Treatment of men with metastatic prostate cancer can be difficult due to the heterogeneity of response of lesions. [68Ga]Ga-PSMA-11 (PSMA) PET/CT assists with monitoring and directing clinical intervention; however, the impact of response heterogeneity has yet to be related to outcome measures. The aim of this study was to assess the impact of quantitative imaging information on the value of PSMA PET/CT to assess patient outcomes in response evaluation.
Baseline and follow-up (6 months) PSMA PET/CT of 162 men with oligometastatic PC treated with standard clinical care were acquired between 2015 and 2016 for analysis. An augmentative software medical device was used to track lesions between scans and quantify lesion change to categorize them as either new, increasing, stable, decreasing, or disappeared. Quantitative imaging features describing the size, intensity, extent, change, and heterogeneity of change (based on percent change in SUVtotal) among lesions were extracted and evaluated for association with overall survival (OS) using Cox regression models. Model performance was evaluated using the c-index.
Forty-one (25%) of subjects demonstrated heterogeneous response at follow-up, defined as having at least 1 new or increasing lesion and at least 1 decreasing or disappeared lesion. Subjects with heterogeneous response demonstrated significantly shorter OS than subjects without (median OS = 76.6 months vs. median OS not reached, P < .05, c-index = 0.61). In univariate analyses, SUVtotal at follow-up was most strongly associated with OS (HR = 1.29 [1.19, 1.40], P < .001, c-index = 0.73). Multivariable models applied using heterogeneity of change features demonstrated higher performance (c-index = 0.79) than models without (c-index = 0.71-0.76, P < .05).
Augmentative software tools enhance the evaluation change on serial PSMA PET scans and can facilitate lesional evaluation between timepoints. This study demonstrates that a heterogeneous response at a lesional level may impact adversely on patient outcomes and supports further investigation to evaluate the role of imaging to guide individualized patient management to improve clinical outcomes.
Clinical genitourinary cancer. 2024 Jul 06 [Epub ahead of print]
Mikaela Dell'Oro, Daniel T Huff, Ojaswita Lokre, Jake Kendrick, Rajkumar Munian Govindan, Jeremy S L Ong, Martin A Ebert, Timothy G Perk, Roslyn J Francis
Australian Centre for Quantitative Imaging, School of Medicine, The University of Western Australia, Perth, Australia. Electronic address: ., AIQ Solutions, Madison, WI., School of Physics, Mathematics and Computing, The University of Western Australia, Perth, Australia; Centre for Advanced Technologies in Cancer Research, Perth, Australia., Department of Nuclear Medicine, Fiona Stanley Hospital, Murdoch, Australia., Australian Centre for Quantitative Imaging, School of Medicine, The University of Western Australia, Perth, Australia; School of Physics, Mathematics and Computing, The University of Western Australia, Perth, Australia; Centre for Advanced Technologies in Cancer Research, Perth, Australia; Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Australia., Australian Centre for Quantitative Imaging, School of Medicine, The University of Western Australia, Perth, Australia; Department of Nuclear Medicine, Sir Charles Gairdner Hospital, Nedlands, Australia.