| Title: |
Multisequence MRI-driven assessment of PD-L1 expression in non-small cell lung cancer: a pilot study |
| Authors: |
Robustelli Test, Agnese; Bortolotto, Chandra; Thulasi Seetha, Sithin; Marrocco, Alessandra; Pairazzi, Carlotta; Messana, Gaia; Brizzi, Leonardo; Zacà, Domenico; Grimm, Robert; Brero, Francesca; Mariani, Manuel; Cabini, Raffaella Fiamma; Stella, Giulia Maria; Preda, Lorenzo; Lascialfari, Alessandro |
| Contributors: |
Foundation IRCCS Polyclinic San Matteo; INFN, NEXT_AIM project; PNRR National Centre for HPC, Big Data and Quantum Computing |
| Source: |
Biomedical Physics & Engineering Express ; volume 12, issue 1, page 015019 ; ISSN 2057-1976 |
| Publisher Information: |
IOP Publishing |
| Publication Year: |
2025 |
| Description: |
Objective. Lung cancer remains the leading cause of cancer-related mortality worldwide, with Non-Small Cell Lung Cancer (NSCLC) accounting for approximately 85% of all cases. Programmed cell Death Ligand-1 (PD-L1) is a well-established biomarker that guides immunotherapy in advanced-stage NSCLC, currently evaluated via invasive biopsy procedures. This study aims to develop and validate a non-invasive pipeline for stratifying PD-L1 expression using quantitative analysis of IVIM parameter maps—diffusion (D), pseudo-diffusion (D*), perfusion fraction (pf)—and T1-VIBE MRI acquisitions. Approach. MRI data from 43 NSCLC patients were analysed and labelled as PD-L1 positive (≥1%) or negative ( |
| Document Type: |
article in journal/newspaper |
| Language: |
unknown |
| DOI: |
10.1088/2057-1976/ae2621 |
| DOI: |
10.1088/2057-1976/ae2621/pdf |
| Availability: |
https://doi.org/10.1088/2057-1976/ae2621; https://iopscience.iop.org/article/10.1088/2057-1976/ae2621; https://iopscience.iop.org/article/10.1088/2057-1976/ae2621/pdf |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ ; https://iopscience.iop.org/info/page/text-and-data-mining |
| Accession Number: |
edsbas.84934A3E |
| Database: |
BASE |