Medicine and Health Sciences Commons^™

Clinical And Dosimetric Impact Of 2d Kv Motion Monitoring And Intervention In Liver Stereotactic Body Radiation Therapy., Andrew Santoso, Yevgeniy Vinogradskiy, Tyler Robin, Karyn Goodman, Tracey Schefter, Moyed Miften, Bernard Jones

Department of Radiation Oncology Faculty Papers

PURPOSE: Positional errors resulting from motion are a principal challenge across all disease sites in radiation therapy. This is particularly pertinent when treating lesions in the liver with stereotactic body radiation therapy (SBRT). To achieve dose escalation and margin reduction for liver SBRT, kV real-time imaging interventions may serve as a potential solution. In this study, we report results of a retrospective cohort of liver patients treated using real-time 2D kV-image guidance SBRT with emphasis on the impact of (1) clinical workflow, (2) treatment accuracy, and (3) tumor dose.

METHODS AND MATERIALS: Data from 33 patients treated with 41 courses …

A Multidimensional Connectomics- And Radiomics-Based Advanced Machine-Learning Framework To Distinguish Radiation Necrosis From True Progression In Brain Metastases, Yilin Cao, Vishwa S Parekh, Emerson Lee, Xuguang Chen, Kristin J Redmond, Jay J Pillai, Luke Peng, Michael A Jacobs, Lawrence R Kleinberg

Journal Articles

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 …

Pitfalls In Machine Learning-Based Assessment Of Tumor-Infiltrating Lymphocytes In Breast Cancer: A Report Of The International Immuno-Oncology Biomarker Working Group On Breast Cancer, Jeppe Thagaard, Glenn Broeckx, Chowdhury Arif Jahangir, Sara Verbandt, Rajarsi Gupta, Reena Khiroya, Khalid Abduljabbar, Gabriela Acosta Haab, Balazs Acs, Shahin Sayed

Pathology, East Africa

Abstract: The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL …

Predicting Survival Of Nsclc Patients Treated With Immune Checkpoint Inhibitors: Impact And Timing Of Immune-Related Adverse Events And Prior Tyrosine Kinase Inhibitor Therapy, Michael R. Sayer, Isa Mambetsariev, Kun-Han Lu, Chi Wah Wong, Ashley Duche, Richard Beuttler, Jeremy Fricke, Rebecca Pharaon, Leonidas Arvanitis, Zahra Eftekhari, Arya Amini, Marianna Koczywas, Erminia Massarelli, Moom Rahman Roosan, Ravi Salgia

Pharmacy Faculty Articles and Research

Introduction: Immune checkpoint inhibitors (ICIs) produce a broad spectrum of immune-related adverse events (irAEs) affecting various organ systems. While ICIs are established as a therapeutic option in non-small cell lung cancer (NSCLC) treatment, most patients receiving ICI relapse. Additionally, the role of ICIs on survival in patients receiving prior targeted tyrosine kinase inhibitor (TKI) therapy has not been well-defined.

Objective: To investigate the impact of irAEs, the relative time of occurrence, and prior TKI therapy to predict clinical outcomes in NSCLC patients treated with ICIs.

Methods: A single center retrospective cohort study identified 354 adult patients with NSCLC receiving ICI …