Dataset Information

Follow-up of Lesions with Equivocal Radiotracer Uptake on PSMA-Targeted PET in Patients with Prostate Cancer: Predictive Values of the PSMA-RADS-3A and PSMA-RADS-3B Categories.

ABSTRACT: Prostate-specific membrane antigen (PSMA)-targeted PET imaging has become commonly used in patients with prostate cancer (PCa). The PSMA reporting and data system version 1.0 (PSMA-RADS version 1.0) categorizes lesions on the basis of the likelihood of PCa involvement, with PSMA-RADS-3A (soft-tissue) and PSMA-RADS-3B (bone) lesions being indeterminate for the presence of disease. We retrospectively reviewed the imaging follow-up of such lesions to determine the rate at which they underwent changes suggestive of underlying PCa. Methods: PET/CT imaging with 18F-DCFPyL was performed in 110 patients with PCa, and lesions were categorized according to PSMA-RADS version 1.0. The study reported herein is a retrospective analysis of those patients. Fifty-six of 110 (50.9%) patients were determined to have indeterminate PSMA-RADS-3A or PSMA-RADS-3B lesions, and 22 of 56 (39.3%) patients had adequate follow-up to be included in the analysis (median follow-up time was 10 mo [range, 3-22 mo]). The SUVmax of the lesions was obtained, and the ratios of SUVmax of the lesions to SUVmean of blood pool (SUVmax-lesion/SUVmean-bloodpool) were calculated. Predetermined criteria were used to evaluate the PSMA-RADS-3A and PSMA-RADS-3B lesions on follow-up imaging to determine whether they demonstrated evidence of underlying malignancy. Results: A total of 46 lesions in 22 patients were considered indeterminate for PCa (i.e., PSMA-RADS-3A [32 lesions] or PSMA-RADS-3B [14 lesions]) and were evaluable on follow-up imaging. Twenty-seven of 46 (58.7%) lesions demonstrated changes suggesting they were true-positive for PCa. These lesions included 24 of 32 (75.0%) PSMA-RADS-3A lesions and 3 of 14 (21.4%) lesions categorized as PSMA-RADS-3B. The ranges of SUVmax and SUVmax-lesion/SUVmean-bloodpool overlapped between those lesions demonstrating changes consistent with malignancy on follow-up imaging and those lesions that remained unchanged on follow-up. The presence of additional definitive sites of PCa (PSMA-RADS-4 and PSMA-RADS-5) increases the likelihood that indeterminate lesions will manifest as true-positive on follow-up imaging. Conclusion: PSMA-RADS-3A and PSMA-RADS-3B lesions are truly indeterminate in that proportions of findings in both categories demonstrate evidence of malignancy on follow-up imaging. Overall, PSMA-RADS-3A lesions are more likely than PSMA-RADS-3B lesions to represent sites of PCa, and this information should be considered when guiding patient therapy.

SUBMITTER: Yin Y

PROVIDER: S-EPMC6448464 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Follow-up of Lesions with Equivocal Radiotracer Uptake on PSMA-Targeted PET in Patients with Prostate Cancer: Predictive Values of the PSMA-RADS-3A and PSMA-RADS-3B Categories.

Yin Yafu Y Werner Rudolf A RA Higuchi Takahiro T Lapa Constantin C Pienta Kenneth J KJ Pomper Martin G MG Gorin Michael A MA Rowe Steven P SP

Journal of nuclear medicine : official publication, Society of Nuclear Medicine 20180906 4

Prostate-specific membrane antigen (PSMA)-targeted PET imaging has become commonly used in patients with prostate cancer (PCa). The PSMA reporting and data system version 1.0 (PSMA-RADS version 1.0) categorizes lesions on the basis of the likelihood of PCa involvement, with PSMA-RADS-3A (soft-tissue) and PSMA-RADS-3B (bone) lesions being indeterminate for the presence of disease. We retrospectively reviewed the imaging follow-up of such lesions to determine the rate at which they underwent chang ...[more]

PMID: 30190303

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Project description:Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) is emerging as an important modality for imaging patients with prostate cancer (PCa). As with any imaging modality, indeterminate findings will arise. The PSMA reporting and data system (PSMA-RADS) version 1.0 codifies indeterminate soft tissue findings with the PSMA-RADS-3A moniker. We investigated the role of point-spread function (PSF) reconstructions on categorization of PSMA-RADS-3A lesions. This was a post hoc analysis of an institutional review board approved prospective trial. Around 60 min after the administration of 333 MBq (9 mCi) of PSMA-targeted 18F-DCFPyL, patients underwent PET/computed tomography (CT) acquisitions from the mid-thighs to the skull vertex. The PET data were reconstructed with and without PSF. Scans were categorized according to PSMA-RADS version 1.0, and all PSMA-RADS-3A lesions on non-PSF images were re-evaluated to determine if any could be re-categorized as PSMA-RADS-4. The maximum standardized uptake values (SUVs) of the lesions, mean SUVs of blood pool, and the ratios of those values were determined. A total of 171 PSMA-RADS-3A lesions were identified in 30 patients for whom both PSF reconstructions and cross-sectional imaging follow-up were available. A total of 13/171 (7.6%) were re-categorized as PSMA-RADS-4 lesions with PSF reconstructions. A total of 112/171 (65.5%) were found on follow-up to be true positive for PCa, with all 13 of the re-categorized lesions being true positive on follow-up. The lesions that were re-categorized trended towards having higher SUVmax-lesion and SUVmax-lesion/SUVmean-blood-pool metrics, although these relationships were not statistically significant. The use of PSF reconstructions for 18F-DCFPyL PET can allow the appropriate re-categorization of a small number of indeterminate PSMA-RADS-3A soft tissue lesions as more definitive PSMA-RADS-4 lesions. The routine use of PSF reconstructions for PSMA-targeted PET may be of value at those sites that utilize this technology.

Project description:Despite the key-role of the Prostate Imaging and Reporting and Data System (PI-RADS) in the diagnosis and characterization of prostate cancer (PCa), this system remains to be affected by several limitations, primarily associated with the interpretation of equivocal PI-RADS 3 lesions and with the debated role of Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI), which is only used to upgrade peripheral PI-RADS category 3 lesions to PI-RADS category 4 if enhancement is focal. We aimed at investigating the usefulness of radiomics for detection of PCa lesions (Gleason Score ≥ 6) in PI-RADS 3 lesions and in peripheral PI-RADS 3 upgraded to PI-RADS 4 lesions (upPI-RADS 4). Multiparametric MRI (mpMRI) data of patients who underwent prostatic mpMRI between April 2013 and September 2018 were retrospectively evaluated. Biopsy results were used as gold standard. PI-RADS 3 and PI-RADS 4 lesions were re-scored according to the PI-RADS v2.1 before and after DCE-MRI evaluation. Radiomic features were extracted from T2-weighted MRI (T2), Apparent diffusion Coefficient (ADC) map and DCE-MRI subtracted images using PyRadiomics. Feature selection was performed using Wilcoxon-ranksum test and Minimum Redundancy Maximum Relevance (mRMR). Predictive models were constructed for PCa detection in PI-RADS 3 and upPI-RADS 4 lesions using at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. 41 PI-RADS 3 and 32 upPI-RADS 4 lesions were analyzed. Among 293 radiomic features, the top selected features derived from T2 and ADC. For PI-RADS 3 stratification, second order model showed higher performances (Area Under the Receiver Operating Characteristic Curve-AUC- = 80%), while for upPI-RADS 4 stratification, first order model showed higher performances respect to superior order models (AUC = 89%). Our results support the significant role of T2 and ADC radiomic features for PCa detection in lesions scored as PI-RADS 3 and upPI-RADS 4. Radiomics models showed high diagnostic efficacy in classify PI-RADS 3 and upPI-RADS 4 lesions, outperforming PI-RADS v2.1 performance.

Project description:We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 (18)F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75 ± 1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV(max) (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV(max). We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16).

Project description:Recently, the standardized reporting and data system for prostate-specific membrane antigen (PSMA)-targeted PET imaging studies, termed PSMA-RADS version 1.0, was introduced. We aimed to determine the interobserver agreement for applying PSMA-RADS to imaging interpretation of 18F-DCFPyL (2-(3-{1-carboxy-5-[(6-18F-fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid) PET examinations in a prospective setting mimicking the typical clinical workflow at a prostate cancer referral center. Methods: Four readers (2 experienced readers (ERs, >3 y of PSMA-targeted PET interpretation experience) and 2 inexperienced readers (IRs, <1 y of experience)), who had all read the initial publication on PSMA-RADS 1.0, assessed 50 18F-DCFPyL PET/CT studies independently. Per scan, a maximum of 5 target lesions was selected by the observers, and a PSMA-RADS score for every target lesion was recorded. No specific preexisting conditions were placed on the selection of the target lesions, although PSMA-RADS 1.0 suggests that readers focus on the most avid or largest lesions. An overall scan impression based on PSMA-RADS was indicated, and interobserver agreement rates on a target lesion-based, on an organ-based, and on an overall PSMA-RADS score-based level were computed. Results: The number of target lesions identified by each observer was as follows: ER 1, 123; ER 2, 134; IR 1, 123; and IR 2, 120. Among those selected target lesions, 125 were chosen by at least 2 individual observers (all 4 readers selected the same target lesion in 58 of 125 [46.4%] instances, 3 readers in 40 of 125 [32%], and 2 observers in 27 of 125 [21.6%]). The interobserver agreement for PSMA-RADS scoring among identical target lesions was good (intraclass correlation coefficient [ICC] for 4, 3, and 2 identical target lesions, ≥0.60, respectively). For lymph nodes, an excellent interobserver agreement was derived (ICC, 0.79). The interobserver agreement for an overall scan impression based on PSMA-RADS was also excellent (ICC, 0.84), with a significant difference for ER (ICC, 0.97) vs. IR (ICC, 0.74) (P = 0.005). Conclusion: PSMA-RADS demonstrated a high concordance rate in this study, even among readers with different levels of experience. This finding suggests that PSMA-RADS can be effectively used for communication with clinicians and can be implemented in the collection of data for large prospective trials.

Dataset Information

Follow-up of Lesions with Equivocal Radiotracer Uptake on PSMA-Targeted PET in Patients with Prostate Cancer: Predictive Values of the PSMA-RADS-3A and PSMA-RADS-3B Categories.

Publications

Follow-up of Lesions with Equivocal Radiotracer Uptake on PSMA-Targeted PET in Patients with Prostate Cancer: Predictive Values of the PSMA-RADS-3A and PSMA-RADS-3B Categories.

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