Pillai, Jay J

We introduce tumor connectomics, a novel MRI-based complex graph theory framework that describes the intricate network of relationships within the tumor and surrounding tissue, and combine this with multiparametric radiomics (mpRad) in a machine-learning approach to distinguish radiation necrosis (RN) from true progression (TP). Pathologically confirmed cases of RN vs. TP in brain metastases treated with SRS were included from a single institution. The region of interest was manually segmented as the single largest diameter of the T1 post-contrast (T1C) lesion plus the corresponding area of T2 FLAIR hyperintensity. There were 40 mpRad features and 6 connectomics features extracted, as well as 5 clinical and treatment factors. We developed an Integrated Radiomics Informatics System (IRIS) based on an Isomap support vector machine (IsoSVM) model to distinguish TP from RN using leave-one-out cross-validation. Class imbalance was resolved with differential misclassification weighting during model training using the IRIS. In total, 135 lesions in 110 patients were analyzed, including 43 cases (31.9%) of pathologically proven RN and 92 cases (68.1%) of TP. The top-performing connectomics features were three centrality measures of degree, betweenness, and eigenvector centralities. Combining these with the 10 top-performing mpRad features, an optimized IsoSVM model was able to produce a sensitivity of 0.87, specificity of 0.84, AUC-ROC of 0.89 (95% CI: 0.82–0.94), and AUC-PR of 0.94 (95% CI: 0.87–0.97).

AbstractBackground and PurposeTo determine the incidence of acute neuroimaging (NI) findings and comorbidities in the coronavirus disease of 2019 (COVID‐19)‐infected subjects in seven U.S. and four European hospitals.MethodsThis is a retrospective study of COVID‐19‐positive subjects with the following inclusion criteria: age >18, lab‐confirmed COVID‐19 infection, and acute NI findings (NI+) attributed to COVID‐19 on CT or MRI brain. NI+ and comorbidities in total hospitalized COVID‐19‐positive (TN) subjects were assessed.ResultsA total of 37,950 COVID‐19‐positive subjects were reviewed and 4342 underwent NI. NI+ incidence in subjects with NI was 10.1% (442/4342) including 7.9% (294/3701) in the United States and 22.8% (148/647) in Europe. NI+ incidence in TN was 1.16% (442/37,950). In NI (4342), incidence of ischemic stroke was 6.4% followed by intracranial hemorrhage (ICH) (3.8%), encephalitis (0.5%), sinus venous thrombosis (0.2%), and acute disseminated encephalomyelitis (ADEM) (0.2%). White matter involvement was seen in 57% of NI+. Hypertension was the most common comorbidity (54%) before cardiac disease (28.8%) and diabetes mellitus (27.7%). Cardiac disease (p < .025), diabetes (p < .014), and chronic kidney disease (p < .012) were more common in the United States.ConclusionThis multicenter, multinational study investigated the incidence and spectrum of NI+ in 37,950 hospitalized adult COVID‐19 subjects including regional differences in incidences of NI+, associated comorbidities, and other demographics. NI+ incidence in TN was 1.16% including 0.95% in the United States and 2.09% in Europe. ICH, encephalitis, and ADEM were common in Europe, while ischemic strokes were more common in the United States. In this cohort, incidence and distribution of NI+ helped characterize the neurological complications of COVID‐19.

AbstractAccumulating evidence from recent studies has indicated the importance of studying the interaction between the microvascular and lymphatic systems in the brain. To date, most imaging methods can only measure blood or lymphatic vessels separately, such as dynamic susceptibility contrast (DSC) MRI for blood vessels and DSC MRI‐in‐the‐cerebrospinal fluid (CSF) (cDSC MRI) for lymphatic vessels. An approach that can measure both blood and lymphatic vessels in a single scan offers advantages such as a halved scan time and contrast dosage. This study attempts to develop one such approach by optimizing a dual‐echo turbo‐spin‐echo sequence, termed “dynamic dual‐spin‐echo perfusion (DDSEP) MRI”. Bloch simulations were performed to optimize the dual‐echo sequence for the measurement of gadolinium (Gd)‐induced blood and CSF signal changes using a short and a long echo time, respectively. The proposed method furnishes a T1‐dominant contrast in CSF and a T2‐dominant contrast in blood. MRI experiments were performed in healthy subjects to evaluate the dual‐echo approach by comparing it with existing separate methods. Based on simulations, the short and long echo time were chosen around the time when blood signals show maximum difference between post‐ and pre‐Gd scans, and the time when blood signals are completely suppressed, respectively. The proposed method showed consistent results in human brains as previous studies using separate methods. Signal changes from small blood vessels occurred faster than from lymphatic vessels after intravenous Gd injection. In conclusion, Gd‐induced signal changes in blood and CSF can be detected simultaneously in healthy subjects with the proposed sequence. The temporal difference in Gd‐induced signal changes from small blood and lymphatic vessels after intravenous Gd injection was confirmed using the proposed approach in the same human subjects. Results from this proof‐of‐concept study will be used to further optimize DDSEP MRI in subsequent studies.