Besides prognostic clinical factors, baseline risk assessment in personalized cancer research would benefit from quantitative disease characterization to inform therapy planning. Texture analysis of [18F]FMCH PET/CT imaging is paving the way for such purposes but its potential is still braked by radiomic feature limitation, such as redundancy and lack of standardization. In this work, we provide a method for a robust assessment of intratumor heterogeneity in patients affected by prostate cancer, through a depth-based ranking quantifying the level of centrality/outlyingness of the lesion with respect to peers. We interpret the results in terms of clinical information of lesions.

Quantitative depth-based [18F]FMCH-avid lesion profiling in prostate cancer treatment

Cavinato, Lara;Ragni, Alessandra;Ieva, Francesca;
2021

Abstract

Besides prognostic clinical factors, baseline risk assessment in personalized cancer research would benefit from quantitative disease characterization to inform therapy planning. Texture analysis of [18F]FMCH PET/CT imaging is paving the way for such purposes but its potential is still braked by radiomic feature limitation, such as redundancy and lack of standardization. In this work, we provide a method for a robust assessment of intratumor heterogeneity in patients affected by prostate cancer, through a depth-based ranking quantifying the level of centrality/outlyingness of the lesion with respect to peers. We interpret the results in terms of clinical information of lesions.
Quantitative depth-based [18F]FMCH-avid lesion profiling in prostate cancer treatment
9788891927361
Depth Measures, PET/CT medical imaging, Precision medicine, Prostate cancer, Ranking, Radiomics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1177649
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