NS-HGlio: A generalizable and repeatable HGG segmentation and volumetric measurement AI algorithm for the longitudinal MRI assessment to inform RANO in trials and clinics

BACKGROUND Accurate and repeatable measurement of high-grade glioma (HGG) enhancing (Enh.) and T2/FLAIR hyperintensity/edema (Ed.) is required for monitoring treatment response. 3D measurements can be used to inform the modified Response Assessment in Neuro-oncology criteria. We aim to develop an HGG volumetric measurement and visualization AI algorithm that is generalizable and repeatable. METHODS A single 3D-Convoluted Neural Network, NS-HGlio, to analyze HGG on MRIs using 5-fold cross validation was developed using retrospective (557 MRIs), multicentre (38 sites) and multivendor (32 scanners) dataset divided into training (70%), validation (20%), and testing (10%). Six neuroradiologists created the ground truth (GT). Additional Internal validation (IV, three institutions) using 70 MRIs, and External validation (EV, single institution) using 40 MRIs through measuring the Dice Similarity Coefficient (DSC) of Enh., Ed. ,and Enh. + Ed. (WholeLesion/WL) tumor tissue and repeatability testing on 14 subjects from the TCIA MGH-QIN-GBM dataset using volume correlations between timepoints were performed. RESULTS IV Preoperative median DSC Enh. 0.89 (SD 0.11), Ed. 0.88 (0.28), WL 0.88 (0.11). EV Preoperative median DSC Enh. 0.82 (0.09), Ed. 0.83 (0.11), WL 0.86 (0.06). IV Postoperative median DSC Enh. 0.77 (SD 0.20), Ed 0.78. (SD 0.09), WL 0.78 (SD 0.11). EV Postoperative median DSC Enh. 0.75 (0.21), Ed 0.74 (0.12), WL 0.79 (0.07). Repeatability testing; Intraclass Correlation Coefficient of 0.95 Enh. and 0.92 Ed. CONCLUSION NS-HGlio is accurate, repeatable, and generalizable. The output can be used for visualization, documentation, treatment response monitoring, radiation planning, intra-operative targeting, and estimation of Residual Tumor Volume among others

NS-HGlio: A generalizable and repeatable HGG segmentation and volumetric measurement AI algorithm for the longitudinal MRI assessment to inform RANO in trials and clinics.

BACKGROUND Accurate and repeatable measurement of high-grade glioma (HGG) enhancing (Enh.) and T2/FLAIR hyperintensity/edema (Ed.) is required for monitoring treatment response. 3D measurements can be used to inform the modified Response Assessment in Neuro-oncology criteria. We aim to develop an HGG volumetric measurement and visualization AI algorithm that is generalizable and repeatable. METHODS A single 3D-Convoluted Neural Network, NS-HGlio, to analyze HGG on MRIs using 5-fold cross validation was developed using retrospective (557 MRIs), multicentre (38 sites) and multivendor (32 scanners) dataset divided into training (70%), validation (20%), and testing (10%). Six neuroradiologists created the ground truth (GT). Additional Internal validation (IV, three institutions) using 70 MRIs, and External validation (EV, single institution) using 40 MRIs through measuring the Dice Similarity Coefficient (DSC) of Enh., Ed. ,and Enh. + Ed. (WholeLesion/WL) tumor tissue and repeatability testing on 14 subjects from the TCIA MGH-QIN-GBM dataset using volume correlations between timepoints were performed. RESULTS IV Preoperative median DSC Enh. 0.89 (SD 0.11), Ed. 0.88 (0.28), WL 0.88 (0.11). EV Preoperative median DSC Enh. 0.82 (0.09), Ed. 0.83 (0.11), WL 0.86 (0.06). IV Postoperative median DSC Enh. 0.77 (SD 0.20), Ed 0.78. (SD 0.09), WL 0.78 (SD 0.11). EV Postoperative median DSC Enh. 0.75 (0.21), Ed 0.74 (0.12), WL 0.79 (0.07). Repeatability testing; Intraclass Correlation Coefficient of 0.95 Enh. and 0.92 Ed. CONCLUSION NS-HGlio is accurate, repeatable, and generalizable. The output can be used for visualization, documentation, treatment response monitoring, radiation planning, intra-operative targeting, and estimation of Residual Tumor Volume among others

Imaging manifestations of immune-related adverse effects in checkpoint inhibitor therapies: A primer for the radiologist

Immune checkpoint inhibitors are monoclonal antibodies directed against cellular pathways on T-cells to treat different types of malignancies. This new therapy can cause immune-related adverse events that can involve almost any organ system. This article will review clinical presentations, molecular mechanisms and imaging manifestations of adverse events caused by checkpoint inhibitors and also illustrate the pseudoprogression tumor response pattern

Contrast inhomogeneity in CT angiography of the abdominal aortic aneurysm

Background If undetected, infrarenal Abdominal Aortic Aneurysm (AAA) growth can lead to rupture, a high-mortality complication. Some AAA patients exhibit inhomogeneous luminal contrast attenuation at first-pass CT angiography (CTA). This study assesses the association between this observation and aneurysm growth. Methods Sixty-seven consecutive pre-repair AAA CTAs were included in this retrospective study. The “Gravitational Gradient” (GG), defined as the ratio of the mean attenuation in a region-of-interest placed posteriorly to that in a region-of-interest placed anteriorly within the lumen of the aortic aneurysm on a single axial slice, and the maximum aneurysm diameter were measured from each CT data set. “AAA Contrast Inhomogeneity” was defined as the absolute value of the difference between the GG and 1.0. Univariate and multivariate logistic regression was used to assess the association of aneurysm growth >0.4 and >1.0 cm/year to AAA Contrast Inhomogeneity, aneurysm diameter, patient characteristics and cardiovascular co-morbidities. Results AAA Contrast Inhomogeneity was not correlated to aneurysm diameter (p=0.325). In multivariable analysis that included initial aneurysm diameter and AAA Contrast Inhomogeneity, both factors were significantly associated with rapid aneurysm growth (initial diameter: p=0.0029 and 0.011, and, AAA Contrast Inhomogeneity: p=0.045 and 0.048 for growth >0.4 cm/year and >1 cm/year respectively). Conclusions AAA Contrast Inhomogeneity is a common observation in first-pass CTA. It is associated with rapid aneurysm growth, independent of and incremental to aneurysm diameter

AAV gene therapy for Tay-Sachs disease

Tay-Sachs disease (TSD) is an inherited neurological disorder caused by deficiency of hexosaminidase A (HexA). Here, we describe an adeno-associated virus (AAV) gene therapy expanded-access trial in two patients with infantile TSD (IND 18225) with safety as the primary endpoint and no secondary endpoints. Patient TSD-001 was treated at 30 months with an equimolar mix of AAVrh8-HEXA and AAVrh8-HEXB administered intrathecally (i.t.), with 75% of the total dose (1 x 10(14) vector genomes (vg)) in the cisterna magna and 25% at the thoracolumbar junction. Patient TSD-002 was treated at 7 months by combined bilateral thalamic (1.5 x 10(12) vg per thalamus) and i.t. infusion (3.9 x 10(13) vg). Both patients were immunosuppressed. Injection procedures were well tolerated, with no vector-related adverse events (AEs) to date. Cerebrospinal fluid (CSF) HexA activity increased from baseline and remained stable in both patients. TSD-002 showed disease stabilization by 3 months after injection with ongoing myelination, a temporary deviation from the natural history of infantile TSD, but disease progression was evident at 6 months after treatment. TSD-001 remains seizure-free at 5 years of age on the same anticonvulsant therapy as before therapy. TSD-002 developed anticonvulsant-responsive seizures at 2 years of age. This study provides early safety and proof-of-concept data in humans for treatment of patients with TSD by AAV gene therapy