Search

Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. Here, we introduce Histogram-based polynomial synthesis (HIPS), a fast preprocessing step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation. HIPS was incorporated into our Thalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts, scanner manufacturers, and field strength. HIPS-synthesized images improved intra-thalamic contrast and thalamic boundaries, and their segmentations yielded significantly better mean Dice, lower percentage of volume error, and lower standard deviations compared to both the CNN method and T1w-THOMAS. Finally, using THOMAS, HIPS-synthesized images were as effective as WMn images for identifying thalamic nuclei atrophy in alcohol use disorders subjects relative to healthy controls, with a higher area under the ROC curve compared to T1w-THOMAS (0.79 vs 0.73)., Comment: 5 Figures, 3 Tables, 1 Supplemental Figure, Submitted to Scientific Reports Apr 12 2023

Supplemental material, sj-docx-1-msj-10.1177_13524585221114247 for Differential vulnerability of thalamic nuclei in multiple sclerosis by Simon Blyau, Ismail Koubiyr, Manojkumar Saranathan, Pierrick Coupé, Mathilde Deloire, Julie Charré-Morin, Aurore Saubusse, Bei Zhang, Brian Rutt, Vincent Dousset, Bruno Brochet, Aurélie Ruet and Thomas Tourdias in Multiple Sclerosis Journal

These are the WMn MPRAGE datasets used to create the structural thalamic nuclei atlas (which can be found here https://zenodo.org/record/5045684). They are 9 healthy controls (ctrl1, ctrl2 etc). For the latest atlas uploaded, only these 9 healthy controls were used. The format is as follows. Each tgz file contains a WMnMPRAGE_bias_corr.nii.gz which is the bias corrected WMn MPRAGE 7T data set in NifTi format and a directory called sanitized_rois which contains the manual delineation of 11 thalamic nuclei, the mammillothalamic tract (MTT) and the whole thalamus in NifTi format. This is part of a submission to Scientific Data titled In vivo structural MRI-based atlas of human thalamic nuclei by Saranathan, Manojkumar; Iglehart, Charles; Monti, Martin; Tourdias, Thomas; Rutt, Brian. Copyright Manojkumar Saranathan 2020 Not tested or validated for clinical use

Purpose: Thalamic nuclei are largely invisible in conventional MRI due to poor contrast. Thalamus Optimized Multi-Atlas Segmentation (THOMAS) provides automatic segmentation of 12 thalamic nuclei using white-matter-nulled (WMn) MPRAGE sequence at 7T. Application of THOMAS to Magnetization Prepared 2 Rapid Gradient Echo (MP2RAGE) sequence acquired at 7T has been investigated in this study. Methods: 8 healthy volunteers and 5 pediatric-onset multiple sclerosis patients were recruited at the Children's Hospital of Philadelphia and scanned at Siemens 7T with WMn-MPRAGE and multi-echo MP2RAGE (ME-MP2RAGE) sequences. White-matter-nulled contrast was synthesized (MP2-SYN) from T1 maps from ME-MP2RAGE sequence. Thalamic nuclei were segmented using THOMAS joint label fusion algorithm from WMn-MPRAGE and MP2-SYN datasets. THOMAS pipeline was modified to use majority voting to segment the bias corrected MP2-UNI images. Thalamic nuclei from MP2-SYN and MP2-UNI images were evaluated against corresponding nuclei obtained from WMn-MPRAGE images using dice coefficients, volume similarity indices (VSI) and distance between centroids. Results: For MP2-SYN, dice > 0.85 and VSI > 0.95 was achieved for the 5 larger nuclei and dice > 0.6 and VSI > 0.7 was achieved for the 7 smaller nuclei. The dice and VSI were slightly higher whilst the distance between centroids were smaller for MP2-SYN compared to MP2-UNI, indicating improved performance using the synthesized WMn image. Discussion: THOMAS algorithm can successfully segment thalamic nuclei in routinely acquired bias-free MP2RAGE images with essentially equivalent quality when evaluated against WMn-MPRAGE, hence has wider applicability in studies focused on thalamic involvement in aging and disease., 13 pages, 4 figures

The thalamus consists of several histologically and functionally distinct nuclei increasingly implicated in brain pathology and important for treatment, motivating the need for development of fast and accurate thalamic segmentation. The contrast between thalamic nuclei as well as between the thalamus and surrounding tissues is poor in T1 and T2 weighted magnetic resonance imaging (MRI), inhibiting efforts to date to segment the thalamus using standard clinical MRI. Automatic segmentation techniques have been developed to leverage thalamic features better captured by advanced MRI methods, including magnetization prepared rapid acquisition gradient echo (MP-RAGE) , diffusion tensor imaging (DTI), and resting state functional MRI (fMRI). Despite operating on fundamentally different image features, these methods claim a high degree of agreement with the Morel stereotactic atlas of the thalamus. However, no comparison has been undertaken to compare the results of these disparate segmentation methods. We have implemented state-of-the-art structural, diffusion, and functional imaging-based thalamus segmentation techniques and used them on a single set of subjects. We present the first systematic qualitative and quantitative comparison of these methods. We found that functional connectivity-based parcellation exhibited a close correspondence with structural parcellation on the basis of qualitative concordance with the Morel thalamic atlas as well as the quantitative measures of Dice scores and volumetric similarity index., Comment: 24 pages, 9 figures, submitted to Brain Structure and Function December 2019

PurposeTo present a new method that can simultaneously and efficiently measure T1 and B1 (+) maps using reference region variable flip angle (RR-VFA) imaging.MethodsAssuming T1 relaxation time in a reference region such as fat is well characterized, and the reference region sufficiently covers smoothly varying B1 (+) field inhomogeneity, B1 (+) maps can be measured from VFA images, conventionally used for T1 measurements. Fat-only images from two-point Dixon acquisitions were used to compute B1 (+) maps, and the B1 (+) maps were compared with ones using the double-angle method (DAM) in 22 breast MRI patients at 3T. Additionally, high spatial resolution VFA images were acquired to show T1 measurements with and without the RR-VFA B1 (+) correction in six patients.ResultsRR-VFA is able to generate reliable B1 (+) maps, similar to those using the conventional DAM. This simultaneous T1 and B1 (+) mapping can also be used to reduce T1 estimation errors, where T1 maps have more uniform fibroglandular tissue T1 and better depiction of heterogeneous T1 of breast masses.ConclusionA new method that can measure both T1 and B1 (+) maps based on Dixon VFA images is described, offering improved T1 quantification with no scan time penalty.