Submillimeter T1 atlas for subject-specific abnormality detection at 7T.

PURPOSE: Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. METHODS: T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. RESULTS: The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. CONCLUSION: A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.

A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients.

BACKGROUND: Detecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarged white matter lesions (NELs) in the follow-up of MS patients; however, multicenter validation studies are lacking. PURPOSE: To assess the accuracy of LeMan-PV for the longitudinal detection NEL white-matter MS lesions in a multicenter clinical setting. STUDY TYPE: Retrospective, longitudinal. SUBJECTS: A total of 206 patients with a definitive MS diagnosis and at least two follow-up MRI studies from five centers participating in the Swiss Multiple Sclerosis Cohort study. Mean age at first follow-up = 45.2 years (range: 36.9-52.8 years); 70 males. FIELD STRENGTH/SEQUENCE: Fluid attenuated inversion recovery (FLAIR) and T1-weighted magnetization prepared rapid gradient echo (T1-MPRAGE) sequences at 1.5 T and 3 T. ASSESSMENT: The study included 313 MRI pairs of datasets. Data were analyzed with LeMan-PV and compared with a manual "reference standard" provided by a neuroradiologist. A second rater (neurologist) performed the same analysis in a subset of MRI pairs to evaluate the rating-accuracy. The Sensitivity (Se), Specificity (Sp), Accuracy (Acc), F1-score, lesion-wise False-Positive-Rate (aFPR), and other measures were used to assess LeMan-PV performance for the detection of NEL at 1.5 T and 3 T. The performance was also evaluated in the subgroup of 123 MRI pairs at 3 T. STATISTICAL TESTS: Intraclass correlation coefficient (ICC) and Cohen's kappa (CK) were used to evaluate the agreement between readers. RESULTS: The interreader agreement was high for detecting new lesions (ICC = 0.97, Pvalue < 10-20 , CK = 0.82, P value = 0) and good (ICC = 0.75, P value < 10-12 , CK = 0.68, P value = 0) for detecting enlarged lesions. Across all centers, scanner field strengths (1.5 T, 3 T), and for NEL, LeMan-PV achieved: Acc = 61%, Se = 65%, Sp = 60%, F1-score = 0.44, aFPR = 1.31. When both follow-ups were acquired at 3 T, LeMan-PV accuracy was higher (Acc = 66%, Se = 66%, Sp = 66%, F1-score = 0.28, aFPR = 3.03). DATA CONCLUSION: In this multicenter study using clinical data settings acquired at 1.5 T and 3 T, and variations in MRI protocols, LeMan-PV showed similar sensitivity in detecting NEL with respect to other recent 3 T multicentric studies based on neural networks. While LeMan-PV performance is not optimal, its main advantage is that it provides automated clinical decision support integrated into the radiological-routine flow. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Automated MRI-based volumetry of basal ganglia and thalamus at the chronic phase of cortical stroke.

PURPOSE: We aimed at assessing the potential of automated MR morphometry to assess individual basal ganglia and thalamus volumetric changes at the chronic phase after cortical stroke. METHODS: Ninety-six patients (mean age: 65 ± 18 years, male 55) with cortical stroke at the chronic phase were retrospectively included. Patients were scanned at 1.5 T or 3 T using a T1-MPRAGE sequence. Resulting 3D images were processed with the MorphoBox prototype software to automatically segment basal ganglia and thalamus structures, and to obtain Z scores considering the confounding effects of age and sex. Stroke volume was estimated by manual delineation on T2-SE imaging. Z scores were compared between ipsi- and contralateral stroke side and according to the vascular territory. Potential relationship between Z scores and stroke volume was assessed using the Spearman correlation coefficient. RESULTS: Basal ganglia and thalamus volume Z scores were lower ipsilaterally to MCA territory stroke (p values < 0.034) while they were not different between ipsi- and contralateral stroke sides in non-MCA territory stroke (p values > 0.37). In MCA territory stroke, ipsilateral caudate nucleus (rho = - 0.34, p = 0.007), putamen (rho = - 0.50, p < 0.001), pallidum (rho = - 0.44, p < 0.001), and thalamus (rho = - 0.48, p < 0.001) volume Z scores negatively correlated with the cortical stroke volume. This relation was not influenced by cardiovascular risk factors or time since stroke. CONCLUSION: Automated MR morphometry demonstrated atrophy of ipsilateral basal ganglia and thalamus at the chronic phase after cortical stroke in the MCA territory. The atrophy was related to stroke volume. These results confirm the potential role for automated MRI morphometry to assess remote changes after stroke.

Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis.

BACKGROUND AND OBJECTIVES: In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes. METHODS: We analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue. RESULTS AND CONCLUSIONS: Stable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions.

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study.

BACKGROUND: Small-vessel disease (SVD) plays a crucial role in cardiac and brain ischemia, but little is known about potential interrelation between both. We retrospectively evaluated 370 patients, aiming at assessing the interrelation between cardiac and brain SVD by using quantitative 82Rb cardiac PET/CT and brain MRI. RESULTS: In our population of 370 patients, 176 had normal myocardial perfusion, 38 had pure cardiac SVD and 156 had obstructive coronary artery disease. All underwent both a cardiac 82Rb PET/CT and a brain 1.5T or 3T MRI. Left-ventricle myocardial blood flow (LV-MBF) and flow reserve (LV-MFR) were recorded from 82Rb PET/CT, while Fazekas score, white matter lesion (WMab) volume, deep gray matter lesion (GMab) volume, and brain morphometry (for z-score calculation) using the MorphoBox research application were derived from MRI. Groups were compared with Kruskal-Wallis test, and the potential interrelation between heart and brain SVD markers was assessed using Pearson's correlation coefficient. Patients with cardiac SVD had lower stress LV-MBF and MFR (P < 0.001) than patients with normal myocardial perfusion; Fazekas scores and WMab volumes were similar in those two groups (P > 0.45). In patients with cardiac SVD only, higher rest LV-MBF was associated with a lower left-putamen (rho = - 0.62, P = 0.033), right-thalamus (rho = 0.64, P = 0.026), and right-pallidum (rho = 0.60, P = 0.039) z-scores and with a higher GMab volume. Lower stress LV-MBF was associated with lower left-caudate z-score (rho = 0.69, P = 0.014), while lower LV-MFR was associated with lower left (rho = 0.75, P = 0.005)- and right (rho = 0.59, P = 0.045)-putamen z-scores, as well as higher right-thalamus GMab volume (rho = - 0.72, P = 0.009). CONCLUSION: Significant interrelations between cardiac and cerebral SVD markers were found, especially regarding deep gray matter alterations, which supports the hypothesis of SVD as a systemic disease.

Cerebral Metabolic Dysfunction at the Acute Phase of Traumatic Brain Injury Correlates with Long-Term Tissue Loss.

Following traumatic brain injury (TBI), cerebral metabolic dysfunction, characterized by an elevated cerebral microdialysis (CMD) lactate/pyruvate (LP) ratio, is associated with poor outcome. However, the exact pathophysiological mechanisms underlying this association are not entirely established. In this pre-planned analysis of the BIOmarkers of AXonal injury after Traumatic Brain Injury (BIO-AX-TBI) prospective study, we investigated any associations of LP ratio with brain structure volume change rates at 1 year. Fourteen subjects underwent acute-phase (0-96 h post-TBI) CMD monitoring and had longitudinal magnetic resonance imaging (MRI) quantification of brain volume loss between the subacute phase (14 days to 6 weeks) and 1 year after TBI, recalculated as an annual rate. On average, CMD showed an elevated (>25) LP ratio (31 [interquartile range (IQR) 24-34]), indicating acute cerebral metabolic dysfunction. Annualized whole brain and total gray matter (GM) volume change rates were abnormally reduced (-3.2% [-9.3 to -2.2] and -1.9% [-4.4 to 1.7], respectively). Reduced annualized total GM volume correlated significantly with elevated CMD LP ratio (Spearman's ρ = -0.68, p-value = 0.01) and low CMD glucose (ρ = 0.66, p-value = 0.01). After adjusting for age, admission Glasgow Coma Scale (GCS) score and CT Marshall score, CMD LP ratio remained strongly associated with 1-year total GM volume change rate (p < 0.001; multi-variable analysis). No relationship was found between WM volume changes and CMD metabolites. We demonstrate a strong association between acute post-traumatic cerebral metabolic dysfunction and 1-year gray matter atrophy, reinforcing the role of CMD LP ratio as an early biomarker of poor long-term recovery after TBI.

Serum GFAP in multiple sclerosis: correlation with disease type and MRI markers of disease severity.

Neurofilament light chain (NfL) has been demonstrated to correlate with multiple sclerosis disease severity as well as treatment response. Nevertheless, additional serum biomarkers are still needed to better differentiate disease activity from disease progression. The aim of our study was to assess serum glial fibrillary acid protein (s-GFAP) and neurofilament light chain (s-NfL) in a cohort of 129 multiple sclerosis (MS) patients. Eighteen primary progressive multiple sclerosis (PPMS) and 111 relapsing remitting MS (RRMS) were included. We showed that these 2 biomarkers were significantly correlated with each other (R = 0.72, p < 0.001). Moreover, both biomarkers were higher in PPMS than in RRMS even if multivariate analysis only confirmed this difference for s-GFAP (130.3 ± 72.8 pg/ml vs 83.4 ± 41.1 pg/ml, p = 0.008). Finally, s-GFAP was correlated with white matter lesion load and inversely correlated with WM and GM volume. Our results seem to confirm the added value of s-GFAP in the context of multiple sclerosis.

Multilevel segmentation of intracranial aneurysms in CT angiography images.

PURPOSE: Segmentation of aneurysms plays an important role in interventional planning. Yet, the segmentation of both the lumen and the thrombus of an intracranial aneurysm in computed tomography angiography (CTA) remains a challenge. This paper proposes a multilevel segmentation methodology for efficiently segmenting intracranial aneurysms in CTA images. METHODS: The proposed methodology first uses the lattice Boltzmann method (LBM) to extract the lumen part directly from the original image. Then, the LBM is applied again on an intermediate image whose lumen part is filled by the mean gray-level value outside the lumen, to yield an image region containing part of the aneurysm boundary. After that, an expanding disk is introduced to estimate the complete contour of the aneurysm. Finally, the contour detected is used as the initial contour of the level set with ellipse to refine the aneurysm. RESULTS: The results obtained on 11 patients from different hospitals showed that the proposed segmentation was comparable with manual segmentation, and that quantitatively, the average segmentation matching factor (SMF) reached 86.99%, demonstrating good segmentation accuracy. Chan-Vese method, Sen's model, and Luca's model were used to compare the proposed method and their average SMF values were 39.98%, 40.76%, and 77.11%, respectively. CONCLUSIONS: The authors have presented a multilevel segmentation method based on the LBM and level set with ellipse for accurate segmentation of intracranial aneurysms. Compared to three existing methods, for all eleven patients, the proposed method can successfully segment the lumen with the highest SMF values for nine patients and second highest SMF values for the two. It also segments the entire aneurysm with the highest SMF values for ten patients and second highest SMF value for the one. This makes it potential for clinical assessment of the volume and aspect ratio of the intracranial aneurysms.

Determination of a shear rate threshold for thrombus formation in intracranial aneurysms.

BACKGROUND: Particular intra-aneurysmal blood flow conditions, created naturally by the growth of an aneurysm or induced artificially by implantation of a flow diverter stent (FDS), can potentiate intra-aneurysmal thrombosis. The aim of this study was to identify hemodynamic indicators, relevant to this process, which could be used as a prediction of the success of a preventive endovascular treatment. METHOD: A cross sectional study on 21 patients was carried out to investigate the possible association between intra-aneurysmal spontaneous thrombus volume and the dome to neck aspect ratio (AR) of the aneurysm. The mechanistic link between these two parameters was further investigated through a Fourier analysis of the intra-aneurysmal shear rate (SR) obtained by computational fluid dynamics (CFD). This analysis was first applied to 10 additional patients (4 with and 6 without spontaneous thrombosis) and later to 3 patients whose intracranial aneurysms only thrombosed after FDS implantation. RESULTS: The cross sectional study revealed an association between intra-aneurysmal spontaneous thrombus volume and the AR of the aneurysm (R(2)=0.67, p<0.001). Fourier analysis revealed that in cases where thrombosis occurred, the SR harmonics 0, 1, and 2 were always less than 25/s, 10/s, and 5/s, respectively, and always greater than these values where spontaneous thrombosis was not observed. CONCLUSIONS: Our study suggests the existence of an SR threshold below which thrombosis will occur. Therefore, by analyzing the SR on patient specific data with CFD techniques, it may be potentially possible to predict whether or the intra-aneurysmal flow conditions, after FDS implantation, will become prothrombotic.

Creatools: una plataforma para el desarrollo de software de procesamiento de imágenes médicas. Aplicación a la segmentación de arterias coronarias y a la detección automática de lesiones en imágenes de angiotac / Creatools: a framework for the development of medical image processing software. Application for the segmentation of coronary arteries and for the automatic detection of lesions in CT images

En este artículo se presenta un software de código abierto, llamado CreaTools, cuyo principal objetivo es el procesar y facilitar la visualización de imágenes médicas. Este software flexible funciona en diferentes sistemas operativos (Linux, Mac OS X, Windows), se desarrolla en el lenguaje de programación C++ para asegurar una fácil integración de módulos C++ y proporciona a los usuarios herramientas computacionales para construir interfaces gráficas de usuario (GUI), incluidos los datos de entrada/salida (manejo de archivos), la visualización, la interacción y el procesamiento de datos. Este artículo muestra también la utilidad de CreaTools mediante un proyecto de investigación que consiste en la detección automática de lesiones arteriales. Los algoritmos desarrollados han sido implementados en una interfaz gráfica amigable con visualización 3D e interacción. Ejemplos de tales algoritmos incluyen la extracción de ejes de arterias y la generación de modelos descriptivos de arterias con lesiones y sin lesiones.