Whether multiparametric MRI improves the detection of clinically significant prostate cancer and avoids the need for systematic biopsy in biopsy-naive patients remains controversial. We aimed to ...investigate whether using this approach before biopsy would improve detection of clinically significant prostate cancer in biopsy-naive patients.
In this prospective, multicentre, paired diagnostic study, done at 16 centres in France, we enrolled patients aged 18–75 years with prostate-specific antigen concentrations of 20 ng/mL or less, and with stage T2c or lower prostate cancer. Eligible patients had been referred for prostate multiparametric MRI before a first set of prostate biopsies, with a planned interval of less than 3 months between MRI and biopsies. An operator masked to multiparametric MRI results did a systematic biopsy by obtaining 12 systematic cores and up to two cores targeting hypoechoic lesions. In the same patient, another operator targeted up to two lesions seen on MRI with a Likert score of 3 or higher (three cores per lesion) using targeted biopsy based on multiparametric MRI findings. Patients with negative multiparametric MRI (Likert score ≤2) had systematic biopsy only. The primary outcome was the detection of clinically significant prostate cancer of International Society of Urological Pathology grade group 2 or higher (csPCa-A), analysed in all patients who received both systematic and targeted biopsies and whose results from both were available for pathological central review, including patients who had protocol deviations. This study is registered with ClinicalTrials.gov, number NCT02485379, and is closed to new participants.
Between July 15, 2015, and Aug 11, 2016, we enrolled 275 patients. 24 (9%) were excluded from the analysis. 53 (21%) of 251 analysed patients had negative (Likert ≤2) multiparametric MRI. csPCa-A was detected in 94 (37%) of 251 patients. 13 (14%) of these 94 patients were diagnosed by systematic biopsy only, 19 (20%) by targeted biopsy only, and 62 (66%) by both techniques. Detection of csPCa-A by systematic biopsy (29·9%, 95% CI 24·3–36·0) and targeted biopsy (32·3%, 26·5–38·4) did not differ significantly (p=0·38). csPCa-A would have been missed in 5·2% (95% CI 2·8–8·7) of patients had systematic biopsy not been done, and in 7·6% (4·6–11·6) of patients had targeted biopsy not been done. Four grade 3 post-biopsy adverse events were reported (3 cases of prostatitis, and 1 case of urinary retention with haematuria).
There was no difference between systematic biopsy and targeted biopsy in the detection of ISUP grade group 2 or higher prostate cancer; however, this detection was improved by combining both techniques and both techniques showed substantial added value. Thus, obtaining a multiparametric MRI before biopsy in biopsy-naive patients can improve the detection of clinically significant prostate cancer but does not seem to avoid the need for systematic biopsy.
French National Cancer Institute.
Despite the significant advances in the management of advanced prostate cancer (PCa), metastatic PCa is currently considered incurable. For further investigations in precision treatment, the ...development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.
Fresh tumor samples along with normal corresponding tissues were obtained directly from patients at surgery. To ensure that the established models reproduce the main features of patient's tumor, both PDX tumors at multiple passages and patient's primary tumors, were processed for histological characteristics. STR profile analyses were also performed to confirm patient identity. Finally, the responses of the PDX models to androgen deprivation, PARP inhibitors and chemotherapy were also evaluated.
In this study, we described the development and characterization of 5 new PDX models of PCa. Within this collection, hormone-naïve, androgen-sensitive and castration-resistant (CRPC) primary tumors as well as prostate carcinoma with neuroendocrine differentiation (CRPC-NE) were represented. Interestingly, the comprehensive genomic characterization of the models identified recurrent cancer driver alterations in androgen signaling, DNA repair and PI3K, among others. Results were supported by expression patterns highlighting new potential targets among gene drivers and the metabolic pathway. In addition,
results showed heterogeneity of response to androgen deprivation and chemotherapy, like the responses of patients to these treatments. Importantly, the neuroendocrine model has been shown to be responsive to PARP inhibitor.
We have developed a biobank of 5 PDX models from hormone-naïve, androgen-sensitive to CRPC primary tumors and CRPC-NE. Increased copy-number alterations and accumulation of mutations within cancer driver genes as well as the metabolism shift are consistent with the increased resistance mechanisms to treatment. The pharmacological characterization suggested that the CRPC-NE could benefit from the PARP inhibitor treatment. Given the difficulties in developing such models, this relevant panel of PDX models of PCa will provide the scientific community with an additional resource for the further development of PDAC research.
Objectives To determine the diagnostic performance of dynamic contrast-enhanced–magnetic resonance imaging (DCE-MRI) in the identification of intraprostatic cancer foci related to cancer volume at ...histopathology, in patients with clinically localized cancer treated by radical prostatectomy, with whole-mount histopathologic sections as the reference standard. Methods Eighty-three consecutive radical prostatectomy specimens from patients referred for a prostate-specific antigen elevation were correlated with prebiopsy MRI. MRI results ranked on a 5-point scale were correlated with the findings of histopathology maps in 8 prostate sectors, including volume, largest surface area, and percentage of Gleason grade 4/5. The area under the receiver operating characteristic curve was used. Results Median prostate-specific antigen was 8.15 ng/mL. DCE-MRI was suspicious in 55 (66%) out of 83 patients. A separate cancer foci (mean 2.55 per patient) was present in 212 (34%) of 664 octants and DCE-MRI was suspicious in 68 of 212. Sensitivity and specificity of DCE-MRI at score 3.4 or 5 for identification of cancer foci at any volume was 32% and 95%, respectively. For identification of cancer foci > 0.5 mL, the sensitivity and specificity were 86% and 94%, respectively, with the under the receiver operating characteristic curve of 0.874. Mean volume of DCE-MRI detected and missed cancers were 2.44 mL (0.02-14.5) and 0.16 mL (0.005-2.4), respectively. Sensitivity and specificity of DCE-MRI for identification of > 10% of Gleason grade 4/5 were 81% and 82%, respectively. Conclusions DCE-MRI can accurately identify intraprostatic cancer foci. Possible applications are guidance for biopsies, selection of patients for watchful waiting, and focal treatment planning.
Lymph node metastasis is an important prognostic factor in prostate cancer (PC). The aim of this prospective study was to validate, through laparoscopic surgery, the accuracy of the isotopic sentinel ...lymph node (SLN) technique correlated with hyperextensive pelvic resection (extended pelvic lymphadenectomy dissection) in patients with localized PC, candidates for local curative treatment.
A transrectal ultrasound-guided injection of (99m)Tc-sulfur rhenium colloid (0.3 mL/100 MBq) in each prostatic lobe was performed the day before surgery. Detection was performed intraoperatively with a laparoscopic probe, followed by extensive resection. SLN counts were performed in vivo and confirmed ex vivo. Histologic analysis was performed by hematoxylin-phloxine-safran staining, followed by immunohistochemistry if the SLN was free of metastasis.
Two hundred three patients with PC at intermediate or high risk of lymph node metastases were included. The intraoperative detection rate was 96% (195/203). Thirty-five patients had lymph node metastases, 19 only in the SLN. The false-negative rate was 8.5% (3/35). Unilateral surgical SLN detection did not validate bilateral pelvic lymph node status, and extended pelvic lymphadenectomy dissection was necessary on the opposite side of detection to minimize the false-negative rate (2.8% 1/35). A significant metastatic sentinel invasion in the common iliac region existed (9.3%) but was always associated with other metastatic node areas. The internal iliac region was the primary metastatic site (40.7%). Finally, this series invalidated any justification for a standard or limited dissection, which would have missed 51.9% and 74.1% of lymph node metastases, respectively.
The radioisotope SLN identification method up to the common iliac region is successful to identify sentinel nodes during laparoscopic surgery per hemipelvis to be acceptably considered as an isolated procedure and should be validated for intermediate- and high-risk patients.
Aim
In intermediate- or high-risk prostate cancer (PC) patients, to avoid extended pelvic lymph node dissection (ePLND), the updated Briganti nomogram is recommended with the cost of missing 1.5 % of ...patients with lymph node invasion (LNI). Is it possible to reduce the percentage of unexpected LNI patients (nomogram false negative)? We used the isotopic sentinel lymph node (SLN) technique systematically associated with laparoscopic ePLND to assess the potential value of isotopic SLN method to adress this point.
Methods
Two hundred and two consecutive patients had procedures with isotopic SLN detection associated with laparoscopic ePLND for high or intermediate risk of PC. The area under the curve (AUC) of the receiver operating characteristics (ROC) analysis was used to quantify the accuracy of different models as: the updated Briganti nomogram, the percentage of positive cores, and an equation of the best predictors of LNI. We tested the model cutoffs associated with an optimal negative predictive value (NPV) and the best cutoff associated with avoiding false negative SLN detection, in order to assist the clinician’s decision of when to spare ePLND.
Results
LNI was detected in 35 patients (17.2 %). Based on preoperative primary Gleason grade and percentage of positive cores, a bivariate model was built to calculate a combined score reflecting the risk of LNI. For the Briganti nomogram, the 5 % probability cutoff avoided ePLND in 53 % (108/202) of patients, missing three LNI patients (8.6 %), but all were detected by the SLN technique. For our bivariate model, the best cutoff was <10, leaving no patient with LNI due to positive SLN detection (four patients = 11.4 %), and avoiding ePLND in 52 % (105/202) of patients.
Conclusion
For patients with a low risk of LNI determined using the updated Briganti nomogram or bivariate model, SLN technique could be used alone for lymph node staging in intermediate- or high-risk PC patients.
The overall performance of the tested computer-aided diagnosis (CADx) system was similar to that of the Prostate Imaging Reporting and Data System version 2 score assigned prospectively at the time ...of biopsy. The CADx predefined diagnostic thresholds, which provided 90% sensitivity in the training dataset, yielded sensitivity of 86% (95% confidence interval: 76–94) and specificity of 64% (95% confidence interval: 55–74) in the test dataset. The CADx score could help stratify the risk of clinically significant prostate cancer in patients with positive magnetic resonance imaging and negative prostate-specific antigen density.
Prostate multiparametric magnetic resonance imaging (MRI) shows high sensitivity for International Society of Urological Pathology grade group (GG) ≥2 cancers. Many artificial intelligence algorithms have shown promising results in diagnosing clinically significant prostate cancer on MRI. To assess a region-of-interest–based machine-learning algorithm aimed at characterising GG ≥2 prostate cancer on multiparametric MRI.
The lesions targeted at biopsy in the MRI-FIRST dataset were retrospectively delineated and assessed using a previously developed algorithm. The Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) score assigned prospectively before biopsy and the algorithm score calculated retrospectively in the regions of interest were compared for diagnosing GG ≥2 cancer, using the areas under the curve (AUCs), and sensitivities and specificities calculated with predefined thresholds (PIRADSv2 scores ≥3 and ≥4; algorithm scores yielding 90% sensitivity in the training database). Ten predefined biopsy strategies were assessed retrospectively.
After excluding 19 patients, we analysed 232 patients imaged on 16 different scanners; 85 had GG ≥2 cancer at biopsy. At patient level, AUCs of the algorithm and PI-RADSv2 were 77% (95% confidence interval CI: 70–82) and 80% (CI: 74–85; p = 0.36), respectively. The algorithm’s sensitivity and specificity were 86% (CI: 76–93) and 65% (CI: 54–73), respectively. PI-RADSv2 sensitivities and specificities were 95% (CI: 89–100) and 38% (CI: 26–47), and 89% (CI: 79–96) and 47% (CI: 35–57) for thresholds of ≥3 and ≥4, respectively. Using the PI-RADSv2 score to trigger a biopsy would have avoided 26–34% of biopsies while missing 5–11% of GG ≥2 cancers. Combining prostate-specific antigen density, the PI-RADSv2 and algorithm’s scores would have avoided 44–47% of biopsies while missing 6–9% of GG ≥2 cancers. Limitations include the retrospective nature of the study and a lack of PI-RADS version 2.1 assessment.
The algorithm provided robust results in the multicentre multiscanner MRI-FIRST database and could help select patients for biopsy.
An artificial intelligence–based algorithm aimed at diagnosing aggressive cancers on prostate magnetic resonance imaging showed results similar to expert human assessment in a prospectively acquired multicentre test database.
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