NNFit: A Self-Supervised Deep Learning Method for Accelerated Quantification of High- Resolution Short Echo Time MR Spectroscopy Datasets.

Purpose To develop and evaluate the performance of NNFit, a self-supervised deep-learning method for quantification of high-resolution short echo-time (TE) echo-planar spectroscopic imaging (EPSI) datasets, with the goal of addressing the computational bottleneck of conventional spectral quantification methods in the clinical workflow. Materials and Methods This retrospective study included 89 short-TE whole-brain EPSI/GRAPPA scans from clinical trials for glioblastoma (Trial 1, May 2014-October 2018) and major-depressive-disorder (Trial 2, 2022- 2023). The training dataset included 685k spectra from 20 participants (60 scans) in Trial 1.

Continuous single-ended depth-of-interaction measurement using highly multiplexed signals and artificial neural networks.

This study aims to enhance positron emission tomography (PET) imaging systems by developing a continuous depth-of-interaction (DOI) measurement technique using a single-ended readout. Our primary focus is on reducing the number of readout channels in the scintillation detectors while maintaining accurate DOI estimations, using a high-pass filter-based signal multiplexing technique combined with artificial neural networks (ANNs). Approach: Instead of reading out all 64 signals from an 8×8 silicon photomultiplier array for DOI estimation, the proposed method technique reduces the signals into just four channels by applying high-pass filters with different time constants.

Engineered GM-CSF polarizes protumorigenic tumor-associated macrophages to an antitumorigenic phenotype and potently synergizes with IL-12 immunotherapy.

Background: The use of immune checkpoint inhibitors (CPIs) has become a dominant regimen in modern cancer therapy, however immune resistance induced by tumor-associated macrophages (TAMs) with immune suppressive and evasion properties limits responses. Therefore, the rational design of immune modulators that can control the immune suppressive properties of TAMs and polarize them, as well as dendritic cells (DCs), toward a more proinflammatory phenotype is a principal objective in cancer immunotherapy.

Methods: Here, using a protein engineering approach to enhance cytokine residence in the tumor microenvironment, we examined combined stimulation of the myeloid compartment via tumor stroma-binding granulocyte-macrophage colony-stimulating factor (GM-CSF) to enhance responses in both DCs and T cells via stroma-binding interleukin-12 (IL-12).

Neoadjuvant and adjuvant osimertinib in stage IA-IIIA, EGFR-mutant non-small cell lung cancer (NORA).

Introduction: Treatment with adjuvant osimertinib for three years is the standard-of-care for resected stage IB-IIIA non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR)-mutations. The role of neoadjuvant osimertinib in the perioperative setting is yet to be elucidated in the NeoADAURA study (NCT04351555).

Methods: This is a single center, pilot study of patients with clinical stage IA-IIIA NSCLC (AJCC 8th edition) harboring an activating EGFR mutation (Exon 19 deletion, L858R) (NCT04816838).