ArticleEuropean journal of nuclear medicine and molecular imaging2024
Quantitative evaluation of lesion response heterogeneity for superior prognostication of clinical outcome.
Article in European journal of nuclear medicine and molecular imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- PET imaging enables direct evaluation of ferroptosis in HCC synergistically induced by anti-PD-L1 and Olaparib.Experimental & molecular medicine · 2026Article
- Artificial intelligence-enabled opportunistic identification of immune checkpoint inhibitor-related adverse events using [European journal of nuclear medicine and molecular imaging · 2025Article
- Editorial Commentary: Should "heterogeneous response" be considered as new category for assessing treatment response in patients with breast cancer?European journal of nuclear medicine and molecular imaging · 2025Article
- Clinical Meaningfulness of an Algorithm-Based Service for Analyzing Treatment Response in Patients with Metastatic Cancer Using FDG PET/CT.Journal of clinical medicine · 2024Article
- Uncertainty quantification via localized gradients for deep learning-based medical image assessments.Physics in medicine and biology · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
purposeStandardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome.
methods[
resultsMultivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001).
conclusionsQuantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.
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