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Alessandro Cagol

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4 papers

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YNICL Journal 2025 Journal Article

Fluid and White Matter Suppression contrasts MRI improves Deep Learning detection of Multiple Sclerosis Cortical Lesions

Pedro M. Gordaliza
Jannis Müller
Alessandro Cagol
Nataliia Molchanova
Francesco La Rosa
Charidimos Tsagkas
Cristina Granziera
Meritxell Bach Cuadra

PURPOSE: To investigate the efficacy of Fluid and White Matter Suppression (FLAWS) MRI sequence in improving Deep Learning (DL)-based detection and segmentation of cortical lesions in Multiple Sclerosis (MS) patients even, and to develop models that can generalize to clinical settings where only standard T1-weighted images (MPRAGE) are available. MATERIALS AND METHODS: -score for detection and DSC for segmentation accuracy. RESULTS: -score: 0.55[0.211-0.998]), demonstrating successful knowledge transfer from advanced research sequences to routine clinical sequences. CONCLUSION: Integration of FLAWS-derived contrasts and annotations significantly improves DL-based CL detection and segmentation. The models demonstrate capability in identifying lesions missed by individual raters and maintain robust performance when applied to standard clinical sequences at external sites. This cross-sequence generalization facilitates immediate clinical translation, supported by publicly available inference models on DockerHub.

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YNICL Journal 2025 Journal Article

TIME: Tractography-Informed myelin estimation

Sara Bosticardo
Matteo Battocchio
Mario Ocampo-Pineda
Alessandro Cagol
Po- Jui Lu
Esther Ruberte
Nina De Oliveira S. Siebenborn
Xinjie Chen

Investigating myelin integrity within multiple sclerosis (MS) lesions and in normal-appearing white matter is crucial for understanding demyelination and remyelination processes. While most approaches assess global myelin changes or compare lesions with homologous regions in healthy controls, they do not allow direct within-tract comparisons between lesional and non-lesional tissue. We introduce the tractography-informed myelin estimate (TIME), a novel map designed to quantify tract-specific myelin loss. TIME integrates tractography with myelin-sensitive imaging, such as myelin volume fraction, to compare lesional and non-lesional segments within the same white matter tract. By modeling local deviations from the expected myelin volume fraction signal along streamlines, TIME captures tract-specific myelin damage while accounting for within-tract variability. TIME is based on a microstructure-informed tractography framework, with an extra compartment to model signal loss caused by lesions. We evaluated TIME in 159 MS patients, assessing its association with neurological disability at baseline and longitudinally over a median follow-up of two years. At baseline, higher myelin loss captured by TIME was significantly associated with worse disability (β = 0.14, p = 0.015). Longitudinally, greater baseline disability predicted faster TIME-quantified myelin loss, which was in turn associated with a higher risk of disability worsening. In contrast, lesion-averaged myelin volume fraction showed no significant associations with either baseline disability or its progression. TIME provides a detailed, tract-specific assessment of myelin damage, providing greater sensitivity than conventional metrics, highlighting its potential as a biomarker in MS.

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YNICL Journal 2023 Journal Article

Personalized maps of T1 relaxometry abnormalities provide correlates of disability in multiple sclerosis patients

Xinjie Chen
Sabine Schädelin
Po-Jui Lu
Mario Ocampo-Pineda
Matthias Weigel
Muhamed Barakovic
Esther Ruberte
Alessandro Cagol

OBJECTIVES AND AIMS: Quantitative MRI (qMRI) has greatly improved the sensitivity and specificity of microstructural brain pathology in multiple sclerosis (MS) when compared to conventional MRI (cMRI). More than cMRI, qMRI also provides means to assess pathology within the normal-appearing and lesion tissue. In this work, we further developed a method providing personalized quantitative T1 (qT1) abnormality maps in individual MS patients by modeling the age dependence of qT1 alterations. In addition, we assessed the relationship between qT1 abnormality maps and patients' disability, in order to evaluate the potential value of this measurement in clinical practice. METHODS: We included 119 MS patients (64 relapsing-remitting MS (RRMS), 34 secondary progressive MS (SPMS), 21 primary progressive MS (PPMS)), and 98 Healthy Controls (HC). All individuals underwent 3T MRI examinations, including Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) for qT1 maps and High-Resolution 3D Fluid Attenuated Inversion Recovery (FLAIR) imaging. To calculate personalized qT1 abnormality maps, we compared qT1 in each brain voxel in MS patients to the average qT1 obtained in the same tissue (grey/white matter) and region of interest (ROI) in healthy controls, hereby providing individual voxel-based Z-score maps. The age dependence of qT1 in HC was modeled using linear polynomial regression. We computed the average qT1 Z-scores in white matter lesions (WMLs), normal-appearing white matter (NAWM), cortical grey matter lesions (GMcLs) and normal-appearing cortical grey matter (NAcGM). Lastly, a multiple linear regression (MLR) model with the backward selection including age, sex, disease duration, phenotype, lesion number, lesion volume and average Z-score (NAWM/NAcGM/WMLs/GMcLs) was used to assess the relationship between qT1 measures and clinical disability (evaluated with EDSS). RESULTS: = 0.099, β = 0.269, 97.5 % CI = 0.078 to 0.461, p = 0.007). CONCLUSIONS: We showed that personalized qT1 abnormality maps in MS patients provide measures related to clinical disability, supporting the use of those maps in clinical practice.

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YNICL Journal 2022 Journal Article

A comparative assessment of myelin-sensitive measures in multiple sclerosis patients and healthy subjects

Reza Rahmanzadeh
Matthias Weigel
Po-Jui Lu
Lester Melie-Garcia
Thanh D. Nguyen
Alessandro Cagol
Francesco La Rosa
Muhamed Barakovic

INTRODUCTION: Multiple Sclerosis (MS) is a common neurological disease primarily characterized by myelin damage in lesions and in normal - appearing white and gray matter (NAWM, NAGM). Several quantitative MRI (qMRI) methods are sensitive to myelin characteristics by measuring specific tissue biophysical properties. However, there are currently few studies assessing the relative reproducibility and sensitivity of qMRI measures to MS pathology in vivo in patients. METHODS: We performed two studies. The first study assessed of the sensitivity of qMRI measures to MS pathology: in this work, we recruited 150 MS and 100 healthy subjects, who underwent brain MRI at 3 T including quantitative T1 mapping (qT1), quantitative susceptibility mapping (QSM), magnetization transfer saturation imaging (MTsat) and myelin water imaging for myelin water fraction (MWF). The sensitivity of qMRIs to MS focal pathology (MS lesions vs peri-plaque white/gray matter (PPWM/PPGM)) was studied lesion-wise; the sensitivity to diffuse normal appearing (NA) pathology was measured using voxel-wise threshold-free cluster enhancement (TFCE) in NAWM and vertex-wise inflated cortex analysis in NAGM. Furthermore, the sensitivity of qMRI to the identification of lesion tissue was investigated using a voxel-wise logistic regression analysis to distinguish MS lesion and PP voxels. The second study assessed the reproducibility of myelin-sensitive qMRI measures in a single scanner. To evaluate the intra-session and inter-session reproducibility of qMRI measures, we have investigated 10 healthy subjects, who underwent two brain 3 T MRIs within the same day (without repositioning), and one after 1-week interval. Five region of interest (ROIs) in white and deep grey matter areas were segmented, and inter- and intra- session reproducibility was studied using the intra-class correlation coefficient (ICC). Further, we also investigated the voxel-wise reproducibility of qMRI measures in NAWM and NAGM. RESULTS: qT1 and QSM showed the highest sensitivity to distinguish MS focal WM and cortical pathology from peri-plaque WM (P < 0.0001), although QSM also showed the highest variance when applied to lesions. MWF and MTsat exhibited the highest sensitivity to NAWM pathology (P < 0.01). On the other hand, qT1 appeared to be the most sensitive measure to NAGM pathology (P < 0.01). All myelin-sensitive qMRI measures exhibited high inter/intra sessional ICCs in various WM and deep GM ROIs, in NAWM and in NAGM (ICC 0.82 ± 0.12). CONCLUSION: This work shows that the applied qT1, MWF, MTsat and QSM are highly reproducible and exhibit differential sensitivity to focal and diffuse WM and GM pathology in MS patients.

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