Lobar quantification of pulmonary perfusion prior to minimally invasive lung reduction improves prediction of postprocedure outcomes: A pilot study. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Endobronchial valve placement is a minimally invasive option for treatment of patients with severe emphysema, by reducing lung volumes in lobes with both poor ventilation and perfusion; ventilation is determined by emphysematous scores and perfusion by quantitative lung perfusion imaging. CT-based fissure identifying artificial intelligence algorithms have recently demonstrated enhanced quantification of the perfusion in a 5-lobar analysis. We hypothesized that this newly developed algorithm may offer greater utility in determining target treatment lobes by supplementing the radiographic risk stratification initiated by the conventional emphysematous scores alone. METHODS: Quantification images of 43 deidentified individuals underwent perfusion SPECT/CT with Tc99m Macro-Aggregated Albumin (4mCi/148MBq intravenous) using both conventional zonal anatomy and AI augmented 5-lobar analysis. ANALYSIS: Images were reviewed to demonstrate that the new algorithm was not inferior to standard of care imaging with zonal segmentation. A pilot subcohort analysis of 4 patients with severe emphysema who had pre-endobronchial valve placement imaging demonstrated that an emphysema-perfusion ratio greater than 3 was indicative of a potential target lobe. DISCUSSION: We conclude that 5-lobar analysis in not inferior to conventional zonal analysis and allows the determination of emphysema-to-perfusion ratio. Preliminary review of a small subcohort suggests an emphysema-to-perfusion ratio greater than 3 for a lobe may clinically benefit in endobronchial valve placement. Further evaluation with prospective studies and larger sample sizes are recommended before clinical implementation.

publication date

  • July 12, 2023

Research

keywords

  • Emphysema
  • Pulmonary Emphysema

Identity

Scopus Document Identifier

  • 85165160347

Digital Object Identifier (DOI)

  • 10.1111/cpf.12847

PubMed ID

  • 37421336

Additional Document Info

volume

  • 44

issue

  • 1