1
|
Wang X, Wang X, Yan Z, Yin F, Li Y, Liu X, Liu Y. Enhanced choroid plexus segmentation with 3D UX-Net and its association with disease progression in multiple sclerosis. Mult Scler Relat Disord 2024; 88:105750. [PMID: 38986172 DOI: 10.1016/j.msard.2024.105750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 06/26/2024] [Accepted: 06/27/2024] [Indexed: 07/12/2024]
Abstract
BACKGROUND The choroid plexus (CP) is suggested to be closely associated with the neuroinflammation of multiple sclerosis (MS). Segmentation based on deep learning (DL) could facilitate rapid and reproducible volume assessment of the CP, which is crucial for elucidating its role in MS. PURPOSE To develop a reliable DL model for the automatic segmentation of CP, and further validate its clinical significance in MS. METHODS The 3D UX-Net model (3D U-Net used for comparison) was trained and validated on T1-weighted MRI from a cohort of 216 relapsing-remitting MS (RRMS) patients and 75 healthy subjects. Among these, 53 RRMS with baseline and 2-year follow-up scans formed an internal test set (dataset1b). Another 58 RRMS from multi-center data served as an external test set (dataset2). Dice coefficient was computed to assess segmentation performance. Compare the correlation of CP volume obtained through automatic and manual segmentation with clinical outcomes in MS. Disability and cognitive function of patients were assessed using the Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT). RESULTS The 3D UX-Net model achieved Dice coefficients of 0.875 ± 0.030 and 0.870 ± 0.044 for CP segmentation on dataset1b and dataset2, respectively, outperforming 3D U-Net's scores of 0.809 ± 0.098 and 0.601 ± 0.226. Furthermore, CP volumes segmented by the 3D UX-Net model aligned consistently with clinical outcomes compared to manual segmentation. In dataset1b, both manual and automatic segmentation revealed a significant positive correlation between normalized CP volume (nCPV) and EDSS scores at baseline (manual: r = 0.285, p = 0.045; automatic: r = 0.287, p = 0.044) and a negative correlation with SDMT scores (manual: r = -0.331, p = 0.020; automatic: r = -0.329, p = 0.021). In dataset2, similar correlations were found with EDSS scores (manual: r = 0.337, p = 0.021; automatic: r = 0.346, p = 0.017). Meanwhile, in dataset1b, both manual and automatic segmentation revealed a significant increase in nCPV from baseline to follow-up (p < 0.05). The increase of nCPV was more pronounced in patients with disability worsened than stable patients (manual: p = 0.023; automatic: p = 0.018). Patients receiving disease-modifying therapy (DMT) exhibited a significantly lower nCPV increase than untreated patients (manual: p = 0.004; automatic: p = 0.004). CONCLUSION The 3D UX-Net model demonstrated strong segmentation performance for the CP, and the automatic segmented CP can be directly used in MS clinical practice. CP volume can serve as a surrogate imaging biomarker for monitoring disease progression and DMT response in MS patients.
Collapse
Affiliation(s)
- Xiaohua Wang
- College of Medical Informatics, Chongqing Medical University, Chongqing, 400016, China; Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaolong Wang
- College of Computer and Information Science, Southwest University, Chongqing, 400054, China
| | - Zichun Yan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Feiyue Yin
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
| | - Xiaojuan Liu
- College of Computer and Information Science, Southwest University, Chongqing, 400054, China.
| | - Yanbing Liu
- College of Medical Informatics, Chongqing Medical University, Chongqing, 400016, China.
| |
Collapse
|
2
|
Li J, Hu Y, Xu Y, Feng X, Meyer CH, Dai W, Zhao L. Associations between the choroid plexus and tau in Alzheimer's disease using an active learning segmentation pipeline. Fluids Barriers CNS 2024; 21:56. [PMID: 38997764 PMCID: PMC11245807 DOI: 10.1186/s12987-024-00554-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/26/2024] [Indexed: 07/14/2024] Open
Abstract
BACKGROUND The cerebrospinal fluid (CSF), primarily generated by the choroid plexus (ChP), is the major carrier of the glymphatic system. The alternations of CSF production and the ChP can be associated with the Alzheimer's disease (AD). The present work investigated the roles of the ChP in the AD based on a proposed ChP image segmentation pipeline. METHODS A human-in-the-loop ChP image segmentation pipeline was implemented with intermediate and active learning datasets. The performance of the proposed pipeline was evaluated on manual contours by five radiologists, compared to the FreeSurfer and FastSurfer toolboxes. The ChP volume and blood flow were investigated among AD groups. The correlations between the ChP volume and AD CSF biomarkers including phosphorylated tau (p-tau), total tau (t-tau), amyloid-β42 (Aβ42), and amyloid-β40 (Aβ40) was investigated using three models (univariate, multiple variables, and stepwise regression) on two datasets with 806 and 320 subjects. RESULTS The proposed ChP segmentation pipeline achieved superior performance with a Dice coefficient of 0.620 on the test dataset, compared to the FreeSurfer (0.342) and FastSurfer (0.371). Significantly larger volumes (p < 0.001) and higher perfusion (p = 0.032) at the ChP were found in AD compared to CN groups. Significant correlations were found between the tau and the relative ChP volume (the ChP volume and ChP/parenchyma ratio) in each patient groups and in the univariate regression analysis (p < 0.001), the multiple regression model (p < 0.05 except for the t-tau in the LMCI), and in the step-wise regression model (p < 0.021). In addition, the correlation coefficients changed from - 0.32 to - 0.21 along with the AD progression in the multiple regression model. In contrast, the Aβ42 and Aβ40 shows consistent and significant associations with the lateral ventricle related measures in the step-wise regression model (p < 0.027). CONCLUSIONS The proposed pipeline provided accurate ChP segmentation which revealed the associations between the ChP and tau level in the AD. The proposed pipeline is available on GitHub ( https://github.com/princeleeee/ChP-Seg ).
Collapse
Affiliation(s)
- Jiaxin Li
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yueqin Hu
- Psychology, Beijing Normal University, Beijing, China
| | - Yunzhi Xu
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xue Feng
- Biomedical Engineering, University of Virginia, Charlottesville, VA, US
| | - Craig H Meyer
- Biomedical Engineering, University of Virginia, Charlottesville, VA, US
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, US
| | - Li Zhao
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
| |
Collapse
|
3
|
Demuth S, Paris J, Faddeenkov I, De Sèze J, Gourraud PA. Clinical applications of deep learning in neuroinflammatory diseases: A scoping review. Rev Neurol (Paris) 2024:S0035-3787(24)00522-8. [PMID: 38772806 DOI: 10.1016/j.neurol.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 03/26/2024] [Accepted: 04/09/2024] [Indexed: 05/23/2024]
Abstract
BACKGROUND Deep learning (DL) is an artificial intelligence technology that has aroused much excitement for predictive medicine due to its ability to process raw data modalities such as images, text, and time series of signals. OBJECTIVES Here, we intend to give the clinical reader elements to understand this technology, taking neuroinflammatory diseases as an illustrative use case of clinical translation efforts. We reviewed the scope of this rapidly evolving field to get quantitative insights about which clinical applications concentrate the efforts and which data modalities are most commonly used. METHODS We queried the PubMed database for articles reporting DL algorithms for clinical applications in neuroinflammatory diseases and the radiology.healthairegister.com website for commercial algorithms. RESULTS The review included 148 articles published between 2018 and 2024 and five commercial algorithms. The clinical applications could be grouped as computer-aided diagnosis, individual prognosis, functional assessment, the segmentation of radiological structures, and the optimization of data acquisition. Our review highlighted important discrepancies in efforts. The segmentation of radiological structures and computer-aided diagnosis currently concentrate most efforts with an overrepresentation of imaging. Various model architectures have addressed different applications, relatively low volume of data, and diverse data modalities. We report the high-level technical characteristics of the algorithms and synthesize narratively the clinical applications. Predictive performances and some common a priori on this topic are finally discussed. CONCLUSION The currently reported efforts position DL as an information processing technology, enhancing existing modalities of paraclinical investigations and bringing perspectives to make innovative ones actionable for healthcare.
Collapse
Affiliation(s)
- S Demuth
- Inserm U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 44000 Nantes, France; Inserm U1119 : biopathologie de la myéline, neuroprotection et stratégies thérapeutiques, University of Strasbourg, 1, rue Eugène-Boeckel - CS 60026, 67084 Strasbourg, France.
| | - J Paris
- Inserm U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 44000 Nantes, France
| | - I Faddeenkov
- Inserm U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 44000 Nantes, France
| | - J De Sèze
- Inserm U1119 : biopathologie de la myéline, neuroprotection et stratégies thérapeutiques, University of Strasbourg, 1, rue Eugène-Boeckel - CS 60026, 67084 Strasbourg, France; Department of Neurology, University Hospital of Strasbourg, 1, avenue Molière, 67200 Strasbourg, France; Inserm CIC 1434 Clinical Investigation Center, University Hospital of Strasbourg, 1, avenue Molière, 67200 Strasbourg, France
| | - P-A Gourraud
- Inserm U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 44000 Nantes, France; "Data clinic", Department of Public Health, University Hospital of Nantes, Nantes, France
| |
Collapse
|
4
|
Storelli L, Pagani E, Rubin M, Margoni M, Filippi M, Rocca MA. A Fully Automatic Method to Segment Choroid Plexuses in Multiple Sclerosis Using Conventional MRI Sequences. J Magn Reson Imaging 2024; 59:1643-1652. [PMID: 37530734 DOI: 10.1002/jmri.28937] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/19/2023] [Accepted: 07/20/2023] [Indexed: 08/03/2023] Open
Abstract
BACKGROUND Choroid plexus (CP) volume has been recently proposed as a proxy for brain neuroinflammation in multiple sclerosis (MS). PURPOSE To develop and validate a fast automatic method to segment CP using routinely acquired brain T1-weighted and FLAIR MRI. STUDY TYPE Retrospective. POPULATION Fifty-five MS patients (33 relapsing-remitting, 22 progressive; mean age = 46.8 ± 10.2 years; 31 women) and 60 healthy controls (HC; mean age = 36.1 ± 12.6 years, 33 women). FIELD STRENGTH/SEQUENCE 3D T2-weighted FLAIR and 3D T1-weighted gradient echo sequences at 3.0 T. ASSESSMENT Brain tissues were segmented on T1-weighted sequences and a Gaussian Mixture Model (GMM) was fitted to FLAIR image intensities obtained from the ventricle masks of the SIENAX. A second GMM was then applied on the thresholded and filtered ventricle mask. CP volumes were automatically determined and compared with those from manual segmentation by two raters (with 3 and 10 years' experience; reference standard). CP volumes from previously published automatic segmentation methods (freely available Freesurfer [FS] and FS-GMM) were also compared with reference standard. Expanded Disability Status Scale (EDSS) score was assessed within 3 days of MRI. Computational time was assessed for each automatic technique and manual segmentation. STATISTICAL TESTS Comparisons of CP volumes with reference standard were evaluated with Bland Altman analysis. Dice similarity coefficients (DSC) were computed to assess automatic CP segmentations. Volume differences between MS and HC for each method were assessed with t-tests and correlations of CP volumes with EDSS were assessed with Pearson's correlation coefficients (R). A P value <0.05 was considered statistically significant. RESULTS Compared to manual segmentation, the proposed method had the highest segmentation accuracy (mean DSC = 0.65 ± 0.06) compared to FS (mean DSC = 0.37 ± 0.08) and FS-GMM (0.58 ± 0.06). The percentage CP volume differences relative to manual segmentation were -0.1% ± 0.23, 4.6% ± 2.5, and -0.48% ± 2 for the proposed method, FS, and FS-GMM, respectively. The Pearson's correlations between automatically obtained CP volumes and the manually obtained volumes were 0.70, 0.54, and 0.56 for the proposed method, FS, and FS-GMM, respectively. A significant correlation between CP volume and EDSS was found for the proposed automatic pipeline (R = 0.2), for FS-GMM (R = 0.3) and for manual segmentation (R = 0.4). Computational time for the proposed method (32 ± 2 minutes) was similar to the manual segmentation (20 ± 5 minutes) but <25% of the FS (120 ± 15 minutes) and FS-GMM (125 ± 15 minutes) methods. DATA CONCLUSION This study developed an accurate and easily implementable method for automatic CP segmentation in MS using T1-weighted and FLAIR MRI. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 4.
Collapse
Affiliation(s)
- Loredana Storelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Martina Rubin
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| |
Collapse
|
5
|
Andravizou A, Stavropoulou De Lorenzo S, Kesidou E, Michailidou I, Parissis D, Boziki MK, Stamati P, Bakirtzis C, Grigoriadis N. The Time Trajectory of Choroid Plexus Enlargement in Multiple Sclerosis. Healthcare (Basel) 2024; 12:768. [PMID: 38610190 PMCID: PMC11011748 DOI: 10.3390/healthcare12070768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 03/22/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
Choroid plexus (CP) can be seen as a watchtower of the central nervous system (CNS) that actively regulates CNS homeostasis. A growing body of literature suggests that CP alterations are involved in the pathogenesis of multiple sclerosis (MS) but the underlying mechanisms remain elusive. CPs are enlarged and inflamed in relapsing-remitting (RRMS) but also in clinically isolated syndrome (CIS) and radiologically isolated syndrome (RIS) stages, far beyond MS diagnosis. Increases in the choroid plexus/total intracranial volume (CP/TIV) ratio have been robustly associated with increased lesion load, higher translocator protein (TSPO) uptake in normal-appearing white matter (NAWM) and thalami, as well as with higher annual relapse rate and disability progression in highly active RRMS individuals, but not in progressive MS. The CP/TIV ratio has only slightly been correlated with magnetic resonance imaging (MRI) findings (cortical or whole brain atrophy) and clinical outcomes (EDSS score) in progressive MS. Therefore, we suggest that plexus volumetric assessments should be mainly applied to the early disease stages of MS, whereas it should be taken into consideration with caution in progressive MS. In this review, we attempt to clarify the pathological significance of the temporal CP volume (CPV) changes in MS and highlight the pitfalls and limitations of CP volumetric analysis.
Collapse
Affiliation(s)
- Athina Andravizou
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| | - Sotiria Stavropoulou De Lorenzo
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| | - Evangelia Kesidou
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| | - Iliana Michailidou
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| | - Dimitrios Parissis
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| | - Marina-Kleopatra Boziki
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| | - Polyxeni Stamati
- Department of Neurology, University Hospital of Larissa, 41334 Larissa, Greece;
| | - Christos Bakirtzis
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| | - Nikolaos Grigoriadis
- Multiple Sclerosis Center, Second Department of Neurology, School of Medicine, Aristotle University of Thessaloniki, 54621 Thessaloniki, Greece; (A.A.); (S.S.D.L.); (E.K.); (I.M.); (D.P.); (M.-K.B.); (N.G.)
| |
Collapse
|
6
|
Klistorner S, Barnett MH, Wang C, Parratt J, Yiannikas C, Klistorner A. Longitudinal enlargement of choroid plexus is associated with chronic lesion expansion and neurodegeneration in RRMS patients. Mult Scler 2024; 30:496-504. [PMID: 38318807 PMCID: PMC11010552 DOI: 10.1177/13524585241228423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 12/27/2023] [Accepted: 01/09/2024] [Indexed: 02/07/2024]
Abstract
BACKGROUND AND OBJECTIVE We explored dynamic changes in the choroid plexus (CP) in patients with relapsing-remitting multiple sclerosis (RRMS) and assessed its relationship with chronic lesion expansion and atrophy in various brain compartments. METHODS Fifty-seven RRMS patients were annually assessed for a minimum of 48 months with 3D FLAIR, pre- and post-contrast 3D T1 and diffusion-weighted magnetic resonance imaging (MRI). The CP was manually segmented at baseline and last follow-up. RESULTS The volume of CP significantly increased by 1.4% annually. However, the extent of CP enlargement varied considerably among individuals (ranging from -3.6 to 150.8 mm3 or -0.2% to 6.3%). The magnitude of CP enlargement significantly correlated with central (r = 0.70, p < 0.001) and total brain atrophy (r = -0.57, p < 0.001), white (r = -0.61, p < 0.001) and deep grey matter atrophy (r = -0.60, p < 0.001). Progressive CP enlargement was significantly associated with the volume and extent of chronic lesion expansion (r = 0.60, p < 0.001), but not with the number or volume of new lesions. CONCLUSION This study provides evidence of progressive CP enlargement in patients with RRMS. Our findings also demonstrate that enlargement of the CP volume is linked to the expansion of chronic lesions and neurodegeneration of periventricular white and grey matter in RRMS patients.
Collapse
Affiliation(s)
- Samuel Klistorner
- Save Sight Institute, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
| | - Michael H Barnett
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- Sydney Neuroimaging Analysis Centre, Camperdown, NSW, Australia; Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Chenyu Wang
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia/Sydney Neuroimaging Analysis Centre, Camperdown, NSW, Australia
| | - John Parratt
- Royal North Shore Hospital, Sydney, NSW, Australia
| | | | - Alexander Klistorner
- Save Sight Institute, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
| |
Collapse
|
7
|
Bannai D, Reuter M, Hegde R, Hoang D, Adhan I, Gandu S, Pong S, Raymond N, Zeng V, Chung Y, He G, Sun D, van Erp TGM, Addington J, Bearden CE, Cadenhead K, Cornblatt B, Mathalon DH, McGlashan T, Jeffries C, Stone W, Tsuang M, Walker E, Woods SW, Cannon TD, Perkins D, Keshavan M, Lizano P. Linking enlarged choroid plexus with plasma analyte and structural phenotypes in clinical high risk for psychosis: A multisite neuroimaging study. Brain Behav Immun 2024; 117:70-79. [PMID: 38169244 DOI: 10.1016/j.bbi.2023.12.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 12/04/2023] [Accepted: 12/19/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Choroid plexus (ChP) enlargement exists in first-episode and chronic psychosis, but whether enlargement occurs before psychosis onset is unknown. This study investigated whether ChP volume is enlarged in individuals with clinical high-risk (CHR) for psychosis and whether these changes are related to clinical, neuroanatomical, and plasma analytes. METHODS Clinical and neuroimaging data from the North American Prodrome Longitudinal Study 2 (NAPLS2) was used for analysis. 509 participants (169 controls, 340 CHR) were recruited. Conversion status was determined after 2-years of follow-up, with 36 psychosis converters. The lateral ventricle ChP was manually segmented from baseline scans. A subsample of 31 controls and 53 CHR had plasma analyte and neuroimaging data. RESULTS Compared to controls, CHR (d = 0.23, p = 0.017) and non-converters (d = 0.22, p = 0.03) demonstrated higher ChP volumes, but not in converters. In CHR, greater ChP volume correlated with lower cortical (r = -0.22, p < 0.001), subcortical gray matter (r = -0.21, p < 0.001), and total white matter volume (r = -0.28,p < 0.001), as well as larger lateral ventricle volume (r = 0.63,p < 0.001). Greater ChP volume correlated with makers functionally associated with the lateral ventricle ChP in CHR [CCL1 (r = -0.30, p = 0.035), ICAM1 (r = 0.33, p = 0.02)], converters [IL1β (r = 0.66, p = 0.004)], and non-converters [BMP6 (r = -0.96, p < 0.001), CALB1 (r = -0.98, p < 0.001), ICAM1 (r = 0.80, p = 0.003), SELE (r = 0.59, p = 0.026), SHBG (r = 0.99, p < 0.001), TNFRSF10C (r = 0.78, p = 0.001)]. CONCLUSIONS CHR and non-converters demonstrated significantly larger ChP volumes compared to controls. Enlarged ChP was associated with neuroanatomical alterations and analyte markers functionally associated with the ChP. These findings suggest that the ChP may be a key an important biomarker in CHR.
Collapse
Affiliation(s)
- Deepthi Bannai
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Martin Reuter
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Rachal Hegde
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dung Hoang
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Iniya Adhan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Swetha Gandu
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sovannarath Pong
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Nick Raymond
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Victor Zeng
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yoonho Chung
- Department of Psychology, Yale University, New Haven, CT, USA
| | - George He
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Daqiang Sun
- Semel Institute for Neuroscience and Human Behavior and Department of Psychology, UCLA, Los Angeles, CA, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, UC Irvine, Irvine, CA, USA
| | - Jean Addington
- Hotchkins Brain Institute, Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior and Department of Psychology, UCLA, Los Angeles, CA, USA
| | | | | | | | | | - Clark Jeffries
- Renaissance Computing Institute, University of North Carolina, Chapel Hill, NC, USA
| | - William Stone
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Ming Tsuang
- Department of Psychiatry, UCSD, San Diego, CA, USA
| | - Elaine Walker
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA; Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Diana Perkins
- Renaissance Computing Institute, University of North Carolina, Chapel Hill, NC, USA; Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| |
Collapse
|
8
|
Eisma JJ, McKnight CD, Hett K, Elenberger J, Han CJ, Song AK, Considine C, Claassen DO, Donahue MJ. Deep learning segmentation of the choroid plexus from structural magnetic resonance imaging (MRI): validation and normative ranges across the adult lifespan. Fluids Barriers CNS 2024; 21:21. [PMID: 38424598 PMCID: PMC10903155 DOI: 10.1186/s12987-024-00525-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 02/21/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND The choroid plexus functions as the blood-cerebrospinal fluid (CSF) barrier, plays an important role in CSF production and circulation, and has gained increased attention in light of the recent elucidation of CSF circulation dysfunction in neurodegenerative conditions. However, methods for routinely quantifying choroid plexus volume are suboptimal and require technical improvements and validation. Here, we propose three deep learning models that can segment the choroid plexus from commonly-acquired anatomical MRI data and report performance metrics and changes across the adult lifespan. METHODS Fully convolutional neural networks were trained from 3D T1-weighted, 3D T2-weighted, and 2D T2-weighted FLAIR MRI using gold-standard manual segmentations in control and neurodegenerative participants across the lifespan (n = 50; age = 21-85 years). Dice coefficients, 95% Hausdorff distances, and area-under-curve (AUCs) were calculated for each model and compared to segmentations from FreeSurfer using two-tailed Wilcoxon tests (significance criteria: p < 0.05 after false discovery rate multiple comparisons correction). Metrics were regressed against lateral ventricular volume using generalized linear models to assess model performance for varying levels of atrophy. Finally, models were applied to an expanded cohort of adult controls (n = 98; age = 21-89 years) to provide an exemplar of choroid plexus volumetry values across the lifespan. RESULTS Deep learning results yielded Dice coefficient = 0.72, Hausdorff distance = 1.97 mm, AUC = 0.87 for T1-weighted MRI, Dice coefficient = 0.72, Hausdorff distance = 2.22 mm, AUC = 0.87 for T2-weighted MRI, and Dice coefficient = 0.74, Hausdorff distance = 1.69 mm, AUC = 0.87 for T2-weighted FLAIR MRI; values did not differ significantly between MRI sequences and were statistically improved compared to current commercially-available algorithms (p < 0.001). The intraclass coefficients were 0.95, 0.95, and 0.96 between T1-weighted and T2-weighted FLAIR, T1-weighted and T2-weighted, and T2-weighted and T2-weighted FLAIR models, respectively. Mean lateral ventricle choroid plexus volume across all participants was 3.20 ± 1.4 cm3; a significant, positive relationship (R2 = 0.54-0.60) was observed between participant age and choroid plexus volume for all MRI sequences (p < 0.001). CONCLUSIONS Findings support comparable performance in choroid plexus delineation between standard, clinically available, non-contrasted anatomical MRI sequences. The software embedding the evaluated models is freely available online and should provide a useful tool for the growing number of studies that desire to quantitatively evaluate choroid plexus structure and function ( https://github.com/hettk/chp_seg ).
Collapse
Affiliation(s)
- Jarrod J Eisma
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kilian Hett
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA
| | - Jason Elenberger
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA
| | - Caleb J Han
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA
| | - Alexander K Song
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA
| | - Ciaran Considine
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA
| | - Daniel O Claassen
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA
| | - Manus J Donahue
- Department of Neurology, Behavioral and Cognitive Neurology, Vanderbilt University Medical Center, 1500 21 stAve South, Village at Vanderbilt, Suite 2600, Nashville, TN, 37212, USA.
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
| |
Collapse
|
9
|
Visani V, Pizzini FB, Natale V, Tamanti A, Anglani M, Bertoldo A, Calabrese M, Castellaro M. Choroid plexus volume in multiple sclerosis can be estimated on structural MRI avoiding contrast injection. Eur Radiol Exp 2024; 8:33. [PMID: 38409562 PMCID: PMC10897123 DOI: 10.1186/s41747-024-00421-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 12/11/2023] [Indexed: 02/28/2024] Open
Abstract
We compared choroid plexus (ChP) manual segmentation on non-contrast-enhanced (non-CE) sequences and reference standard CE T1- weighted (T1w) sequences in 61 multiple sclerosis patients prospectively included. ChP was separately segmented on T1w, T2-weighted (T2w) fluid-attenuated inversion-recovery (FLAIR), and CE-T1w sequences. Inter-rater variability assessed on 10 subjects showed high reproducibility between sequences measured by intraclass correlation coefficient (T1w 0.93, FLAIR 0.93, CE-T1w 0.99). CE-T1w showed higher signal-to-noise ratio and contrast-to-noise ratio (CE-T1w 23.77 and 18.49, T1w 13.73 and 7.44, FLAIR 13.09 and 10.77, respectively). Manual segmentation of ChP resulted 3.073 ± 0.563 mL (mean ± standard deviation) on T1w, 3.787 ± 0.679 mL on FLAIR, and 2.984 ± 0.506 mL on CE-T1w images, with an error of 28.02 ± 19.02% for FLAIR and 3.52 ± 12.61% for T1w. FLAIR overestimated ChP volume compared to CE-T1w (p < 0.001). The Dice similarity coefficient of CE-T1w versus T1w and FLAIR was 0.67 ± 0.05 and 0.68 ± 0.05, respectively. Spatial error distribution per slice was calculated after nonlinear coregistration to the standard MNI152 space and showed a heterogeneous profile along the ChP especially near the fornix and the hippocampus. Quantitative analyses suggest T1w as a surrogate of CE-T1w to estimate ChP volume.Relevance statement To estimate the ChP volume, CE-T1w can be replaced by non-CE T1w sequences because the error is acceptable, while FLAIR overestimates the ChP volume. This encourages the development of automatic tools for ChP segmentation, also improving the understanding of the role of the ChP volume in multiple sclerosis, promoting longitudinal studies.Key points • CE-T1w sequences are considered the reference standard for ChP manual segmentation.• FLAIR sequences showed a higher CNR than T1w sequences but overestimated the ChP volume.• Non-CE T1w sequences can be a surrogate of CE-T1w sequences for manual segmentation of ChP.
Collapse
Affiliation(s)
- Valentina Visani
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Francesca B Pizzini
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Valerio Natale
- Department of Diagnostic and Public Health, University of Verona, Verona, Italy
| | - Agnese Tamanti
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Massimiliano Calabrese
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Marco Castellaro
- Department of Information Engineering, University of Padova, Padova, Italy.
| |
Collapse
|
10
|
Parobková V, Kompaníková P, Lázňovský J, Kavková M, Hampl M, Buchtová M, Zikmund T, Kaiser J, Bryja V. Ch OP-CT: quantitative morphometrical analysis of the Hindbrain Choroid Plexus by X-ray micro-computed tomography. Fluids Barriers CNS 2024; 21:9. [PMID: 38268040 DOI: 10.1186/s12987-023-00502-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/11/2023] [Indexed: 01/26/2024] Open
Abstract
The Hindbrain Choroid Plexus is a complex, cerebrospinal fluid-secreting tissue that projects into the 4th vertebrate brain ventricle. Despite its irreplaceability in the development and homeostasis of the entire central nervous system, the research of Hindbrain Choroid Plexus and other Choroid Plexuses has been neglected by neuroscientists for decades. One of the obstacles is the lack of tools that describe the complex shape of the Hindbrain Choroid Plexus in the context of brain ventricles. Here we introduce an effective tool, termed ChOP-CT, for the noninvasive, X-ray micro-computed tomography-based, three-dimensional visualization and subsequent quantitative spatial morphological analysis of developing mouse Hindbrain Choroid Plexus. ChOP-CT can reliably quantify Hindbrain Choroid Plexus volume, surface area, length, outgrowth angle, the proportion of the ventricular space occupied, asymmetries and general shape alterations in mouse embryos from embryonic day 13.5 onwards. We provide evidence that ChOP-CT is suitable for the unbiased evaluation and detection of the Hindbrain Choroid Plexus alterations within various mutant embryos. We believe, that thanks to its versatility, quantitative nature and the possibility of automation, ChOP-CT will facilitate the analysis of the Hindbrain Choroid Plexus in the mouse models. This will ultimately accelerate the screening of the candidate genes and mechanisms involved in the onset of various Hindbrain Choroid Plexus-related diseases.
Collapse
Affiliation(s)
- Viktória Parobková
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Petra Kompaníková
- Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic
| | - Jakub Lázňovský
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Michaela Kavková
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Marek Hampl
- Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic
- Laboratory of Molecular Morphogenesis, Institute of Animal Physiology and Genetics, Czech Academy of Sciences, 602 00, Brno, Czech Republic
| | - Marcela Buchtová
- Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic
- Laboratory of Molecular Morphogenesis, Institute of Animal Physiology and Genetics, Czech Academy of Sciences, 602 00, Brno, Czech Republic
| | - Tomáš Zikmund
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic.
| | - Jozef Kaiser
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Vítězslav Bryja
- Department of Experimental Biology, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic.
- Department of Cytokinetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Brno, Czech Republic.
| |
Collapse
|
11
|
Ricigliano VAG, Stankoff B. Choroid plexuses at the interface of peripheral immunity and tissue repair in multiple sclerosis. Curr Opin Neurol 2023; 36:214-221. [PMID: 37078651 DOI: 10.1097/wco.0000000000001160] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
PURPOSE OF REVIEW Choroid plexuses (ChPs) are key actors of the blood-to-cerebrospinal-fluid barrier and serve as brain immune checkpoint. The past years have seen a regain of interest about their potential involvement in the physiopathology of neuroinflammatory disorders like multiple sclerosis (MS). This article offers an overview of the recent findings on ChP alterations in MS, with a focus on the imaging tools able to detect these abnormalities and on their involvement in inflammation, tissue damage and repair. RECENT FINDINGS On MRI, ChPs are enlarged in people with MS (PwMS) versus healthy individuals. This size increase is an early event, already detected in presymptomatic and pediatric MS. Enlargement of ChPs is linked to local inflammatory infiltrates, and their dysfunction selectively impacts periventricular damage, larger ChPs predicting the expansion of chronic active lesions, smoldering inflammation and remyelination failure in tissues surrounding the ventricles. ChP volumetry may add value for the prediction of disease activity and disability worsening. SUMMARY ChP imaging metrics are emerging as possible biomarkers of neuroinflammation and repair failure in MS. Future works combining multimodal imaging techniques should provide a more refined characterization of ChP functional changes, their link with tissue damage, blood to cerebrospinal-fluid barrier dysfunction and fluid trafficking in MS.
Collapse
Affiliation(s)
- Vito A G Ricigliano
- Sorbonne Université, Paris Brain Institute, ICM, CNRS, Inserm
- Neurology Department, Pitié-Salpêtrière Hospital
| | - Bruno Stankoff
- Sorbonne Université, Paris Brain Institute, ICM, CNRS, Inserm
- Neurology Department, St Antoine Hospital, APHP-Sorbonne, Paris, France
| |
Collapse
|