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Uncovering the Invisible - Prevalence, Characteristics, and Radiomics Feature-based Detection of Visually Undetectable Intraprostatic Tumor Lesions in 68GaPSMA-11 PET Images of Patients with Primary Prostate Cancer

Constantinos ZamboglouAlisa S. BettermannChristian GratzkeMichael MixJuri RufSelina KieferCordula JilgMatthias BenndorfSimon Konrad Benedict SpohnThomas Franz Stephan FaßbenderPeter BronsertMengxia ChenHongqian GuoFeng Wangxuefeng QiuAnca-Ligia Grosu

出版	Universität, 2021
URL	http://books.google.com.hk/books?id=8tOGzgEACAAJ&hl=&source=gbs_api

註釋

Abstract: Introduction
Primary prostate cancer (PCa) can be visualized on prostate-specific membrane antigen positron emission tomography (PSMA-PET) with high accuracy. However, intraprostatic lesions may be missed by visual PSMA-PET interpretation. In this work, we quantified and characterized the intraprostatic lesions which have been missed by visual PSMA-PET image interpretation. In addition, we investigated whether PSMA-PET-derived radiomics features (RFs) could detect these lesions.

Methodology
This study consists of two cohorts of primary PCa patients: a prospective training cohort (n = 20) and an external validation cohort (n = 52). All patients underwent 68Ga-PSMA-11 PET/CT and histology sections were obtained after surgery. PCa lesions missed by visual PET image interpretation were counted and their International Society of Urological Pathology score (ISUP) was obtained. Finally, 154 RFs were derived from the PET images and the discriminative power to differentiate between prostates with or without visually undetectable lesions was assessed and areas under the receiver-operating curve (ROC-AUC) as well as sensitivities/specificities were calculated.

Results
In the training cohort, visual PET image interpretation missed 134 tumor lesions in 60% (12/20) of the patients, and of these patients, 75% had clinically significant (ISUP > 1) PCa. The median diameter of the missed lesions was 2.2 mm (range: 1-6). Standard clinical parameters like the NCCN risk group were equally distributed between patients with and without visually missed lesions (p 0.05). Two RFs (local binary pattern (LBP) size-zone non-uniformality normalized and LBP small-area emphasis) were found to perform excellently in visually unknown PCa detection (Mann-Whitney U: p 0.01, ROC-AUC: ≥ 0.93). In the validation cohort, PCa was missed in 50% (26/52) of the patients and 77% of these patients possessed clinically significant PCa. The sensitivities of both RFs in the validation cohort were ≥ 0.8.br