Nadim Farhat, Jinghang Li, Jacob Berardinelli, Mark Stauffer, Andrea Sajewski, Salem Alkhateeb, Noah Schweitzer, Hecheng Jin, Sossena Wood, Milos D. Ikonomovic, Jr-Jiun Liou, Howard J. Aizenstein, Joseph M. Mettenburg, Tales Santini, Minjie Wu, Julia K. Kofler, Tamer S. Ibrahim
Background and Purpose
White matter lesions are common imaging biomarkers associated with aging and neurodegenerative diseases, yet their underlying pathology remains unclear due to limitations in imaging-based characterization. We aim to develop and validate a comprehensive workflow enabling precise MRI-guided histological sampling of white matter lesions to bridge neuroimaging and neuropathology.
Methods
We established a workflow integrating agar-sucrose brain embedding, ultrahigh field 7 Tesla (7T) MRI acquisition, reusable three-dimensional (3D) printed cutting guides, and semiautomated MRI-blockface alignment. Left hemispheric postmortem brains were stabilized in the embedding medium and scanned using optimized MRI protocols. Coronal sectioning was guided by standardized 3D-printed cutting guides, and knife traces were digitally matched to MRI planes. White matter lesions were segmented on MRI and aligned for histopathological sampling.
Results
The workflow enabled reproducible brain sectioning, minimized imaging artifacts, and achieved precise spatial alignment between MRI and histology. For demonstration, detailed results from two representative brains were presented in this article. Consistent, high-resolution MRI data facilitated accurate lesion detection and sampling. The use of standardized cutting guides and alignment protocols reduced variability and improved efficiency.
Conclusions
Our cost-effective, scalable workflow reliably linked neuroimaging findings with histological analysis, enhancing the understanding of white matter lesion pathology. This framework held significant potential for advancing translational research in aging and neurodegenerative diseases.
{"title":"Bridging Neuroimaging and Neuropathology: A Comprehensive Workflow for Targeted Sampling of White Matter Lesions","authors":"Nadim Farhat, Jinghang Li, Jacob Berardinelli, Mark Stauffer, Andrea Sajewski, Salem Alkhateeb, Noah Schweitzer, Hecheng Jin, Sossena Wood, Milos D. Ikonomovic, Jr-Jiun Liou, Howard J. Aizenstein, Joseph M. Mettenburg, Tales Santini, Minjie Wu, Julia K. Kofler, Tamer S. Ibrahim","doi":"10.1111/jon.70094","DOIUrl":"10.1111/jon.70094","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>White matter lesions are common imaging biomarkers associated with aging and neurodegenerative diseases, yet their underlying pathology remains unclear due to limitations in imaging-based characterization. We aim to develop and validate a comprehensive workflow enabling precise MRI-guided histological sampling of white matter lesions to bridge neuroimaging and neuropathology.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We established a workflow integrating agar-sucrose brain embedding, ultrahigh field 7 Tesla (7T) MRI acquisition, reusable three-dimensional (3D) printed cutting guides, and semiautomated MRI-blockface alignment. Left hemispheric postmortem brains were stabilized in the embedding medium and scanned using optimized MRI protocols. Coronal sectioning was guided by standardized 3D-printed cutting guides, and knife traces were digitally matched to MRI planes. White matter lesions were segmented on MRI and aligned for histopathological sampling.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The workflow enabled reproducible brain sectioning, minimized imaging artifacts, and achieved precise spatial alignment between MRI and histology. For demonstration, detailed results from two representative brains were presented in this article. Consistent, high-resolution MRI data facilitated accurate lesion detection and sampling. The use of standardized cutting guides and alignment protocols reduced variability and improved efficiency.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our cost-effective, scalable workflow reliably linked neuroimaging findings with histological analysis, enhancing the understanding of white matter lesion pathology. This framework held significant potential for advancing translational research in aging and neurodegenerative diseases.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145345671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhib Khan, Leo Gallagher, Laurel Packard, Jessica Parker, Dave Chesla, Gabe Heredia
Background and Purpose
Corticospinal tract (CST) integrity is an imaging biomarker for predicting upper extremity motor recovery, but data are limited in acute ischemic stroke patients. Our study aimed to assess the impact of CST disruption on upper extremity motor recovery after acute ischemic stroke.
Methods
We enrolled patients with upper extremity motor deficits within 7 days of stroke onset. Patients’ clinical status was assessed for the upper extremity Fugl–Meyer assessment motor component (UE-FM) within 7 days of stroke and at 15, 30, and 90 days. MRI with tractography was performed within 7 days of stroke. Diffusion tensor images (DTI) were processed to produce maps of fractional anisotropy (FA), apparent diffusion, axial, radial, and mean diffusivity. FA maps were used to assess CST asymmetry index (CST-AI). Fisher's exact tests for categorical variables, two-sample t-tests for normally distributed numerical data, and Wilcoxon rank sums for non-normally distributed numeric data were used.
Results
A total of 21 patients were enrolled in the study with a mean age of 66 (±14) years and median baseline upper extremity motor component score (UE-FM) of 42 (median) [range: 23, 53]. Baseline UE-FM was not predictive of a 10-point change at 90 days (p = 0.4469). CST-AI was predictive of recovery at 15 days (p = 0.0373), and axial diffusivity was predictive of recovery at 90 days (p = 0.0402). All other imaging variables did not predict recovery.
Conclusion
Our data suggest that upper extremity motor recovery after acute ischemic stroke is impacted by CST integrity. Further studies are needed to validate our findings.
{"title":"Corticospinal Tract Injury Leads to Poor Motor Recovery Immediately After Ischemic Stroke","authors":"Muhib Khan, Leo Gallagher, Laurel Packard, Jessica Parker, Dave Chesla, Gabe Heredia","doi":"10.1111/jon.70095","DOIUrl":"10.1111/jon.70095","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>Corticospinal tract (CST) integrity is an imaging biomarker for predicting upper extremity motor recovery, but data are limited in acute ischemic stroke patients. Our study aimed to assess the impact of CST disruption on upper extremity motor recovery after acute ischemic stroke.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We enrolled patients with upper extremity motor deficits within 7 days of stroke onset. Patients’ clinical status was assessed for the upper extremity Fugl–Meyer assessment motor component (UE-FM) within 7 days of stroke and at 15, 30, and 90 days. MRI with tractography was performed within 7 days of stroke. Diffusion tensor images (DTI) were processed to produce maps of fractional anisotropy (FA), apparent diffusion, axial, radial, and mean diffusivity. FA maps were used to assess CST asymmetry index (CST-AI). Fisher's exact tests for categorical variables, two-sample <i>t</i>-tests for normally distributed numerical data, and Wilcoxon rank sums for non-normally distributed numeric data were used.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 21 patients were enrolled in the study with a mean age of 66 (±14) years and median baseline upper extremity motor component score (UE-FM) of 42 (median) [range: 23, 53]. Baseline UE-FM was not predictive of a 10-point change at 90 days (<i>p</i> = 0.4469). CST-AI was predictive of recovery at 15 days (<i>p</i> = 0.0373), and axial diffusivity was predictive of recovery at 90 days (<i>p</i> = 0.0402). All other imaging variables did not predict recovery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our data suggest that upper extremity motor recovery after acute ischemic stroke is impacted by CST integrity. Further studies are needed to validate our findings.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145258470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E Dereskewicz, F La Rosa, J Dos Santos Silva, et al. “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation.” Journal of Neuroimaging 35.5 (2025): e70085.
In Table 7, the text “dawm” was a typo and should have been removed. In addition, the table should present all values with two significant figures.
We apologize for this error.
Table 7. Performance comparison between 2D and 3D scans in the clinical dataset across all models.
Note: Average values across five subjects are provided for each metric.
E Dereskewicz, F La Rosa， J Dos Santos Silva等，“用于多发性硬化症脑损伤自动分割的新型卷积神经网络”。中华神经影像学杂志35.5 (2025):e70085。在表7中，文本“dawm”是一个错字，应该删除。此外，该表应以两位有效数字表示所有值。我们为这个错误道歉。表7所示。在所有模型的临床数据集中进行2D和3D扫描的性能比较。注意：每个指标提供了五个主题的平均值。缩写：LFPR，病变假阳性率；LTPR：病变真阳性率；RVD，相对容积差。
{"title":"Correction to “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation”","authors":"","doi":"10.1111/jon.70093","DOIUrl":"10.1111/jon.70093","url":null,"abstract":"<p>E Dereskewicz, F La Rosa, J Dos Santos Silva, et al. “A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation.” <i>Journal of Neuroimaging</i> 35.5 (2025): e70085.</p><p>In Table 7, the text “dawm” was a typo and should have been removed. In addition, the table should present all values with two significant figures.</p><p>We apologize for this error.</p><p>Table 7. Performance comparison between 2D and 3D scans in the clinical dataset across all models.\u0000\u0000 </p><p><i>Note</i>: Average values across five subjects are provided for each metric.</p><p>Abbreviations: LFPR, lesion false positive rate; LTPR, lesion true positive rate; RVD, relative volume difference.</p>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Livja Mertiri, Nilesh Desai, Maarten Lequin, Denada Mertiri, Hui Brandon Tran, Cesar Alves, Marcello Chiocchi, Thierry A. G. M. Huisman, Felice D'Arco
Cancer predisposition syndromes (CPSs) are a group of inherited disorders that significantly increase the risk of developing various cancers, ranging from infancy through adulthood. CPSs account for about 10% of the pediatric cancers, and they represent a major cause of morbidity and mortality in affected children. The inheritance pattern and the variable penetrance influence the age of onset and the clinical course, resulting in substantial variation in presentation, even within a single family. Early recognition of CPSs is crucial, as timely diagnosis allows for health surveillance, preventive interventions, and genetic counselling for patients and their families. Guidelines and surveillance programs have been developed to identify at-risk patients and coordinate long-term care. This review focuses on the most common CPSs associated with pediatric cancers, with particular emphasis on the involvement of the head and neck region. For each syndrome, we provide a background summary including its genetics and clinical manifestations, followed by a detailed description of characteristic head and neck imaging findings. Illustrative case examples are then presented to demonstrate the spectrum of clinical and imaging features. It highlights imaging features to assist providers reading these studies in the early identification of all possible pathological manifestations in these syndromes. Key CPSs covered include retinoblastoma, Li–Fraumeni syndrome, neurofibromatosis type 1, DICER1 syndrome, rhabdoid tumor predisposition syndrome, Gorlin–Goltz syndrome, hereditary paraganglioma–pheochromocytoma syndrome, constitutional mismatch repair deficiency syndrome, and neuroblastoma predisposition syndrome.
{"title":"Cancer Predisposition Syndromes With Involvement of the Head and Neck Regions in Children: An Imaging Guide","authors":"Livja Mertiri, Nilesh Desai, Maarten Lequin, Denada Mertiri, Hui Brandon Tran, Cesar Alves, Marcello Chiocchi, Thierry A. G. M. Huisman, Felice D'Arco","doi":"10.1111/jon.70092","DOIUrl":"10.1111/jon.70092","url":null,"abstract":"<div>\u0000 \u0000 <p>Cancer predisposition syndromes (CPSs) are a group of inherited disorders that significantly increase the risk of developing various cancers, ranging from infancy through adulthood. CPSs account for about 10% of the pediatric cancers, and they represent a major cause of morbidity and mortality in affected children. The inheritance pattern and the variable penetrance influence the age of onset and the clinical course, resulting in substantial variation in presentation, even within a single family. Early recognition of CPSs is crucial, as timely diagnosis allows for health surveillance, preventive interventions, and genetic counselling for patients and their families. Guidelines and surveillance programs have been developed to identify at-risk patients and coordinate long-term care. This review focuses on the most common CPSs associated with pediatric cancers, with particular emphasis on the involvement of the head and neck region. For each syndrome, we provide a background summary including its genetics and clinical manifestations, followed by a detailed description of characteristic head and neck imaging findings. Illustrative case examples are then presented to demonstrate the spectrum of clinical and imaging features. It highlights imaging features to assist providers reading these studies in the early identification of all possible pathological manifestations in these syndromes. Key CPSs covered include retinoblastoma, Li–Fraumeni syndrome, neurofibromatosis type 1, DICER1 syndrome, rhabdoid tumor predisposition syndrome, Gorlin–Goltz syndrome, hereditary paraganglioma–pheochromocytoma syndrome, constitutional mismatch repair deficiency syndrome, and neuroblastoma predisposition syndrome.</p>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145199701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hamza Adel Salim, Dhairya A. Lakhani, Aneri Balar, Mona Shahriari, Aakanksha Sriwastawa, Andrew Cho, Adam A. Dmytriw, Adrien Guenego, Elisabeth B. Marsh, Hanzhang Lu, Risheng Xu, Rich Leigh, Gaurang Shah, Sijin Wen, Gregory W. Albers, Argye E. Hillis, Rafael Llinas, Kambiz Nael, Max Wintermark, Jeremy J. Heit, Tobias D. Faizy, Vivek S. Yedavalli
Background and Purpose
Distal medium-vessel occlusion (DMVO) strokes represent a significant proportion of acute ischemic stroke cases, yet optimal management remains unclear. Prolonged venous transit (PVT), a marker of poor venous outflow, has been associated with worse outcomes in large-vessel occlusion strokes, but its role in DMVO is unknown.
Methods
In a retrospective study, consecutive patients with anterior-circulation DMVO, defined as occlusions in the M2–M4 segments of the middle cerebral artery or the anterior cerebral artery. PVT status was determined on pretreatment time-to-maximum perfusion maps by identifying ≥10-s delays in either the posterior superior sagittal sinus or the torcula. Baseline characteristics, imaging findings, and interventions were collected. The primary outcome was a 90-day modified Rankin Scale (mRS) score of 0–2.
Results
Among 77 patients (median age 70 years, 56% female), 18 (23%) had PVT. Median admission National Institutes of Health Stroke Scale scores were 11 (interquartile range, 7–15), and intravenous thrombolysis was administered to 35% of patients. Patients with PVT+ were less likely to achieve mRS 0–2 at 90 days (adjusted odds ratio, 0.14; 95% confidence interval, 0.02–0.85; p = 0.046). There were no significant differences in rates of hemorrhagic transformation or mortality.
Conclusions
PVT is independently associated with unfavorable functional outcomes in anterior-circulation DMVO. These findings suggest PVT may serve as a prognostic indicator and could inform treatment decisions in this challenging stroke subtype.
{"title":"Prolonged Venous Transit Is Associated With Unfavorable Outcomes in Anterior Circulation Distal Medium Vessel Stroke","authors":"Hamza Adel Salim, Dhairya A. Lakhani, Aneri Balar, Mona Shahriari, Aakanksha Sriwastawa, Andrew Cho, Adam A. Dmytriw, Adrien Guenego, Elisabeth B. Marsh, Hanzhang Lu, Risheng Xu, Rich Leigh, Gaurang Shah, Sijin Wen, Gregory W. Albers, Argye E. Hillis, Rafael Llinas, Kambiz Nael, Max Wintermark, Jeremy J. Heit, Tobias D. Faizy, Vivek S. Yedavalli","doi":"10.1111/jon.70091","DOIUrl":"https://doi.org/10.1111/jon.70091","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>Distal medium-vessel occlusion (DMVO) strokes represent a significant proportion of acute ischemic stroke cases, yet optimal management remains unclear. Prolonged venous transit (PVT), a marker of poor venous outflow, has been associated with worse outcomes in large-vessel occlusion strokes, but its role in DMVO is unknown.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In a retrospective study, consecutive patients with anterior-circulation DMVO, defined as occlusions in the M2–M4 segments of the middle cerebral artery or the anterior cerebral artery. PVT status was determined on pretreatment time-to-maximum perfusion maps by identifying ≥10-s delays in either the posterior superior sagittal sinus or the torcula. Baseline characteristics, imaging findings, and interventions were collected. The primary outcome was a 90-day modified Rankin Scale (mRS) score of 0–2.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 77 patients (median age 70 years, 56% female), 18 (23%) had PVT. Median admission National Institutes of Health Stroke Scale scores were 11 (interquartile range, 7–15), and intravenous thrombolysis was administered to 35% of patients. Patients with PVT+ were less likely to achieve mRS 0–2 at 90 days (adjusted odds ratio, 0.14; 95% confidence interval, 0.02–0.85; <i>p</i> = 0.046). There were no significant differences in rates of hemorrhagic transformation or mortality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>PVT is independently associated with unfavorable functional outcomes in anterior-circulation DMVO. These findings suggest PVT may serve as a prognostic indicator and could inform treatment decisions in this challenging stroke subtype.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rebecca Choi, Jacob Schick, Sasicha Manupipatpong, Samuel Law, John Gross, Yuanxuan Xia, Daniel Lubelski, Kristin J. Redmond, Majid Khan
Spinal chordomas are rare, malignant bone tumors originating from notochordal remnants, primarily affecting the sacrum, clivus, and spine. Despite their low prevalence, they present significant diagnostic and therapeutic challenges due to their local aggressiveness, high recurrence rate, and imaging similarities to other tumors, such as chondrosarcomas. Advances in imaging technologies, particularly high-resolution magnetic resonance imaging and computed tomography (CT), have improved the ability to visualize chordomas and enhance the precision of surgical planning. Additionally, newer imaging modalities, including diffusion-weighted imaging and positron emission tomography/CT, offer more refined diagnostic capabilities, though differentiation from other similar lesions remains difficult. Histologically, chordomas are marked by physaliphorous cells and a myxoid stroma, with the brachyury gene playing a key role in tumorigenesis and serving as a potential therapeutic target. The pathophysiology and molecular landscape of chordomas further complicate diagnosis and treatment. This review examines the current state of imaging advancements, challenges in diagnosis, and their impact on clinical management. It highlights the importance of combining various imaging modalities to improve diagnostic accuracy, aid surgical resection planning, and reduce recurrence. Additionally, it discusses the ongoing need for more targeted therapies and improved imaging techniques to optimize patient outcomes in spinal chordoma management.
{"title":"Spinal and Sacral Chordomas: Overview With Imaging Review","authors":"Rebecca Choi, Jacob Schick, Sasicha Manupipatpong, Samuel Law, John Gross, Yuanxuan Xia, Daniel Lubelski, Kristin J. Redmond, Majid Khan","doi":"10.1111/jon.70090","DOIUrl":"10.1111/jon.70090","url":null,"abstract":"<div>\u0000 \u0000 <p>Spinal chordomas are rare, malignant bone tumors originating from notochordal remnants, primarily affecting the sacrum, clivus, and spine. Despite their low prevalence, they present significant diagnostic and therapeutic challenges due to their local aggressiveness, high recurrence rate, and imaging similarities to other tumors, such as chondrosarcomas. Advances in imaging technologies, particularly high-resolution magnetic resonance imaging and computed tomography (CT), have improved the ability to visualize chordomas and enhance the precision of surgical planning. Additionally, newer imaging modalities, including diffusion-weighted imaging and positron emission tomography/CT, offer more refined diagnostic capabilities, though differentiation from other similar lesions remains difficult. Histologically, chordomas are marked by physaliphorous cells and a myxoid stroma, with the brachyury gene playing a key role in tumorigenesis and serving as a potential therapeutic target. The pathophysiology and molecular landscape of chordomas further complicate diagnosis and treatment. This review examines the current state of imaging advancements, challenges in diagnosis, and their impact on clinical management. It highlights the importance of combining various imaging modalities to improve diagnostic accuracy, aid surgical resection planning, and reduce recurrence. Additionally, it discusses the ongoing need for more targeted therapies and improved imaging techniques to optimize patient outcomes in spinal chordoma management.</p>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145069713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jan Kufer, Christine Preibisch, Jens Göttler, Lena Schmitzer, Gabriel Hoffmann, Michael Kallmayer, Claus Zimmer, Fahmeed Hyder, Stephan Kaczmarz
Background and Purpose
Hemodynamic impairment may contribute to stroke risk and cognitive decline in asymptomatic internal carotid artery stenosis (ICAS). Therefore, multimodal MRI-based quantification of hemodynamic impairment could inform improved treatment decisions. While gross interhemispheric hemodynamic imbalances have been reported in ICAS, identifying more spatially resolved patterns of disease-related alterations may be promising to harness the full potential of hemodynamic MRI.
Methods
In this feasibility study, we investigated the spatial topography of ICAS-related impairments by applying scaled subprofile model principal component analysis (SSM-PCA) to cerebral blood flow (CBF), relative oxygen extraction fraction (rOEF), and oxygen extraction capacity (OEFmax) data of 21 unilateral ICAS patients and 25 healthy controls (HC).
Results
We found spatially extended, partly overlapping disease-related patterns for CBF and OEFmax, but not rOEF. CBF (area under the curve [AUC] = 0.95) but not OEFmax (AUC = 0.72) SSM-PCA scores distinguished ICAS patients and HC better than interhemispheric lateralizations (AUC = 0.75/0.73). SSM-PCA scores were only partly explained by interhemispheric lateralization (R2 = −0.27/0.38), indicating complementary information. Critically, ICAS patients with higher OEFmax SSM-PCA scores (z ≥ 1) demonstrated higher stenotic degrees and lower cognitive performance (p < 0.05) without differing in interhemispheric lateralization (p > 0.05).
Conclusions
We demonstrated the feasibility of SSM-PCA in ICAS and obtained novel insights into complex hemodynamic impairment patterns and their association with cognitive function.
{"title":"Multivariate Pattern Analysis of Perfusion and Oxygenation Impairment in Asymptomatic Carotid Artery Stenosis","authors":"Jan Kufer, Christine Preibisch, Jens Göttler, Lena Schmitzer, Gabriel Hoffmann, Michael Kallmayer, Claus Zimmer, Fahmeed Hyder, Stephan Kaczmarz","doi":"10.1111/jon.70084","DOIUrl":"https://doi.org/10.1111/jon.70084","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>Hemodynamic impairment may contribute to stroke risk and cognitive decline in asymptomatic internal carotid artery stenosis (ICAS). Therefore, multimodal MRI-based quantification of hemodynamic impairment could inform improved treatment decisions. While gross interhemispheric hemodynamic imbalances have been reported in ICAS, identifying more spatially resolved patterns of disease-related alterations may be promising to harness the full potential of hemodynamic MRI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this feasibility study, we investigated the spatial topography of ICAS-related impairments by applying scaled subprofile model principal component analysis (SSM-PCA) to cerebral blood flow (CBF), relative oxygen extraction fraction (rOEF), and oxygen extraction capacity (OEF<sup>max</sup>) data of 21 unilateral ICAS patients and 25 healthy controls (HC).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We found spatially extended, partly overlapping disease-related patterns for CBF and OEF<sup>max</sup>, but not rOEF. CBF (area under the curve [AUC] = 0.95) but not OEF<sup>max</sup> (AUC = 0.72) SSM-PCA scores distinguished ICAS patients and HC better than interhemispheric lateralizations (AUC = 0.75/0.73). SSM-PCA scores were only partly explained by interhemispheric lateralization (<i>R</i><sup>2</sup> = −0.27/0.38), indicating complementary information. Critically, ICAS patients with higher OEF<sup>max</sup> SSM-PCA scores (<i>z</i> ≥ 1) demonstrated higher stenotic degrees and lower cognitive performance (<i>p</i> < 0.05) without differing in interhemispheric lateralization (<i>p</i> > 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We demonstrated the feasibility of SSM-PCA in ICAS and obtained novel insights into complex hemodynamic impairment patterns and their association with cognitive function.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jeffrey Lambe, Nicolas R. Thompson, Yadi Li, Kunio Nakamura, Daniel Ontaneda
Background and Purpose
Spinal cord pathology underpins disability accumulation in people with multiple sclerosis (pwMS). Visual inspection of spinal cord magentic resonance imaging (MRI) often fails to reliably detect injury. Radiomics analyzes signal intensities in images to identify pathological changes that may be imperceptible to the human eye. This study evaluated the application of radiomics to spinal cord MRI to distinguish subgroups of pwMS and disability correlations.
Methods
Radiomic features were extracted from upper cervical cord coverage on cross-sectional 3.0T brain noncontrasted T1-weighted MRI scans in pwMS and healthy controls (HCs). Ninety-three radiomic features—predominantly gray-level matrices—were extracted using Pyradiomics, with pixel heterogeneity considered to reflect neuroaxonal pathology. T2 lesion and brain substructure volumes were segmented from 3D fluid-attenuated inversion recovery and magnetization-prepared rapid gradient-echo sequences using an in-house 2.5D U-Net convolutional neural network to encapsulate neuroinflammation and neurodegeneration. Cervical cross-sectional area (C1−C3) was measured using in-house atlas-based segmentation. Imaging features were compared between pwMS and HCs, and pwMS by phenotype (relapsing vs. progressive), age, and race. Associations of imaging features with Patient-Determined Disease Steps (PDDS) were examined.
Results
Among 2966 pwMS and 41 HCs, we identified radiomic features distinguishing pwMS from HCs, and pwMS by phenotype, age, and race. Radiomic features exhibited stronger correlations with PDDS than conventional MRI measures.
Conclusions
Radiomics identified pathological changes in pwMS in varying stages of the disease course that are undetectable by conventional spinal cord MRI. Radiomics may increase the yield of spinal cord MRI in pwMS and serve as biomarkers predicting disability worsening.
{"title":"Association of Spinal Cord Radiomic Features and Disability in Multiple Sclerosis","authors":"Jeffrey Lambe, Nicolas R. Thompson, Yadi Li, Kunio Nakamura, Daniel Ontaneda","doi":"10.1111/jon.70089","DOIUrl":"https://doi.org/10.1111/jon.70089","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>Spinal cord pathology underpins disability accumulation in people with multiple sclerosis (pwMS). Visual inspection of spinal cord magentic resonance imaging (MRI) often fails to reliably detect injury. Radiomics analyzes signal intensities in images to identify pathological changes that may be imperceptible to the human eye. This study evaluated the application of radiomics to spinal cord MRI to distinguish subgroups of pwMS and disability correlations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Radiomic features were extracted from upper cervical cord coverage on cross-sectional 3.0T brain noncontrasted T1-weighted MRI scans in pwMS and healthy controls (HCs). Ninety-three radiomic features—predominantly gray-level matrices—were extracted using Pyradiomics, with pixel heterogeneity considered to reflect neuroaxonal pathology. T2 lesion and brain substructure volumes were segmented from 3D fluid-attenuated inversion recovery and magnetization-prepared rapid gradient-echo sequences using an in-house 2.5D U-Net convolutional neural network to encapsulate neuroinflammation and neurodegeneration. Cervical cross-sectional area (C1−C3) was measured using in-house atlas-based segmentation. Imaging features were compared between pwMS and HCs, and pwMS by phenotype (relapsing vs. progressive), age, and race. Associations of imaging features with Patient-Determined Disease Steps (PDDS) were examined.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 2966 pwMS and 41 HCs, we identified radiomic features distinguishing pwMS from HCs, and pwMS by phenotype, age, and race. Radiomic features exhibited stronger correlations with PDDS than conventional MRI measures.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Radiomics identified pathological changes in pwMS in varying stages of the disease course that are undetectable by conventional spinal cord MRI. Radiomics may increase the yield of spinal cord MRI in pwMS and serve as biomarkers predicting disability worsening.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emma Dereskewicz, Francesco La Rosa, Jonadab Dos Santos Silva, Edward Sizer, Amit Kohli, Maxence Wynen, William A. Mullins, Pietro Maggi, Sarah Levy, Kamso Onyemeh, Batuhan Ayci, Andrew J. Solomon, Jakob Assländer, Omar Al-Louzi, Daniel S. Reich, James Sumowski, Erin S. Beck
Background and Purpose
Assessment of brain lesions on magnetic resonance imaging (MRI) is crucial for research in multiple sclerosis (MS). Manual segmentation is time-consuming and inconsistent. We aimed to develop an automated MS lesion segmentation algorithm for T2-weighted fluid-attenuated inversion recovery (FLAIR) MRI.
Methods
We developed FLAIR Lesion Analysis in Multiple Sclerosis (FLAMeS), a deep learning-based MS lesion segmentation algorithm based on the nnU-Net 3D full-resolution U-Net and trained on 668 FLAIR 1.5 and 3 tesla scans from persons with MS. FLAMeS was evaluated on three external datasets: MSSEG-2 (n = 14), MSLesSeg (n = 51), and a clinical cohort (n = 10), and compared to SAMSEG, LST-LPA, and LST-AI. Performance was assessed qualitatively by two blinded experts and quantitatively by comparing automated and ground truth lesion masks using standard segmentation metrics.
Results
In a blinded qualitative review of 20 scans, both raters selected FLAMeS as the most accurate segmentation in 15 cases, with one rater favoring FLAMeS in two additional cases. Across all testing datasets, FLAMeS achieved a mean Dice score of 0.74, a true positive rate of 0.84, and an F1 score of 0.78, consistently outperforming the benchmark methods. For other metrics, including positive predictive value, relative volume difference, and false positive rate, FLAMeS performed similarly to or better than benchmark methods. Most lesions missed by FLAMeS were smaller than 10 mm3, whereas the benchmark methods missed larger lesions in addition to smaller ones.
Conclusions
FLAMeS is an accurate, robust method for MS lesion segmentation that outperforms other publicly available methods.
{"title":"A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation","authors":"Emma Dereskewicz, Francesco La Rosa, Jonadab Dos Santos Silva, Edward Sizer, Amit Kohli, Maxence Wynen, William A. Mullins, Pietro Maggi, Sarah Levy, Kamso Onyemeh, Batuhan Ayci, Andrew J. Solomon, Jakob Assländer, Omar Al-Louzi, Daniel S. Reich, James Sumowski, Erin S. Beck","doi":"10.1111/jon.70085","DOIUrl":"10.1111/jon.70085","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>Assessment of brain lesions on magnetic resonance imaging (MRI) is crucial for research in multiple sclerosis (MS). Manual segmentation is time-consuming and inconsistent. We aimed to develop an automated MS lesion segmentation algorithm for T2-weighted fluid-attenuated inversion recovery (FLAIR) MRI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We developed FLAIR Lesion Analysis in Multiple Sclerosis (FLAMeS), a deep learning-based MS lesion segmentation algorithm based on the nnU-Net 3D full-resolution U-Net and trained on 668 FLAIR 1.5 and 3 tesla scans from persons with MS. FLAMeS was evaluated on three external datasets: MSSEG-2 (<i>n</i> = 14), MSLesSeg (<i>n</i> = 51), and a clinical cohort (<i>n</i> = 10), and compared to SAMSEG, LST-LPA, and LST-AI. Performance was assessed qualitatively by two blinded experts and quantitatively by comparing automated and ground truth lesion masks using standard segmentation metrics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In a blinded qualitative review of 20 scans, both raters selected FLAMeS as the most accurate segmentation in 15 cases, with one rater favoring FLAMeS in two additional cases. Across all testing datasets, FLAMeS achieved a mean Dice score of 0.74, a true positive rate of 0.84, and an F1 score of 0.78, consistently outperforming the benchmark methods. For other metrics, including positive predictive value, relative volume difference, and false positive rate, FLAMeS performed similarly to or better than benchmark methods. Most lesions missed by FLAMeS were smaller than 10 mm<sup>3</sup>, whereas the benchmark methods missed larger lesions in addition to smaller ones.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>FLAMeS is an accurate, robust method for MS lesion segmentation that outperforms other publicly available methods.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70085","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145040383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To review the existing evidence on multiple timepoint assessments of optic nerve sheath diameter (ONSD) as an indicator of intraindividual variation of intracranial pressure (ICP).
Methods
A systematic search identified studies assessing intraindividual variation in ICP through multiple timepoint measurements of ONSD using ultrasonography. Meta-analysis of studies assessing intraindividual correlation coefficients between ONSD and ICP was performed using a random effects model, and we calculated the weighted correlation coefficient for the expected change in ICP associated with variations in ONSD.
Results
A total of five studies, comprising 157 patients, were included in the review. ONSD was compared with invasive ICP measurement methods at multiple timepoints. Meta-analysis of intraindividual ONSD–ICP correlation demonstrated a correlation coefficient of 0.62 (CI: 0.50–0.71). Individual linear correlation analyses were performed in two of the studies, yielding correlation coefficients ranging from 0.79 to 1.00; however, widely variable individual slopes were found (1.51–41.43 mm/mmHg). ONSD variations ranged from 0.12 to 3.30 mm per 5 mmHg change in ICP, with a variation of 0.55 mm in adults with hypoxic brain injury and 0.77 mm in children with idiopathic intracranial hypertension.
Conclusions
Our findings indicate that ONSD significantly correlates with ICP, and longitudinal intraindividual assessment shows a predominantly linear correlation between both variables. A personalized ONSD–ICP correlation equation may enable accurate ICP prediction, making ONSD a useful tool for follow-up in patients with previous invasive ICP measurements, when adjusted to each patient's characteristics and pathologies.
{"title":"Intraindividual Optic Nerve Sheath Variation and Intracranial Pressure Changes: A Systematic Review and Meta-Analysis","authors":"Henrique Azevedo, Lia Lucas Neto, David Berhanu","doi":"10.1111/jon.70083","DOIUrl":"https://doi.org/10.1111/jon.70083","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Purpose</h3>\u0000 \u0000 <p>To review the existing evidence on multiple timepoint assessments of optic nerve sheath diameter (ONSD) as an indicator of intraindividual variation of intracranial pressure (ICP).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A systematic search identified studies assessing intraindividual variation in ICP through multiple timepoint measurements of ONSD using ultrasonography. Meta-analysis of studies assessing intraindividual correlation coefficients between ONSD and ICP was performed using a random effects model, and we calculated the weighted correlation coefficient for the expected change in ICP associated with variations in ONSD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of five studies, comprising 157 patients, were included in the review. ONSD was compared with invasive ICP measurement methods at multiple timepoints. Meta-analysis of intraindividual ONSD–ICP correlation demonstrated a correlation coefficient of 0.62 (CI: 0.50–0.71). Individual linear correlation analyses were performed in two of the studies, yielding correlation coefficients ranging from 0.79 to 1.00; however, widely variable individual slopes were found (1.51–41.43 mm/mmHg). ONSD variations ranged from 0.12 to 3.30 mm per 5 mmHg change in ICP, with a variation of 0.55 mm in adults with hypoxic brain injury and 0.77 mm in children with idiopathic intracranial hypertension.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our findings indicate that ONSD significantly correlates with ICP, and longitudinal intraindividual assessment shows a predominantly linear correlation between both variables. A personalized ONSD–ICP correlation equation may enable accurate ICP prediction, making ONSD a useful tool for follow-up in patients with previous invasive ICP measurements, when adjusted to each patient's characteristics and pathologies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jon.70083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145012376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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