Dario Pfyffer

All Publications

• Innovations in acute and chronic pain biomarkers: enhancing diagnosis and personalized therapy. Regional anesthesia and pain medicine Mackey, S., Aghaeepour, N., Gaudilliere, B., Kao, M. C., Kaptan, M., Lannon, E., Pfyffer, D., Weber, K. 2025; 50 (2): 110-120

  Abstract

  Pain affects millions worldwide, posing significant challenges in diagnosis and treatment. Despite advances in understanding pain mechanisms, there remains a critical need for validated biomarkers to enhance diagnosis, prognostication, and personalized therapy. This review synthesizes recent advancements in identifying and validating acute and chronic pain biomarkers, including imaging, molecular, sensory, and neurophysiological approaches. We emphasize the emergence of composite, multimodal strategies that integrate psychosocial factors to improve the precision and applicability of biomarkers in chronic pain management. Neuroimaging techniques like MRI and positron emission tomography provide insights into structural and functional abnormalities related to pain, while electrophysiological methods like electroencepholography and magnetoencepholography assess dysfunctional processing in the pain neuroaxis. Molecular biomarkers, including cytokines, proteomics, and metabolites, offer diagnostic and prognostic potential, though extensive validation is needed. Integrating these biomarkers with psychosocial factors into clinical practice can revolutionize pain management by enabling personalized treatment strategies, improving patient outcomes, and potentially reducing healthcare costs. Future directions include the development of composite biomarker signatures, advances in artificial intelligence, and biomarker signature integration into clinical decision support systems. Rigorous validation and standardization efforts are also necessary to ensure these biomarkers are clinically useful. Large-scale collaborative research will be vital to driving progress in this field and implementing these biomarkers in clinical practice. This comprehensive review highlights the potential of biomarkers to transform acute and chronic pain management, offering hope for improved diagnosis, treatment personalization, and patient outcomes.

  View details for DOI 10.1136/rapm-2024-106030

  View details for PubMedID 39909549

• Responsiveness to transcutaneous spinal stimulation for upper extremity recovery following spinal cord injury: A case series exploration of midsagittal tissue bridges. The journal of spinal cord medicine Smith, A. C., Morey, C., Thornton, W. A., Connor, J. R., Pfyffer, D., Weber Ii, K. A., Will, K., Tefertiller, C. 2025: 1-7

  Abstract

  Transcutaneous spinal stimulation (TSS), applied to the cervical spine, is able to improve voluntary upper extremity strength and function in individuals with cervical spinal cord injury (SCI). While most respond and improve in the presence of TSS, others do not respond as favorably. Midsagittal tissue bridges, adjacent to the lesion, can be observed and measured using T2-weighted magnetic resonance imaging (MRI), and both ventral and dorsal tissue bridges are associated with recovery following SCI. Tissue bridges may also be important for responding to neuromodulation such as TSS. The purpose of this case series was to explore potential relationships between the presence of tissue bridges and responsiveness to TSS for recovery of upper extremity strength and function in research participants with cervical-level SCI.This study involved six research participants who completed a clinical trial of rehabilitation paired with TSS to improve upper extremity strength and function. Ventral and dorsal midsagittal tissue bridges were quantified using T2-weighted MRI.Three participants classified as both strength and function responders showed presence of ventral tissue bridges, while the three strength-only responders did not. The same was found for dorsal tissue bridges, except for one strength-only responder that had a dorsal tissue bridge.The findings of this case series shed light onto the potential importance of midsagittal tissue bridges - a proxy for spared sensorimotor tracts - for responsiveness to TSS for upper extremity recovery following SCI.

  View details for DOI 10.1080/10790268.2024.2448046

  View details for PubMedID 39819187

• EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data. bioRxiv : the preprint server for biology Banerjee, R., Kaptan, M., Tinnermann, A., Khatibi, A., Dabbagh, A., Kündig, C. W., Law, C. S., Pfyffer, D., Lythgoe, D. J., Tsivaka, D., Ville, D. V., Eippert, F., Muhammad, F., Glover, G. H., David, G., Haynes, G., Haaker, J., Brooks, J. C., Finsterbusch, J., Martucci, K. T., Hemmerling, K. J., Mobarak-Abadi, M., Hoggarth, M. A., Howard, M. A., Bright, M. G., Kinany, N., Kowalczyk, O. S., Freund, P., Barry, R. L., Mackey, S., Vahdat, S., Schading, S., McMahon, S. B., Parish, T., Marchand-Pauvert, V., Chen, Y., Smith, Z. A., Weber, K. A., Leener, B. D., Cohen-Adad, J. 2025

  Abstract

  Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.0, and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared to other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.

  View details for DOI 10.1101/2025.01.07.631402

  View details for PubMedID 39829895

  View details for PubMedCentralID PMC11741348

• SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans. Radiology. Artificial intelligence Naga Karthik, E., Valošek, J., Smith, A. C., Pfyffer, D., Schading-Sassenhausen, S., Farner, L., Weber, K. A., Freund, P., Cohen-Adad, J. 2024: e240005

  Abstract

  "Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intramedullary lesions in spinal cord injury (SCI) on T2-weighted MRI scans. Materials and Methods This retrospective study included MRI data acquired between July 2002 and February 2023 from 191 patients with SCI (mean age, 48.1 years ± 17.9 [SD]; 142 males). The data consisted of T2-weighted MRI acquired using different scanner manufacturers with various image resolutions (isotropic and anisotropic) and orientations (axial and sagittal). Patients had different lesion etiologies (traumatic, ischemic, and hemorrhagic) and lesion locations across the cervical, thoracic and lumbar spine. A deep learning model, SCIseg, was trained in a three-phase process involving active learning for the automatic segmentation of intramedullary SCI lesions and the spinal cord. The segmentations from the proposed model were visually and quantitatively compared with those from three other open-source methods (PropSeg, DeepSeg and contrast-agnostic, all part of the Spinal Cord Toolbox). Wilcoxon signed-rank test was used to compare quantitative MRI biomarkers of SCI (lesion volume, lesion length, and maximal axial damage ratio) derived from the manual reference standard lesion masks and biomarkers obtained automatically with SCIseg segmentations. Results SCIseg achieved a Dice score of 0.92 ± 0.07 (mean ± SD) and 0.61 ± 0.27 for spinal cord and SCI lesion segmentation, respectively. There was no evidence of a difference between lesion length (P = .42) and maximal axial damage ratio (P = .16) computed from manually annotated lesions and the lesion segmentations obtained using SCIseg. Conclusion SCIseg accurately segmented intramedullary lesions on a diverse dataset of T2-weighted MRI scans and extracted relevant lesion biomarkers (namely, lesion volume, lesion length, and maximal axial damage ratio). SCIseg is open-source and accessible through the Spinal Cord Toolbox (v6.2 and above). Published under a CC BY 4.0 license.

  View details for DOI 10.1148/ryai.240005

  View details for PubMedID 39503603

• Extent of traumatic spinal cord injury is lesion level dependent and predictive of recovery: a multicenter neuroimaging study. Journal of neurotrauma Schading-Sassenhausen, S., Pfyffer, D., Farner, L., Grillhösl, A., Mach, O., Maier, D., Grassner, L., Leister, I., Curt, A., Freund, P. 2024

  Abstract

  Assessing the extent of the intramedullary lesion after spinal cord injury (SCI) might help to improve prognostication. However, since the neurological level of injury (NLI) impacts the recovery potential of SCI patients, the question arises whether lesion size parameters and predictive models based on those parameters are affected as well. In this retrospective observational study, the extent of the intramedullary lesion between individuals who sustained cervical and thoracolumbar SCI was compared and its relation to clinical recovery was assessed. 154 patients with sub-acute SCI (89 individuals with cervical lesions and 65 individuals with thoracolumbar lesions) underwent conventional clinical magnetic resonance imaging (MRI) 1 month after injury and clinical examination at 1 and 12 months. The morphology of the focal lesion within the spinal cord was manually assessed on the midsagittal slice of T2-weighted MR images and compared between cervical and thoracolumbar SCI patients as well as between patients who improved at least one American Spinal Injury Association Impairment Scale (AIS) grade (converters) and patients without AIS grade improvement (non-converters). The predictive value of lesion parameters including lesion length, lesion width, and preserved tissue bridges for predicting AIS grade conversion was assessed using regression models (conditional inference tree analysis). Lesion length was two times longer in thoracolumbar compared to cervical SCI patients (F = 39.48, p < 0.0001), while lesion width and tissue bridges' width did not differ. When comparing AIS grade converters and non-converters, converters showed a smaller lesion length (F = 5.46, p = 0.021), a smaller lesion width (F = 13.75, p = 0.0003) and greater tissue bridges (F = 12.87, p = 0.0005). Using regression models, tissue bridges allowed more refined subgrouping of the heterogenous patient population according to individual recovery profiles between 1 month and 12 months after SCI, while lesion length added no additional information for further subgrouping. This study characterizes differences in the anteroposterior and craniocaudal lesion extent after SCI. The two times greater lesion length in thoracolumbar compared to cervical SCI might be related to differences in the anatomy, biomechanics, and perfusion between the cervical and thoracic spine. Preserved tissue bridges were less influenced by the lesion level, while closely related to the clinical impairment. These results highlight the robustness and utility of tissue bridges as a neuroimaging biomarker for predicting clinical outcome after SCI in heterogeneous patient populations and for patient stratification in clinical trials.

  View details for DOI 10.1089/neu.2023.0555

  View details for PubMedID 39001825

• Prognostic value of tissue bridges in cervical spinal cord injury: a longitudinal, multicentre, retrospective cohort study. The Lancet. Neurology Pfyffer, D., Smith, A. C., Weber, K. A., Grillhoesl, A., Mach, O., Draganich, C., Berliner, J. C., Tefertiller, C., Leister, I., Maier, D., Schwab, J. M., Thompson, A., Curt, A., Freund, P. 2024

  Abstract

  The accuracy of prognostication in patients with cervical spinal cord injury (SCI) needs to be improved. We aimed to explore the prognostic value of preserved spinal tissue bridges-injury-spared neural tissue adjacent to the lesion-for prediction of sensorimotor recovery in a large, multicentre cohort of people with SCI.For this longitudinal study, we included patients with acute cervical SCI (vertebrae C1-C7) admitted to one of three trauma or rehabilitation centres: Murnau, Germany (March 18, 2010-March 1, 2021); Zurich, Switzerland (May 12, 2002-March 2, 2019); and Denver, CO, USA (Jan 12, 2010-Feb 16, 2017). Patients were clinically assessed at admission (baseline), at discharge (3 months), and at 12 months post SCI. Midsagittal tissue bridges were quantified from T2-weighted images assessed at 3-4 weeks post SCI. Fractional regression and unbiased recursive partitioning models, adjusted for age, sex, centre, and neurological level of injury, were used to assess associations between tissue bridge width and baseline-adjusted total motor score, pinprick score, and light touch scores at 3 months and 12 months. Patients were stratified into subgroups according to whether they showed better or worse predicted recovery.The cohort included 227 patients: 93 patients from Murnau (22 [24%] female); 43 patients from Zurich (four [9%] female); and 91 patients from Denver (14 [15%] female). 136 of these participants (from Murnau and Zurich) were followed up for up to 12 months. At 3 months, per preserved 1 mm of tissue bridge at baseline, patients recovered a mean of 9·3% (SD 0·9) of maximal total motor score (95% CI 7·5-11.2), 8·6% (0·8) of maximal pinprick score (7·0-10·1), and 10·9% (0·8) of maximal light touch score (9·4-12·5). At 12 months post SCI, per preserved 1 mm of tissue bridge at baseline, patients recovered a mean of 10·9% (1·3) of maximal total motor score (8·4-13·4), 5·7% (1·3) of maximal pinprick score (3·3-8·2), and 6·9% (1·4) of maximal light touch score (4·1-9·7). Partitioning models identified a tissue bridge cutoff width of 2·0 mm to be indicative of higher or lower 3-month total motor, pinprick, and light touch scores, and a cutoff of 4·0 mm to be indicative of higher and lower 12-month scores. Compared with models that contained clinical predictors only, models additionally including tissue bridges had significantly improved prediction accuracy across all three centres.Tissue bridges, measured in the first few weeks after SCI, are associated with short-term and long-term clinical improvement. Thus, tissue bridges could potentially be used to guide rehabilitation decision making and to stratify patients into more homogeneous subgroups of recovery in regenerative and neuroprotective clinical trials.Wings for Life, International Foundation for Research in Paraplegia, EU project Horizon 2020 (NISCI grant), and ERA-NET NEURON.

  View details for DOI 10.1016/S1474-4422(24)00173-X

  View details for PubMedID 38945142

• Potential thresholds of critically increased cardiac-related spinal cord motion in degenerative cervical myelopathy. Frontiers in neurology Pfender, N., Jutzeler, C. R., Hubli, M., Scheuren, P. S., Pfyffer, D., Zipser, C. M., Rosner, J., Friedl, S., Sutter, R., Spirig, J. M., Betz, M., Schubert, M., Seif, M., Freund, P., Farshad, M., Curt, A., Hupp, M. 2024; 15: 1411182

  Abstract

  New diagnostic techniques are a substantial research focus in degenerative cervical myelopathy (DCM). This cross-sectional study determined the significance of cardiac-related spinal cord motion and the extent of spinal stenosis as indicators of mechanical strain on the cord.Eighty-four DCM patients underwent MRI/clinical assessments and were classified as MRI+ [T2-weighted (T2w) hyperintense lesion in MRI] or MRI- (no T2w-hyperintense lesion). Cord motion (displacement assessed by phase-contrast MRI) and spinal stenosis [adapted spinal canal occupation ratio (aSCOR)] were related to neurological (sensory/motor) and neurophysiological readouts [contact heat evoked potentials (CHEPs)] by receiver operating characteristic (ROC) analysis.MRI+ patients (N = 31; 36.9%) were more impaired compared to MRI- patients (N = 53; 63.1%) based on the modified Japanese Orthopedic Association (mJOA) subscores for upper {MRI+ [median (Interquartile range)]: 4 (4-5); MRI-: 5 (5-5); p < 0.01} and lower extremity [MRI+: 6 (6-7); MRI-: 7 (6-7); p = 0.03] motor dysfunction and the monofilament score [MRI+: 21 (18-23); MRI-: 24 (22-24); p < 0.01]. Both patient groups showed similar extent of cord motion and stenosis. Only in the MRI- group displacement identified patients with pathologic assessments [trunk/lower extremity pin prick score (T/LEPP): AUC = 0.67, p = 0.03; CHEPs: AUC = 0.73, p = 0.01]. Cord motion thresholds: T/LEPP: 1.67 mm (sensitivity 84.6%, specificity 52.5%); CHEPs: 1.96 mm (sensitivity 83.3%, specificity 65.6%). The aSCOR failed to show any relation to the clinical assessments.These findings affirm cord motion measurements as a promising additional biomarker to improve the clinical workup and to enable timely surgical treatment particularly in MRI- DCM patients.www.clinicaltrials.gov, NCT02170155.

  View details for DOI 10.3389/fneur.2024.1411182

  View details for PubMedID 38978814

  View details for PubMedCentralID PMC11228334

• SCIseg: Automatic Segmentation of T2-weighted Intramedullary Lesions in Spinal Cord Injury. medRxiv : the preprint server for health sciences Karthik, E. N., Valosek, J., Smith, A. C., Pfyffer, D., Schading-Sassenhausen, S., Farner, L., Weber, K. A., Freund, P., Cohen-Adad, J. 2024

  Abstract

  To develop a deep learning tool for the automatic segmentation of T2-weighted intramedullary lesions in spinal cord injury (SCI).This retrospective study included a cohort of SCI patients from three sites enrolled between July 2002 and February 2023. A deep learning model, SCIseg, was trained in a three-phase process involving active learning for the automatic segmentation of intramedullary SCI lesions and the spinal cord. The data consisted of T2-weighted MRI acquired using different scanner manufacturers with heterogeneous image resolutions (isotropic/anisotropic), orientations (axial/sagittal), lesion etiologies (traumatic/ischemic/hemorrhagic) and lesions spread across the cervical, thoracic and lumbar spine. The segmentations from the proposed model were visually and quantitatively compared with other open-source baselines. Wilcoxon signed-rank test was used to compare quantitative MRI biomarkers (lesion volume, lesion length, and maximal axial damage ratio) computed from manual lesion masks and those obtained automatically with SCIseg predictions.MRI data from 191 SCI patients (mean age, 48.1 years ± 17.9 [SD]; 142 males) were used for model training and evaluation. SCIseg achieved the best segmentation performance for both the cord and lesions. There was no statistically significant difference between lesion length and maximal axial damage ratio computed from manually annotated lesions and those obtained using SCIseg.Automatic segmentation of intramedullary lesions commonly seen in SCI replaces the tedious manual annotation process and enables the extraction of relevant lesion morphometrics in large cohorts. The proposed model segments lesions across different etiologies, scanner manufacturers, and heterogeneous image resolutions. SCIseg is open-source and accessible through the Spinal Cord Toolbox.

  View details for DOI 10.1101/2024.01.03.24300794

  View details for PubMedID 38699309

  View details for PubMedCentralID PMC11065035

• Exploring Neuronal Underpinnings of Emotional Regulation of Pain in Fibromyalgia Patients Kaptan, M., Pfyffer, D., Law, C. W., Oliva, V., Weber, K., Glover, G., Mackey, S. CHURCHILL LIVINGSTONE. 2024: 47

  View details for Web of Science ID 001282167300210

• Imaging Corticospinal Correlates of Aberrant Pain Processing and Modulation in Fibromyalgia Using Combined Brain-Spinal Cord Functional Magnetic Resonance Imaging Pfyffer, D., Kaptan, M., Law, C. W., Weber, K. A., Oliva, V., Bedard, S., Maronesy, T., Glover, G. H., Mackey, S. CHURCHILL LIVINGSTONE. 2024: 47-48

  View details for Web of Science ID 001282167300214

• Recent developments and future avenues for human corticospinal neuroimaging. Frontiers in human neuroscience Kaptan, M., Pfyffer, D., Konstantopoulos, C. G., Law, C. S., Weber Ii, K. A., Glover, G. H., Mackey, S. 2024; 18: 1339881

  Abstract

  Non-invasive neuroimaging serves as a valuable tool for investigating the mechanisms within the central nervous system (CNS) related to somatosensory and motor processing, emotions, memory, cognition, and other functions. Despite the extensive use of brain imaging, spinal cord imaging has received relatively less attention, regardless of its potential to study peripheral communications with the brain and the descending corticospinal systems. To comprehensively understand the neural mechanisms underlying human sensory and motor functions, particularly in pathological conditions, simultaneous examination of neuronal activity in both the brain and spinal cord becomes imperative. Although technically demanding in terms of data acquisition and analysis, a growing but limited number of studies have successfully utilized specialized acquisition protocols for corticospinal imaging. These studies have effectively assessed sensorimotor, autonomic, and interneuronal signaling within the spinal cord, revealing interactions with cortical processes in the brain. In this mini-review, we aim to examine the expanding body of literature that employs cutting-edge corticospinal imaging to investigate the flow of sensorimotor information between the brain and spinal cord. Additionally, we will provide a concise overview of recent advancements in functional magnetic resonance imaging (fMRI) techniques. Furthermore, we will discuss potential future perspectives aimed at enhancing our comprehension of large-scale neuronal networks in the CNS and their disruptions in clinical disorders. This collective knowledge will aid in refining combined corticospinal fMRI methodologies, leading to the development of clinically relevant biomarkers for conditions affecting sensorimotor processing in the CNS.

  View details for DOI 10.3389/fnhum.2024.1339881

  View details for PubMedID 38332933

  View details for PubMedCentralID PMC10850311

• Longitudinal motor system changes from acute to chronic spinal cord injury. European journal of neurology Emmenegger, T. M., Pfyffer, D., Curt, A., Schading-Sassenhausen, S., Hupp, M., Ashburner, J., Friston, K., Weiskopf, N., Thompson, A., Freund, P. 2024: e16196

  Abstract

  BACKGROUND AND PURPOSE: In acute spinal cord injury (SCI), magnetic resonance imaging (MRI) reveals tissue bridges and neurodegeneration for 2years. This 5-year study aims to track initial lesion changes, subsequent neurodegeneration, and their impact on recovery.METHODS: This prospective longitudinal study enrolled acute SCI patients and healthy controls who were assessed clinically-and by MRI-regularly from 3days postinjury up to 60months. We employed histologically cross-validated quantitative MRI sequences sensitive to volume, myelin, and iron changes, thereby reflecting indirectly processes of neurodegeneration and neuroinflammation. General linear models tracked lesion and remote changes in volume, myelin- and iron-sensitive magnetic resonance indices over 5years. Associations between lesion, degeneration, and recovery (using the Spinal Cord Independence Measure [SCIM] questionnaire and the International Standards for Neurological Classification of Spinal Cord Injury total motor score) were assessed.RESULTS: Patients' motor scores improved by an average of 12.86 (95% confidence interval [CI] =6.70-19.00) points, and SCIM by 26.08 (95% CI=17.00-35.20) points. Within 3-28days post-SCI, lesion size decreased by more than two-thirds (3days:302.52±185.80mm2 , 28days:76.77±88.62mm2 ), revealing tissue bridges. Cervical cord and corticospinal tract volumes transiently increased in SCI patients by 5% and 3%, respectively, accompanied by cervical myelin decreases and iron increases. Over time, progressive atrophy was observed in both regions, which was linked to early lesion dynamics. Tissue bridges, reduced swelling, and myelin content decreases were predictive of long-term motor score recovery and improved SCIM score.CONCLUSIONS: Studying acute changes and their impact on longer follow-up provides insights into SCI trajectory, highlighting the importance of acute intervention while indicating the potential to influence outcomes in the later stages.

  View details for DOI 10.1111/ene.16196

  View details for PubMedID 38258488

• Exploring Corticospinal Functional Connectome Using Resting-State Functional Magnetic Resonance Imaging Kaptan, M., Law, C. W., Weber, K., Pfyffer, D., Zhang, X., Maronesy, T., Glover, G., Mackey, S. CHURCHILL LIVINGSTONE. 2023: 17-18

  View details for Web of Science ID 000995432100047

• Imaging Noxious Thermal Intensity Encoding Along The Neuraxis Using Simultaneous Spinal Cord-Brain Functional Magnetic Resonance Imaging Pfyffer, D., Law, C. W., Weber, K. A., Kaptan, M., Maronesy, T., Glover, G. H., Mackey, S. CHURCHILL LIVINGSTONE. 2023: 76

  View details for Web of Science ID 000995432100203

• Magnetic resonance spectroscopy investigation in the right human hippocampus following spinal cord injury. Frontiers in neurology Pfyffer, D., Zimmermann, S., Simsek, K., Kreis, R., Freund, P., Seif, M. 2023; 14: 1120227

  Abstract

  Objective: Preclinical studies have shown that cognitive impairments following spinal cord injury (SCI), such as impaired spatial memory, are linked to inflammation, neurodegeneration, and reduced neurogenesis in the right hippocampus. This cross-sectional study aims to characterize metabolic and macrostructural changes in the right hippocampus and their association to cognitive function in traumatic SCI patients.Methods: Within this cross-sectional study, cognitive function was assessed in 28 chronic traumatic SCI patients and 18 age-, sex-, and education-matched healthy controls by a visuospatial and verbal memory test. A magnetic resonance spectroscopy (MRS) and structural MRI protocol was performed in the right hippocampus of both groups to quantify metabolic concentrations and hippocampal volume, respectively. Group comparisons investigated changes between SCI patients and healthy controls and correlation analyses investigated their relationship to memory performance.Results: Memory performance was similar in SCI patients and healthy controls. The quality of the recorded MR spectra was excellent in comparison to the best-practice reports for the hippocampus. Metabolite concentrations and volume of the hippocampus measured based on MRS and MRI were not different between two groups. Memory performance in SCI patients and healthy controls was not correlated with metabolic or structural measures.Conclusion: This study suggests that the hippocampus may not be pathologically affected at a functional, metabolic, and macrostructural level in chronic SCI. This points toward the absence of significant and clinically relevant trauma-induced neurodegeneration in the hippocampus.

  View details for DOI 10.3389/fneur.2023.1120227

  View details for PubMedID 37251221

• Width of Tissue Bridges Predicts Neurologic Recovery 3 Months After Spinal Cord Injury: a Multi Center Study Pfyffer, D., Smith, A., Weber, K., Draganich, C., Berliner, J., Tefertiller, C., Hothorn, T., Schwab, J., Curt, A., Freund, P. LIPPINCOTT WILLIAMS & WILKINS. 2022

  View details for Web of Science ID 000894020500066