Allison K. Duh

Abstract H3K27M-mutant diffuse midline gliomas (DMGs) express high levels of the disialoganglioside GD2 (ref. 1 ). Chimeric antigen receptor-modified T cells targeting GD2 (GD2-CART) eradicated DMGs in preclinical models 1 . Arm A of Phase I trial no. NCT04196413 (ref. 2 ) administered one intravenous (IV) dose of autologous GD2-CART to patients with H3K27M-mutant pontine (DIPG) or spinal DMG (sDMG) at two dose levels (DL1, 1 × 10 6 kg − 1 ; DL2, 3 × 10 6 kg −1 ) following lymphodepleting chemotherapy. Patients with clinical or imaging benefit were eligible for subsequent intracerebroventricular (ICV) intracranial infusions (10–30 × 10 6 GD2-CART). Primary objectives were manufacturing feasibility, tolerability and the identification of maximally tolerated IV dose. Secondary objectives included preliminary assessments of benefit. Thirteen patients enroled, with 11 receiving IV GD2-CART on study ( n = 3 DL1 (3 DIPG); n = 8 DL2 (6 DIPG, 2 sDMG)). GD2-CART manufacture was successful for all patients. No dose-limiting toxicities occurred on DL1, but three patients experienced dose-limiting cytokine release syndrome on DL2, establishing DL1 as the maximally tolerated IV dose. Nine patients received ICV infusions, with no dose-limiting toxicities. All patients exhibited tumour inflammation-associated neurotoxicity, safely managed with intensive monitoring and care. Four patients demonstrated major volumetric tumour reductions (52, 54, 91 and 100%), with a further three patients exhibiting smaller reductions. One patient exhibited a complete response ongoing for over 30 months since enrolment. Nine patients demonstrated neurological benefit, as measured by a protocol-directed clinical improvement score. Sequential IV, followed by ICV GD2-CART, induced tumour regressions and neurological improvements in patients with DIPG and those with sDMG.

“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. ©RSNA, 2023

H3K27M-mutant diffuse midline gliomas (DMGs) express high levels of the GD2 disialoganglioside and chimeric antigen receptor modified T-cells targeting GD2 (GD2-CART) eradicate DMGs in preclinical models. Arm A of the Phase I trial NCT04196413 administered one IV dose of autologous GD2-CART to patients with H3K27M-mutant pontine (DIPG) or spinal (sDMG) diffuse midline glioma at two dose levels (DL1=1e6/kg; DL2=3e6/kg) following lymphodepleting (LD) chemotherapy. Patients with clinical or imaging benefit were eligible for subsequent intracerebroventricular (ICV) GD2-CART infusions (10-30e6 GD2-CART). Primary objectives were manufacturing feasibility, tolerability, and identification of a maximally tolerated dose of IV GD2-CART. Secondary objectives included preliminary assessments of benefit. Thirteen patients enrolled and 11 received IV GD2-CART on study [n=3 DL1(3 DIPG); n=8 DL2(6 DIPG/2 sDMG). GD2-CART manufacturing was successful for all patients. No dose-limiting toxicities (DLTs) occurred on DL1, but three patients experienced DLT on DL2 due to grade 4 cytokine release syndrome (CRS). Nine patients received ICV infusions, which were not associated with DLTs. All patients exhibited tumor inflammation-associated neurotoxicity (TIAN). Four patients demonstrated major volumetric tumor reductions (52%, 54%, 91% and 100%). One patient exhibited a complete response ongoing for >30 months since enrollment. Eight patients demonstrated neurological benefit based upon a protocol-directed Clinical Improvement Score. Sequential IV followed by ICV GD2-CART induced tumor regressions and neurological improvements in patients with DIPG and sDMG. DL1 was established as the maximally tolerated IV GD2-CART dose. Neurotoxicity was safely managed with intensive monitoring and close adherence to a management algorithm.

Purpose: Artificial intelligence (AI) models have shown promise in predicting malignant thyroid nodules in adults; however, research on deep learning (DL) for pediatric cases is limited. We evaluated the applicability of a DL-based model for assessing thyroid nodules in children.