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Item Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging(Wiley, 2025) Jelescu, Ileana O.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Barrett, Rachel L. C.; Aggarwal, Manisha; Michielse, Stijn; Nasrallah, Fatima; Syeda, Warda; Wang, Nian; Veraart, Jelle; Roebroeck, Alard; Bagdasarian, Andrew F.; Eichner, Cornelius; Sepehrband, Farshid; Zimmermann, Jan; Soustelle, Lucas; Bowman, Christien; Tendler, Benjamin C.; Hertanu, Andreea; Jeurissen, Ben; Verhoye, Marleen; Frydman, Lucio; van de Looij, Yohan; Hike, David; Dunn, Jeff F.; Miller, Karla; Landman, Bennett A.; Shemesh, Noam; Anderson, Adam; McKinnon, Emilie; Farquharson, Shawna; Dell'Acqua, Flavio; Pierpaoli, Carlo; Drobnjak, Ivana; Leemans, Alexander; Harkins, Kevin D.; Descoteaux, Maxime; Xu, Duan; Huang, Hao; Santin, Mathieu D.; Grant, Samuel C.; Obenaus, Andre; Kim, Gene S.; Wu, Dan; Le Bihan, Denis; Blackband, Stephen J.; Ciobanu, Luisa; Fieremans, Els; Bai, Ruiliang; Leergaard, Trygve B.; Zhang, Jiangyang; Dyrby, Tim B.; Johnson, G. Allan; Cohen-Adad, Julien; Budde, Matthew D.; Schilling, Kurt G.; Neurology, School of MedicineSmall-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the resultant data. This work aims to present selected considerations and recommendations from the diffusion community on best practices for preclinical dMRI of in vivo animals. We describe the general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss why some may be more or less appropriate for different studies. We, then, give recommendations for in vivo acquisition protocols, including decisions on hardware, animal preparation, and imaging sequences, followed by advice for data processing including preprocessing, model-fitting, and tractography. Finally, we provide an online resource that lists publicly available preclinical dMRI datasets and software packages to promote responsible and reproducible research. In each section, we attempt to provide guides and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should focus. Although we mainly cover the central nervous system (on which most preclinical dMRI studies are focused), we also provide, where possible and applicable, recommendations for other organs of interest. An overarching goal is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.Item Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 2-Ex vivo imaging: Added value and acquisition(Wiley, 2025) Schilling, Kurt G.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Howard, Amy F. D.; Barrett, Rachel L. C.; Aggarwal, Manisha; Michielse, Stijn; Nasrallah, Fatima; Syeda, Warda; Wang, Nian; Veraart, Jelle; Roebroeck, Alard; Bagdasarian, Andrew F.; Eichner, Cornelius; Sepehrband, Farshid; Zimmermann, Jan; Soustelle, Lucas; Bowman, Christien; Tendler, Benjamin C.; Hertanu, Andreea; Jeurissen, Ben; Verhoye, Marleen; Frydman, Lucio; van de Looij, Yohan; Hike, David; Dunn, Jeff F.; Miller, Karla; Landman, Bennett A.; Shemesh, Noam; Anderson, Adam; McKinnon, Emilie; Farquharson, Shawna; Dell'Acqua, Flavio; Pierpaoli, Carlo; Drobnjak, Ivana; Leemans, Alexander; Harkins, Kevin D.; Descoteaux, Maxime; Xu, Duan; Huang, Hao; Santin, Mathieu D.; Grant, Samuel C.; Obenaus, Andre; Kim, Gene S.; Wu, Dan; Le Bihan, Denis; Blackband, Stephen J.; Ciobanu, Luisa; Fieremans, Els; Bai, Ruiliang; Leergaard, Trygve B.; Zhang, Jiangyang; Dyrby, Tim B.; Johnson, G. Allan; Cohen-Adad, Julien; Budde, Matthew D.; Jelescu, Ileana O.; Neurology, School of MedicineThe value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages including higher SNR and spatial resolution compared to in vivo studies, and enabling more advanced diffusion contrasts for improved microstructure and connectivity characterization. Another major advantage of ex vivo dMRI is the direct comparison with histological data, as a crucial methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work represents "Part 2" of a three-part series of recommendations and considerations for preclinical dMRI. We describe best practices for dMRI of ex vivo tissue, with a focus on the value that ex vivo imaging adds to the field of dMRI and considerations in ex vivo image acquisition. We first give general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in specimens and models and discuss why some may be more or less appropriate for different studies. We then give guidelines for ex vivo protocols, including tissue fixation, sample preparation, and MR scanning. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. An overarching goal herein is to enhance the rigor and reproducibility of ex vivo dMRI acquisitions and analyses, and thereby advance biomedical knowledge.Item Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3-Ex vivo imaging: Data processing, comparisons with microscopy, and tractography(Wiley, 2025) Schilling, Kurt G.; Howard, Amy F. D.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Barrett, Rachel L. C.; Aggarwal, Manisha; Michielse, Stijn; Nasrallah, Fatima; Syeda, Warda; Wang, Nian; Veraart, Jelle; Roebroeck, Alard; Bagdasarian, Andrew F.; Eichner, Cornelius; Sepehrband, Farshid; Zimmermann, Jan; Soustelle, Lucas; Bowman, Christien; Tendler, Benjamin C.; Hertanu, Andreea; Jeurissen, Ben; Verhoye, Marleen; Frydman, Lucio; van de Looij, Yohan; Hike, David; Dunn, Jeff F.; Miller, Karla; Landman, Bennett A.; Shemesh, Noam; Anderson, Adam; McKinnon, Emilie; Farquharson, Shawna; Dell'Acqua, Flavio; Pierpaoli, Carlo; Drobnjak, Ivana; Leemans, Alexander; Harkins, Kevin D.; Descoteaux, Maxime; Xu, Duan; Huang, Hao; Santin, Mathieu D.; Grant, Samuel C.; Obenaus, Andre; Kim, Gene S.; Wu, Dan; Le Bihan, Denis; Blackband, Stephen J.; Ciobanu, Luisa; Fieremans, Els; Bai, Ruiliang; Leergaard, Trygve B.; Zhang, Jiangyang; Dyrby, Tim B.; Johnson, G. Allan; Cohen-Adad, Julien; Budde, Matthew D.; Jelescu, Ileana O.; Neurology, School of MedicinePreclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high SNR images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a three-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing, and comparisons with microscopy. In each section, we attempt to provide guidelines and recommendations but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing and point toward open-source software and databases specific to small animal and ex vivo imaging.Item Effects of Angular Resolution and b Value on Diffusion Tensor Imaging in Knee Joint(Sage, 2021) Zhao, Qi; Ridout, Rees P.; Shen, Jikai; Wang, Nian; Radiology and Imaging Sciences, School of MedicineObjective: To investigate the influences of the diffusion gradient directions (angular resolution) and the strength of the diffusion gradient (b value) on diffusion tensor imaging (DTI) metrics and tractography of various connective tissues in knee joint. Design: Two rat knee joints were scanned on a preclinical 9.4-T system using a 3-dimensional diffusion-weighted spin echo pulse sequence. One protocol with b value of 500, 1500, and 2500 s/mm2 were acquired separately using 43 diffusion gradient directions. The other protocol with b value of 1000 s/mm2 was performed using 147 diffusion gradient directions. The in-plane resolution was 45 µm isotropic. Fractional anisotropy (FA) and mean diffusivity (MD) were compared at different angular resolution. Tractography was quantitatively evaluated at different b values and angular resolutions in cartilage, ligament, meniscus, and growth plate. Results: The ligament showed higher FA value compared with growth plate and cartilage. The FA values were largely overestimated at the angular resolution of 6. Compared with FA, MD showed less sensitivity to the angular resolution. The fiber tracking was failed at low angular resolution (6 diffusion gradient directions) or high b value (2500 s/mm2). The quantitative measurements of tract length and track volume were strongly dependent on angular resolution and b value. Conclusions: To obtain consistent DTI outputs and tractography in knee joint, the scan may require a proper b value (ranging from 500 to 1500 s/mm2) and sufficient angular resolution (>14) with signal-to-noise ratio >10.Item Effects of White-Matter Tract Length in Sport-Related Concussion: A Tractography Study from the NCAA-DoD CARE Consortium(Mary Ann Liebert, 2022) Mustafi, Sourajit M.; Yang, Ho-Ching; Harezlak, Jaroslaw; Meier, Timothy B.; Brett, Benjamin L.; Giza, Christopher C.; Goldman, Joshua; Guskiewicz, Kevin M.; Mihalik, Jason P.; LaConte, Stephen M.; Duma, Stefan M.; Broglio, Steven P.; McCrea, Michael A.; McAllister, Thomas W.; Wu, Yu-Chien; Radiology and Imaging Sciences, School of MedicineSport-related concussion (SRC) is an important public health issue. White-matter alterations after SRC are widely studied by neuroimaging approaches, such as diffusion magnetic resonance imaging (MRI). Although the exact anatomical location of the alterations may differ, significant white-matter alterations are commonly observed in long fiber tracts, but are never proven. In the present study, we performed streamline tractography to characterize the association between tract length and white-matter microstructural alterations after SRC. Sixty-eight collegiate athletes diagnosed with acute concussion (24–48 h post-injury) and 64 matched contact-sport controls were included in this study. The athletes underwent diffusion tensor imaging (DTI) in 3.0 T MRI scanners across three study sites. DTI metrics were used for tract-based spatial statistics to map white-matter regions-of-interest (ROIs) with significant group differences. Whole-brain white-mater streamline tractography was performed to extract “affected” white-matter streamlines (i.e., streamlines passing through the identified ROIs). In the concussed athletes, streamline counts and DTI metrics of the affected white-matter fiber tracts were summarized and compared with unaffected white-matter tracts across tract length in the same participant. The affected white-matter tracts had a high streamline count at length of 80–100 mm and high length-adjusted affected ratio for streamline length longer than 80 mm. DTI mean diffusivity was higher in the affected streamlines longer than 100 mm with significant associations with the Brief Symptom Inventory score. Our findings suggest that long fibers in the brains of collegiate athletes are more vulnerable to acute SRC with higher mean diffusivity and a higher affected ratio compared with the whole distribution.Item Geometric Navigation of Axons in a Cerebral Pathway: Comparing dMRI with Tract Tracing and Immunohistochemistry(Oxford University Press, 2018-04-01) Mortazavi, Farzad; Oblak, Adrian L.; Morrison, Will Z.; Schmahmann, Jeremy D.; Stanley, H. Eugene; Wedeen, Van J.; Rosene, Douglas L.; Pathology and Laboratory Medicine, School of MedicineBrain fiber pathways are presumed to follow smooth curves but recent high angular resolution diffusion MRI (dMRI) suggests that instead they follow 3 primary axes often nearly orthogonal. To investigate this, we analyzed axon pathways under monkey primary motor cortex with (1) dMRI tractography, (2) axon tract tracing, and (3) axon immunohistochemistry. dMRI tractography shows the predicted crossings of axons in mediolateral and dorsoventral orientations and does not show axon turns in this region. Axons labeled with tract tracer in the motor cortex dispersed in the centrum semiovale by microscopically sharp axonal turns and/or branches (radii ≤15 µm) into 2 sharply defined orientations, mediolateral and dorsoventral. Nearby sections processed with SMI-32 antibody to label projection axons and SMI-312 antibody to label all axons revealed axon distributions parallel to the tracer axons. All 3 histological methods confirmed preponderant axon distributions parallel with dMRI axes with few axons (<20%) following smooth curves or diagonal orientations. These findings indicate that axons navigate deep white matter via microscopic sharp turns and branches between primary axes. They support dMRI observations of primary fiber axes, as well as the prediction that fiber crossings include navigational events not yet directly resolved by dMRI. New methods will be needed to incorporate coherent microscopic navigation into dMRI of connectivity.Item High angular resolution diffusion imaging (HARDI) of porcine menisci: a comparison of diffusion tensor imaging and generalized q-sampling imaging(AME, 2024) Zhao, Qi; Holt, Abigail; Spritzer, Charles E.; DeFrate, Louis E.; McNulty, Amy L.; Wang, Nian; Radiology and Imaging Sciences, School of MedicineBackground: Diffusion magnetic resonance imaging (MRI) allows for the quantification of water diffusion properties in soft tissues. The goal of this study was to characterize the 3D collagen fiber network in the porcine meniscus using high angular resolution diffusion imaging (HARDI) acquisition with both diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI). Methods: Porcine menisci (n=7) were scanned ex vivo using a three-dimensional (3D) HARDI spin-echo pulse sequence with an isotropic resolution of 500 µm at 7.0 Tesla. Both DTI and GQI reconstruction techniques were used to quantify the collagen fiber alignment and visualize the complex collagen network of the meniscus. The MRI findings were validated with conventional histology. Results: DTI and GQI exhibited distinct fiber orientation maps in the meniscus using the same HARDI acquisition. We found that crossing fibers were only resolved with GQI, demonstrating the advantage of GQI over DTI to visualize the complex collagen fiber orientation in the meniscus. Furthermore, the MRI findings were consistent with conventional histology. Conclusions: HARDI acquisition with GQI reconstruction more accurately resolves the complex 3D collagen architecture of the meniscus compared to DTI reconstruction. In the future, these technologies have the potential to nondestructively assess both normal and abnormal meniscal structure.Item Tractography of Porcine Meniscus Microstructure Using High-Resolution Diffusion Magnetic Resonance Imaging(Frontiers Media, 2022-05-10) Shen, Jikai; Zhao, Qi; Qi, Yi; Cofer, Gary; Johnson, G. Allan; Wang, Nian; Radiology and Imaging Sciences, School of MedicineTo noninvasively evaluate the three-dimensional collagen fiber architecture of porcine meniscus using diffusion MRI, meniscal specimens were scanned using a 3D diffusion-weighted spin-echo pulse sequence at 7.0 T. The collagen fiber alignment was revealed in each voxel and the complex 3D collagen network was visualized for the entire meniscus using tractography. The proposed automatic segmentation methods divided the whole meniscus to different zones (Red-Red, Red-White, and White-White) and different parts (anterior, body, and posterior). The diffusion tensor imaging (DTI) metrics were quantified based on the segmentation results. The heatmap was generated to investigate the connections among different regions of meniscus. Strong zonal-dependent diffusion properties were demonstrated by DTI metrics. The fractional anisotropy (FA) value increased from 0.13 (White-White zone) to 0.26 (Red-Red zone) and the radial diffusivity (RD) value changed from 1.0 × 10-3 mm2/s (White-White zone) to 0.7 × 10-3 mm2/s (Red-Red zone). Coexistence of both radial and circumferential collagen fibers in the meniscus was evident by diffusion tractography. Weak connections were found between White-White zone and Red-Red zone in each part of the meniscus. The anterior part and posterior part were less connected, while the body part showed high connections to both anterior part and posterior part. The tractography based on diffusion MRI may provide a complementary method to study the integrity of meniscus and nondestructively visualize the 3D collagen fiber architecture.Item Tractography-Pathology Correlations in Traumatic Brain Injury: A TRACK-TBI Study(Mary Ann Liebert, 2021) Nolan, Amber L.; Petersen, Cathrine; Iacono, Diego; Mac Donald, Christine L.; Mukherjee, Pratik; van der Kouwe, Andre; Jain, Sonia; Stevens, Allison; Diamond, Bram R.; Wang, Ruopeng; Markowitz, Amy J.; Fischl, Bruce; Perl, Daniel P.; Manley, Geoffrey T.; Keene, C. Dirk; Diaz-Arrastia, Ramon; Edlow, Brian L.; TRACK-TBI Investigators; Psychiatry, School of MedicineDiffusion tractography magnetic resonance imaging (MRI) can infer changes in network connectivity in patients with traumatic brain injury (TBI), but the pathological substrates of disconnected tracts have not been well defined because of a lack of high-resolution imaging with histopathological validation. We developed an ex vivo MRI protocol to analyze tract terminations at 750-μm isotropic resolution, followed by histopathological evaluation of white matter pathology, and applied these methods to a 60-year-old man who died 26 days after TBI. Analysis of 74 cerebral hemispheric white matter regions revealed a heterogeneous distribution of tract disruptions. Associated histopathology identified variable white matter injury with patchy deposition of amyloid precursor protein (APP), loss of neurofilament-positive axonal processes, myelin dissolution, astrogliosis, microgliosis, and perivascular hemosiderin-laden macrophages. Multiple linear regression revealed that tract disruption strongly correlated with the density of APP-positive axonal swellings and neurofilament loss. Ex vivo diffusion MRI can detect tract disruptions in the human brain that reflect axonal injury.Item White matter alterations in early-stage Alzheimer's disease: A tract-specific study(Elsevier, 2019-08-21) Wen, Qiuting; Mustafi, Sourajit M.; Li, Junjie; Risacher, Shannon L.; Tallman, Eileen; Brown, Steven A.; West, John D.; Harezlak, Jaroslaw; Farlow, Martin R.; Unverzagt, Frederick W.; Gao, Sujuan; Apostolova, Liana G.; Saykin, Andrew J.; Wu, Yu-Chien; Radiology and Imaging Sciences, School of MedicineIntroduction: Diffusion magnetic resonance imaging may allow for microscopic characterization of white matter degeneration in early stages of Alzheimer's disease. Methods: Multishell Diffusion magnetic resonance imaging data were acquired from 100 participants (40 cognitively normal, 38 with subjective cognitive decline, and 22 with mild cognitive impairment [MCI]). White matter microscopic degeneration in 27 major tracts of interest was assessed using diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging, and q-space imaging. Results: Lower DTI fractional anisotropy and higher radial diffusivity were observed in the cingulum, thalamic radiation, and forceps major of participants with MCI. These tracts of interest also had the highest predictive power to discriminate groups. Diffusion metrics were associated with cognitive performance, particularly Rey Auditory Verbal Learning Test immediate recall, with the highest association observed in participants with MCI. Discussion: While DTI was the most sensitive, neurite orientation dispersion and density imaging and q-space imaging complementarily characterized reduced axonal density accompanied with dispersed and less restricted white matter microstructures.