Howard, Matthew A

Abstract Glioblastoma (GBM), isocitrate dehydrogenase wild-type (IDHwt) and central nervous system diffuse large B-cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. Deep learning on T1 postcontrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study design was utilized. Model development was performed on 146 patients with CNS-DLBCL and 146 age-matched, sex-matched, and MRI year–matched patients with GBM diagnosed at Mayo Clinic between 1998 and 2019. Models were tested on independent temporal test cohorts. Initial testing included 240 independent GBM diagnosed at Mayo Clinic between 1998 and 2019. The prospective test cohort included 37 patients with CNS-DLBCL and 256 patients with GBM diagnosed at Mayo Clinic after January 1, 2020, and 36 patients with CNS-DLBCL diagnosed at an external institution. Of the patients diagnosed at Mayo Clinic, 47% had MRIs generated from non-Mayo institutions. Two different model approaches were compared: (i) ensemble approach using area under the receiver operating characteristic curve (AUC) and cross-validation for model selection and (ii) loss approach minimizing cross-entropy loss and cross-validation to evaluate prediction performance. The AUCs on the prospective test cohort were 0.84 [95% confidence interval (CI), 0.78–0.90] and 0.83 (95% CI, 0.77–0.88) for the ensemble and loss approaches, respectively. Stability of ensemble prediction improved with the increasing number of models. Stratified AUC analysis demonstrated consistent performance across sex and age. We utilized a robust temporal study design and applied 2 different analytic approaches to develop a classification model. The findings confirm the feasibility of using MRI-based deep learning models to differentiate GBM from CNS-DLBCL. Significance: GBM, IDHwt and CNS-DLBCL are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. We developed MRI-based deep learning models to differentiate GBM, IDHwt from CNS-DLBCL using a rigorous three-stage temporal design that included prospective validation. The model AUC on a prospective cohort was 0.84.

Abstract Purpose: Pharmacologic ascorbate (P-AscH−) is hypothesized to be an iron (Fe)-dependent tumor-specific adjuvant to chemoradiation in treating glioblastoma (GBM). This study determined the efficacy of combining P-AscH− with radiation and temozolomide in a phase II clinical trial while simultaneously investigating a mechanism-based, noninvasive biomarker in T2* mapping to predict GBM response to P-AscH− in humans. Patients and Methods: The single-arm phase II clinical trial (NCT02344355) enrolled 55 subjects, with analysis performed 12 months following the completion of treatment. Overall survival (OS) and progression-free survival (PFS) were estimated with the Kaplan–Meier method and compared across patient subgroups with log-rank tests. Forty-nine of 55 subjects were evaluated using T2*-based MRI to assess its utility as an Fe-dependent biomarker. Results: Median OS was estimated to be 19.6 months [90% confidence interval (CI), 15.7–26.5 months], a statistically significant increase compared with historic control patients (14.6 months). Subjects with initial T2* relaxation < 50 ms were associated with a significant increase in PFS compared with T2*-high subjects (11.2 months vs. 5.7 months, P < 0.05) and a trend toward increased OS (26.5 months vs. 17.5 months). These results were validated in preclinical in vitro and in vivo model systems. Conclusions: P-AscH− combined with temozolomide and radiotherapy has the potential to significantly enhance GBM survival. T2*-based MRI assessment of tumor iron content is a prognostic biomarker for GBM clinical outcomes. See related commentary by Nabavizadeh and Bagley, p. 255

Background The authors explored the relationship between nitrous oxide use and neurologic and neuropsychological outcome in a population of patients likely to experience intraoperative cerebral ischemia: those who had temporary cerebral arterial occlusion during aneurysm clipping surgery. Methods A post hoc analysis of a subset of the data from the Intraoperative Hypothermia for Aneurysm Surgery Trial was conducted. Only subjects who had temporary arterial occlusion during surgery were included in the analysis. Metrics of short-term and long-term (i.e., 3 months after surgery) outcome were evaluated via both univariate and multivariate logistic regression analysis. An odds ratio (OR) greater than 1.0 denotes a worse outcome in patients receiving nitrous oxide. Results The authors evaluated 441 patients, of which 199 received nitrous oxide. Patients receiving nitrous oxide had a greater risk of delayed ischemic neurologic deficits (i.e., the clinical manifestation of vasospasm) (OR, 1.78, 95% confidence interval [CI], 1.08-2.95; P = 0.025). However, at 3 months after surgery, there was no difference in any metric of gross neurologic outcome: Glasgow Outcome Score (OR, 0.67; CI, 0.44-1.03; P = 0.065), Rankin Score (OR, 0.74; CI, 0.47-1.16; P = 0.192), National Institutes of Health Stroke Scale (OR, 1.02; CI, 0.66-1.56; P = 0.937), or Barthel Index (OR, 0.69; CI, 0.38-1.25; P = 0.22). The risk of impairment on at least one test of neuropsychological function was reduced in those who received nitrous oxide (OR, 0.56; CI, 0.36-0.89; P = 0.013). Conclusion In this patient population, use of nitrous oxide was associated with an increased risk for the development of delayed ischemic neurologic deficits; however, there was no evidence of detriment to long-term gross neurologic or neuropsychological outcome.