan; 4(1):97-100.
[Nat Med. 1998]Nature. 1999 Jul 8; 400(6740):173-7.
[Nature. 1999]Neurobiol Aging. 1995 Jul-Aug; 16(4):541-8.
[Neurobiol Aging. 1995]Ann Neurol. 2004 Mar; 55(3):306-19.
[Ann Neurol. 2004]Proc Natl Acad Sci U S A. 2003 Oct 14; 100(21):12462-7.
[Proc Natl Acad Sci U S A. 2003]Proc Natl Acad Sci U S A. 1999 Nov 23; 96(24):14079-84.
[Proc Natl Acad Sci U S A. 1999]Magn Reson Med. 2004 Mar; 51(3):452-7.
[Magn Reson Med. 2004]Proc Natl Acad Sci U S A. 1999 Nov 23; 96(24):14079-84.
[Proc Natl Acad Sci U S A. 1999]Neurobiol Dis. 2002 Nov; 11(2):315-29.
[Neurobiol Dis. 2002]Magn Reson Med. 2004 Mar; 51(3):452-7.
[Magn Reson Med. 2004]Magn Reson Med. 2004 Apr; 51(4):794-8.
[Magn Reson Med. 2004]Nat Med. 1998 Jan; 4(1):97-100.
[Nat Med. 1998]Neuroscience. 2000; 101(4):939-44.
[Neuroscience. 2000]J Magn Reson Imaging. 2004 Feb; 19(2):229-37.
[J Magn Reson Imaging. 2004]Radiology. 1989 Oct; 173(1):255-63.
[Radiology. 1989]Neurobiol Dis. 2002 Nov; 11(2):315-29.
[Neurobiol Dis. 2002]Neuroscience. 2000; 101(4):939-44.
[Neuroscience. 2000]Neurobiol Dis. 2002 Nov; 11(2):315-29.
[Neurobiol Dis. 2002]Magn Reson Med. 2003 Aug; 50(2):293-302.
[Magn Reson Med. 2003]Nat Biotechnol. 2000 Aug; 18(8):868-72.
[Nat Biotechnol. 2000]Biochemistry. 2004 May 25; 43(20):6064-75.
[Biochemistry. 2004]Proc Natl Acad Sci U S A. 1999 Nov 23; 96(24):14079-84.
[Proc Natl Acad Sci U S A. 1999]J Neurol Sci. 1998 Jun 11; 158(1):47-52.
[J Neurol Sci. 1998]JAMA. 1989 Nov 10; 262(18):2551-6.
[JAMA. 1989]Ann Neurol. 2004 Mar; 55(3):306-19.
[Ann Neurol. 2004]