2024 World Conference on Lung Cancer (WCLC) - ePosters-EP.06E.05 Is Diffusion-Weighted Imaging Able to Indicate Pathological Response in NSCLC after Neo-Adjuvant Immuno-Chemotherapy?

EP.06E.05 Is Diffusion-Weighted Imaging Able to Indicate Pathological Response in NSCLC after Neo-Adjuvant Immuno-Chemotherapy?

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The study conducted by the Department of Biomedical Imaging and Image-guided Therapy at the Christian Doppler Laboratory, Medical University of Vienna, aimed to determine if diffusion-weighted imaging (DWI) could effectively indicate pathological responses in non-small-cell lung cancer (NSCLC) after neo-adjuvant immuno-chemotherapy. The focus was whether DWI could differentiate between complete pathological response (cPR) and non-cPR in patients.<br /><br />The study involved a small cohort of 14 patients with NSCLC, primarily comprising adenocarcinoma cases. Each patient underwent pre-operative MRI scans to identify areas with restricted water diffusion using apparent diffusion coefficient (ADC) maps. The results aimed to evaluate whether changes in ADC values correlated with treatment responses.<br /><br />The findings showed that, of the patients assessed, six had a complete pathological response, whereas eight did not. The researchers found no significant correlation between tumor size and treatment outcomes. Moreover, while there were some trends in ADC values between cPR and non-cPR patients, neither was statistically nor clinically significant enough to serve as a reliable predictor.<br /><br />The study highlighted several limitations, including its small sample size, single-center design, and potential patient selection bias. The prospective nature of the study suggests preliminary insights, but the heterogeneity of the tumors evaluated means that simple ADC parameters might not adequately capture the complexities of tumor biology. The study concludes that ADC measurements, as currently used, do not effectively discriminate between cPR and non-cPR in NSCLC after immuno-chemotherapy. It implies that future studies may benefit from integrating AI to better understand and predict treatment responses. The authors suggest further research is needed to refine these imaging techniques or explore additional biomarkers that could improve prediction accuracy.

Asset Subtitle

Daria Kifjak

Meta Tag

Speaker Daria Kifjak

Topic Pathology and Biomarkers

Keywords

biomedical imaging

diffusion-weighted imaging

non-small-cell lung cancer

neo-adjuvant immuno-chemotherapy

apparent diffusion coefficient

complete pathological response

tumor biology

treatment response

Christian Doppler Laboratory

AI integration