Quantitative MRI in the Local Staging of Prostate Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND: Local staging of prostate cancer (PCa) is important for treatment planning. Radiologist interpretation using qualitative criteria is variable with high specificity but low sensitivity. Quantitative methods may be useful in the diagnosis of extracapsular extension (ECE). PURPOSE: To assess the performance of quantitative MRI markers for detecting ECE. STUDY TYPE: Systematic review and meta-analysis. SUBJECTS: 4800 patients from 28 studies with histopathologically confirmed PCa on radical prostatectomy were pooled for meta-analysis. Patients from 46 studies were included for systematic review. FIELD STRENGTH/SEQUENCE: Diffusion-weighted, T2-weighted, and dynamic contrast-enhanced MRI at 1.5 T or 3 T. ASSESSMENT: PubMed, Embase, Web of Science, Scopus, and Cochrane databases were searched to identify studies on diagnostic test accuracy or association of any quantitative MRI markers with ECE. Results extracted by two independent reviewers for tumor contact length (TCL) and mean apparent diffusion coefficient (ADC-mean) were pooled for meta-analysis, but not for other quantitative markers including radiomics due to low number of studies available. STATISTICAL TESTS: Hierarchical summary receiver operating characteristic (HSROC) curves were computed for both TCL and ADC-mean, but summary operating points were computed for TCL only. Heterogeneity was investigated by meta-regression. Results were significant if P ≤ 0.05. RESULTS: At the 10 mm threshold for TCL, summary sensitivity and specificity were 0.76 [95% confidence interval (CI) 0.71-0.81] and 0.68 [95% CI 0.63-0.73], respectively. At the 15 mm threshold, summary sensitivity and specificity were 0.70 [95% CI 0.53-0.83] and 0.74 [95% CI 0.60-0.84] respectively. The area under the HSROC curves for TCL and ADC-mean were 0.79 and 0.78, respectively. Significant sources of heterogeneity for TCL included timing of MRI relative to biopsy. DATA CONCLUSION: Both 10 mm and 15 mm thresholds for TCL may be reasonable for clinical use. From comparison of the HSROC curves, ADC-mean may be superior to TCL at higher sensitivities. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Defining the role of multiparametric MRI in predicting prostate cancer extracapsular extension.

OBJECTIVES: To identify the predictive factors of prostate cancer extracapsular extension (ECE) in an institutional cohort of patients who underwent multiparametric MRI of the prostate prior to radical prostatectomy (RP). PATIENTS AND METHODS: Overall, 126 patients met the selection criteria, and their medical records were retrospectively collected and analysed; 2 experienced radiologists reviewed the imaging studies. Logistic regression analysis was conducted to identify the variables associated to ECE at whole-mount histology of RP specimens; according to the statistically significant variables associated, a predictive model was developed and calibrated with the Hosmer-Lomeshow test. RESULTS: The predictive ability to detect ECE with the generated model was 81.4% by including the length of capsular involvement (LCI) and intraprostatic perineural invasion (IPNI). The predictive accuracy of the model at the ROC curve analysis showed an area under the curve (AUC) of 0.83 [95% CI (0.76-0.90)], p < 0.001. Concordance between radiologists was substantial in all parameters examined (p < 0.001). Limitations include the retrospective design, limited number of cases, and MRI images reassessment according to PI-RADS v2.0. CONCLUSION: The LCI is the most robust MRI factor associated to ECE; in our series, we found a strong predictive accuracy when combined in a model with the IPNI presence. This outcome may prompt a change in the definition of PI-RADS score 5.

Utility of positive core number on MRI-ultrasound fusion targeted biopsy in combination with PI-RADS scores for predicting unexpected extracapsular extension of clinically localized prostate cancer.

OBJECTIVES: To evaluate the utility of magnetic resonance imaging (MRI) and MRI-ultrasound fusion targeted biopsy (TB) for predicting unexpected extracapsular extension (ECE) in clinically localized prostate cancer (CLPC). METHODS: This study enrolled 89 prostate cancer patients with one or more lesions showing a Prostate Imaging-Reporting and Data System (PI-RADS) score ≥3 but without morphological abnormality in the prostatic capsule on pre-biopsy MRI. All patients underwent TB and systematic biopsy followed by radical prostatectomy (RP). Each lesion was examined by 3-core TB, taking cores from each third of the lesion. The preoperative variables predictive of ECE were explored by referring to RP specimens in the lesion-based analysis. RESULTS: Overall, 186 lesions, including 81 (43.5%), 73 (39.2%), and 32 (17.2%) with PI-RADS 3, 4, and 5, respectively, were analyzed. One hundred and twenty-two lesions (65.6%) were diagnosed as cancer on TB, and ECE was identified in 33 (17.7%) on the RP specimens. The positive TB core number was ≤2 in 129 lesions (69.4%) and three in 57 lesions (30.6%). On the multivariate analysis, PI-RADS ≥4 (p = 0.049, odds ratio [OR] = 2.39) and three positive cores on TB (p = 0.005, OR = 3.07) were independent predictors of ECE. Lesions with PI-RADS ≥4 and a positive TB core number of 3 had a significantly higher rate of ECE than those with PI-RADS 3 and a positive TB core number ≤2 (37.5% vs. 7.8%, p < 0.001). CONCLUSIONS: Positive TB core number in combination with PI-RADS scores is helpful to predict unexpected ECE in CLPC.

Transperineal template saturation and conventional biopsy for stage prediction in prostate cancer.

OBJECTIVE: To evaluate the performance of risk calculators (RCs) predicting lymph node invasion (LNI) and extraprostatic extension (EPE) in men undergoing transperineal magnetic resonance imaging/transrectal ultrasound (TRUS)-fusion template saturation biopsy (TTSB) and conventional systematic TRUS-guided biopsy (SB). PATIENTS AND METHODS: The RCs were tested in a consecutive cohort of 645 men undergoing radical prostatectomy with extended pelvic LN dissection between 2005 and 2019. TTSB was performed in 230 (35.7%) and SB in 415 (64.3%) men. Risk of LNI and EPE was calculated using the available RCs. Discrimination, calibration, and clinical usefulness stratified by different biopsy techniques were assessed. RESULTS: Lymph node invasion was observed in 23 (10%) and EPE in 73 (31.8%) of cases with TTSB and 53 (12.8%) and 158 (38%) with SB, respectively. RCs showed an excellent discrimination and acceptable calibration for prediction of LNI based on TTSB (area under the curve [AUC]/risk estimation: Memorial Sloan Kettering Cancer Center [MSKCC]-RC 0.79/-4%, Briganti (2012)-RC 0.82/-4%, Gandaglia-RC 0.81/+6%). These were comparable in SB (MSKCC-RC 0.78/+2%; Briganti (2012)-RC 0.77/-3%). Decision curve analysis (DCA) revealed a net benefit at threshold probabilities between 3% and 6% when TTSB was used. For prediction of EPE based on TTSB an inferior discrimination and variable calibration were observed (AUC/risk estimation: MSKCC-RC 0.71/+8% and Martini (2018)-RC 0.69/+2%) achieving a net benefit on DCA only at risk thresholds of >17%. Performance of RCs for prediction of LNI and EPE based on SB showed comparable results with a better performance in the DCA for LNI (risk thresholds 1-2%) and poorer performance for EPE (risk threshold >20%). This study is limited by its retrospective single-institution design. CONCLUSIONS: The potentially more accurate grading ability of TTSB did not result in improved performance of preoperative RCs. Prediction tools for LNI proved clinical usefulness while RCs for EPE did not.

Prediction of T staging in PI-RADS 4-5 prostate cancer by combination of multiparametric MRI and 68Ga-PSMA-11 PET/CT.

BACKGROUND: In this study, we explored the diagnostic performances of multiparametric magnetic resonance imaging (mpMRI), 68 Ga-PSMA-11 PET/CT and combination of 68 Ga-PSMA-11 PET/CT and mpMRI (mpMRI + PET/CT) for extracapsular extension (ECE). Based on the analyses above, we tested the feasibility of using mpMRI + PET/CT results to predict T staging in prostate cancer patients. METHODS: By enrolling 75 patients of prostate cancer with mpMRI and 68 Ga-PSMA-11 PET/CT before radical prostatectomy, we analyzed the detection performances of ECE in mpMRI, 68 Ga-PSMA-11 PET/CT and mpMRI + PET/CT on their lesion images matched with their pathological sample images layer by layer through receiver operating characteristics (ROC) analysis. By inputting the lesion data into Prostate Imaging Reporting and Data System (PI-RADS), we divided the lesions into different PI-RADS scores. The improvement of detecting ECE was analyzed by net reclassification improvement (NRI). The predictors for T staging were evaluated by using univariate and multivariable analysis. The Kappa test was used to evaluate the prediction ability. RESULTS: One hundred three regions of lesion were identified from 75 patients. 50 of 103 regions were positive for ECE. The ECE diagnosis AUC of mpMRI + PET/CT is higher than that of mpMRI alone (ΔAUC = 0.101; 95% CI, 0.0148 to 0.1860; p < 0.05, respectively). Compared to mpMRI, mpMRI + PET/CT has a significant improvement in detecting ECE in PI-RADS 4-5 (NRI 36.1%, p < 0.01). The diagnosis power of mpMRI + PET/CT was an independent predictor for T staging (p < 0.001) in logistic regression analysis. In patients with PI-RADS 4-5 lesions, 40 of 46 (87.0%) patients have correct T staging prediction from mpMRI + PET/CT (κ 0.70, p < 0.01). CONCLUSION: The prediction of T staging in PI-RADS 4-5 prostate cancer patients by mpMRI + PET/CT had a quite good performance.

Prostate-specific antigen level, biopsy grade group, and tumor-capsular contact length on magnetic resonance imaging are independently associated with an extraprostatic extension.

OBJECTIVE: To define the clinicopathological and radiological factors independently associated with the existence of an extraprostatic extension in radical prostatectomy specimens. METHODS: A total of 202 patients who underwent robotic prostatectomy following biparametric magnetic resonance imaging were assessed. We evaluated the clinicopathological and magnetic resonance imaging variables. We performed receiver-operating characteristic curve analyses to identify factors associated with extraprostatic extension. We engaged in multivariate analysis to identify factors independently associated with such extension. RESULTS: Extraprostatic extensions were apparent in the final prostatectomy specimens of 62 patients (31%). The areas under the curves of the prostate-specific antigen level, the biopsy grade group, and the tumor-capsular contact length on magnetic resonance imaging were 0.76, 0.71, and 0.70, respectively, in receiver-operating characteristic analysis when used to predict extraprostatic extension; thus, higher than the areas under the curves of the other variables (0.61-0.68). The prostate-specific antigen level (odds ratio 1.090, p = 0.004), the biopsy grade group (odds ratios 2.678 and 6.358, p = 0.017 and p < 0.001 for grade group 3-4 and 5), and the tumor-capsular contact length (odds ratio 1.079, p = 0.001) were independently associated with extraprostatic extension. When the three factors were combined, the area under the receiver-operator characteristic curve increased to 0.79. CONCLUSIONS: The prostate-specific antigen level, the biopsy grade group, and the tumor-capsular contact length on magnetic resonance imaging were independently associated with extracapsular extension.

Therapeutic efficacy of selective intra-arterial chemoradiotherapy with docetaxel and nedaplatin for fixed bulky nodal disease in head and neck cancer of unknown primary.

PURPOSE: Fixed bulky nodal disease in patients with head and neck cancer of unknown primary (HNCUP) remains difficult to treat. This retrospective study evaluated the therapeutic efficacy of selective intra-arterial chemoradiotherapy with docetaxel and nedaplatin for fixed bulky nodal disease in HNCUP. METHODS: Data from seven consecutive patients with fixed bulky nodal disease in HNCUP who had undergone selective intra-arterial chemoradiotherapy were analyzed. Whole pharyngeal mucosa and all bilateral nodal areas were irradiated (total dose 50 Gy), and bulky nodal lesions were provided an additional 20 Gy. Intra-arterial chemotherapy used a combination of nedaplatin (80 mg/m2) and docetaxel (60 mg/m2). Outcome measures were local control, disease-free survival, overall survival, and adverse events. Statistical analyses were performed using the Kaplan-Meier method. RESULTS: Median follow-up period was 24 months (range 9-64). All patients had extracapsular extension (N3b) on imaging and clinical findings. Symptoms due to bulky disease were neck discomfort (100%), tumor bleeding (43%), tracheal obstruction (14%), and carotid sinus syndrome (28%). Median value for maximum diameter of cervical disease was 84 mm (range 70-107), and 3-year local control, disease-free survival, and overall survival rates were 100, 54, and 64%, respectively. Symptoms due to bulky disease disappeared in all patients after intra-arterial chemoradiotherapy. Grade 4 leukopenia occurred in two patients (28%) as an acute adverse event. No other serious acute adverse events were observed. CONCLUSION: Selective intra-arterial chemoradiotherapy with docetaxel and nedaplatin can potentially achieve both favorable local control and survival in in HNCUP with fixed bulky nodal disease.

Artificial intelligence is a promising prospect for the detection of prostate cancer extracapsular extension with mpMRI: a two-center comparative study.

PURPOSE: A balance between preserving urinary continence as well as sexual potency and achieving negative surgical margins is of clinical relevance while implementary difficulty. Accurate detection of extracapsular extension (ECE) of prostate cancer (PCa) is thus crucial for determining appropriate treatment options. We aimed to develop and validate an artificial intelligence (AI)-based tool for detecting ECE of PCa using multiparametric magnetic resonance imaging (mpMRI). METHODS: Eight hundred and forty nine consecutive PCa patients who underwent mpMRI and prostatectomy without previous radio- or hormonal therapy from two medical centers were retrospectively included. The AI tool was built on a ResNeXt network embedded with a spatial attention map of experts' prior knowledge (PAGNet) from 596 training patients. Model validation was performed in 150 internal and 103 external patients. Performance comparison was made between AI, two experts using a criteria-based ECE grading system, and expert-AI interaction. RESULTS: An index PAGNet model using a single-slice image yielded the highest areas under the receiver operating characteristic curve (AUC) of 0.857 (95% confidence interval [CI], 0.827-0.884), 0.807 (95% CI, 0.735-0.867), and 0.728 (95% CI, 0.631-0.811) in training, internal, and external validation data, respectively. The performance of two experts (AUC, 0.632 to 0.741 vs 0.715 to 0.857) was lower (paired comparison, all p values < 0.05) than that of AI assessment. When experts' interpretations were adjusted by AI assessments, the performance of two experts was improved. CONCLUSION: Our AI tool, showing improved accuracy, offers a promising alternative to human experts for ECE staging using mpMRI.

Multiparametric Magnetic Resonance Imaging-Based Peritumoral Radiomics for Preoperative Prediction of the Presence of Extracapsular Extension With Prostate Cancer.

BACKGROUND: Preoperative prediction of extracapsular extension (ECE) of prostate cancer (PCa) is important to guide clinical decision-making and improve patient prognosis. PURPOSE: To investigate the value of multiparametric magnetic resonance imaging (mpMRI)-based peritumoral radiomics for preoperative prediction of the presence of ECE. STUDY TYPE: Retrospective. POPULATION: Two hundred eighty-four patients with PCa from two centers (center 1: 226 patients; center 2: 58 patients). Cases from center 1 were randomly divided into training (158 patients) and internal validation (68 patients) sets. Cases from center 2 were assigned to the external validation set. FIELD STRENGTH/SEQUENCE: A 3.0 T MRI scanners (three vendors). Sequence: Pelvic T2-weighted turbo/fast spin echo sequence and diffusion weighted echo planar imaging sequence. ASSESSMENT: The peritumoral region (PTR) was obtained by 3-12 mm (half of the tumor length) 3D dilatation of the intratumoral region (ITR). Single-MRI radiomics signatures, mpMRI radiomics signatures, and integrated models, which combined clinical characteristics with the radiomics signatures were built. The discrimination ability was assessed by area under the receiver operating characteristic curve (AUC) in the internal and external validation sets. STATISTICAL TESTS: Fisher's exact test, Mann-Whitney U-test, DeLong test. RESULTS: The PTR radiomics signatures demonstrated significantly better performance than the corresponding ITR radiomics signatures (AUC: 0.674 vs. 0.554, P < 0.05 on T2-weighted, 0.652 vs. 0.546, P < 0.05 on apparent diffusion coefficient, 0.682 vs. 0.556 on mpMRI in the external validation set). The integrated models combining the PTR radiomics signature with clinical characteristics performed better than corresponding radiomics signatures in the internal validation set (eg. AUC: 0.718 vs. 0.671, P < 0.05 on mpMRI) but performed similar in the external validation set (eg. AUC: 0.684, vs. 0.682, P = 0.45 on mpMRI). DATA CONCLUSION: The peritumoral radiomics can better predict the presence of ECE preoperatively compared with the intratumoral radiomics and may have better generalization than clinical characteristics. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: 2.

Combined systematic versus stand-alone multiparametric MRI-guided targeted fusion biopsy: nomogram prediction of non-organ-confined prostate cancer.

OBJECTIVE: Based on unfavorable oncological and functional outcomes of non-organ-confined (NOC) prostate cancer (PCa), defined as ≥ pT3, pN1 or both, we aimed to develop a NOC prediction tool based on multiparametric MRI-guided targeted fusion biopsy (TBx). MATERIALS AND METHODS: Analyses were restricted to 594 patients with simultaneous PCa detection at systematic biopsy (SBx), TBx and subsequent radical prostatectomy (RP) at our institution. Development (n = 396; cohort 1) and validation cohorts (n = 198; cohort 2) were used to develop and validate the NOC nomogram. A head-to-head comparison was performed between stand-alone TBx model and combined TBx/SBx model. Second validation was performed in patients with positive TBx, but negative SBx (n = 193; cohort 3). RESULTS: The most parsimonious TBx model included three independent predictors of NOC: pretreatment PSA (OR 1.05 95% CI: 1.01-1.08), highest TBx-detected Gleason pattern (3 + 3 [REF] vs. ≥ 4 + 5; OR 9.3 95% CI 3.8-22) and presence of TBx-detected perineural invasion (OR 2.2 95% CI: 1.3-3.6). The combined TBx/SBx model had the same predictors. For the stand-alone TBx and combined TBx/SBx model, external validation yielded accuracy of 76.5% (95% CI: 69.3-83.1) and 76.6% (95% CI: 69.4-83.6) within cohort 2. The external validation of the stand-alone TBx model yielded 72.4% (95% CI: 65.0-79.6) accuracy within cohort 3. CONCLUSION: Our stand-alone TBx-based nomogram can identify PCa patients at the risk of NOC, using three simple variables, with the similar accuracy as the TBx/SBx-based model. It is non-inferior to combined TBx/SBx-based model and performs with sufficient accuracy in specific patients with positive TBx, but negative SBx.

Extracapsular extension of neck nodes and absence of human papillomavirus 16-DNA are predictors of impaired survival in p16-positive oropharyngeal squamous cell carcinoma.

BACKGROUND: Human papillomavirus (HPV)-driven oropharyngeal squamous cell carcinomas (OPSCCs) demonstrate superior outcome compared with HPV-negative OPSCCs. The eighth edition of the American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) tumor, lymph node, metastasis (TNM) classification (TNM 2017) modifies OPSCC staging based on p16 positivity as a surrogate for HPV-driven disease. In p16-negative OPSCCs, lymph node (N) categories include extracapsular/extranodal extension (ECE); and, in p16-positive OPSCCs, N categories are based on the number of positive neck lymph nodes omitting ECE status. The objective of the current study was to assess the prognostic impact of positive ECE status and the detection of HPV16 DNA in patients with p16-positive OPSCC. METHODS: In a cohort of 92 patients with p16-positive, lymph node (N)-positive (stage III-IVB) OPSCC who underwent surgery and neck dissection, allowing for a pathologic examination of positive lymph nodes, 66 of 92 patients (71.4%) were p16-positive/HPV16 DNA-positive, 62 of 92 (67%) were ECE-positive, and 45 of 62 (72.6%) were ECE-positive, p16-positive, and HPV16 DNA-positive. Differences in outcome were assessed using Kaplan-Meier plots and Cox proportional hazard regression (CoxR) for tumor-specific survival and overall survival (OS). RESULTS: The mean numbers of positive lymph nodes in ECE-positive patients (5.0 positive lymph nodes; 95% CI, 3.8-6.4 positive lymph nodes) and ECE-negative patients (2.4 positive lymph nodes; 95% CI, 1.8-2.9 positive lymph nodes) were different (P = .0007). ECE affected OS and tumor-specific survival in p16-positive patients (P = .007 and P = .047, respectively) and in p16-positive/HPV16 DNA-positive patients (P = .013 and P = .026, respectively). Related to the unequal distributions of ECE-positive/HPV16 DNA-negative tumors, the TNM 2017 failed to discriminate OS in patients with UICC stage I, II, and III disease (mean OS, 54.5, 73.4, and 45 months, respectively; median OS, 64.7 months, not reached, and 41.1 months, respectively). According to a univariate CoxR, the presence of ECE predicted impaired OS in patients with p16-positive OPSCC (hazard ratio, 3.40; 95% CI, 1.17-9.89; P = .025) and even greater impaired OS in those with p16-positive/HPV16 DNA-positive OPSCC (HR, 8.64; 95% CI, 1.12-66.40; P = .038). Multivariate CoxR confirmed ECE and HPV16 DNA detection as independent predictors. CONCLUSIONS: ECE and HPV16 DNA status should be included in the prognostic staging of patients with p16-positive OPSCC because several lines of evidence demonstrate their impact on survival.

Extracapsular extension in the positive sentinel lymph node: a marker of poor prognosis in cT1-2N0 breast cancer patients?

OBJECTIVE: This study aims to evaluate whether extracapsular extension (ECE) in the sentinel lymph node (SLN) is associated with involvement of ≥ 4 lymph node metastases at completion axillary lymph node dissection (ALND) and the effect on 5-year disease-free survival (DFS) and 10-year overall survival (OS). ECE in a SLN is usually a contraindication for omitting completion ALND in cT1-2N0 breast cancer patients treated with breast-conserving therapy and 1-2 positive SLN(s). METHODS: All cT1-2N0 breast cancer patients with 1-3 positive SLN(s) who underwent ALND between 2005 and 2008 were selected from the Netherlands Cancer Registry. Logistic regression analysis was used to determine the association between ECE and ≥ 4 lymph node metastases. Five-year DFS and 10-year OS were analyzed using Kaplan-Meier survival analysis. Cox regression analysis was performed to correct for other prognostic factors. RESULTS: A total of 3502 patients were included. Information on ECE was available for 2111 (60.3%) patients, consisting of 741 (35.1%) patients with and 1370 (64.9%) without ECE. The incidence of ≥ 4 lymph node metastases was 116 (15.7%) in the ECE group vs. 80 (5.8%) in the group without ECE (p < 0.001). Five-year DFS rate was 86.4% in the ECE group compared to 88.8% in the group without ECE (p = 0.085). 10-year OS rate was 78.6% compared to 83.0% (p = 0.018), respectively. Cox regression analysis showed that ECE was not an independent prognostic factor for both DFS and OS. CONCLUSIONS: ECE was significantly associated with involvement of ≥ 4 lymph node metastases in the completion ALND group. ECE was not an independent prognostic factor for both DFS and OS.

MRI-Based Radiomics Signature for the Preoperative Prediction of Extracapsular Extension of Prostate Cancer.

BACKGROUND: Radiomics approaches based on multiparametric MRI (mp-MRI) have shown high accuracy in prostate cancer (PCa) management. However, there is a need to apply radiomics to the preoperative prediction of extracapsular extension (ECE). PURPOSE: To develop and validate a radiomics signature to preoperatively predict the probability of ECE for patients with PCa, compared with the radiologists' interpretations. STUDY TYPE: Retrospective. POPULATION: In total, 210 patients with pathology-confirmed ECE status (101 positive, 109 negative) were enrolled. FIELD STRENGTH/SEQUENCE: T2 -weighted imaging (T2 WI), diffusion-weighted imaging, and dynamic contrast-enhanced imaging were performed on two 3.0T MR scanners. ASSESSMENT: A radiomics signature was constructed to predict the probability of ECE prior to radical prostatectomy (RP). In all, 17 stable radiomics features of 1619 extracted features based on T2 WI were selected. The same images were also evaluated by three radiologists. The predictive performance of the radiomics signature was validated and compared with radiologists' interpretations. STATISTICAL TESTS: A radiomics signature was developed by a least absolute shrinkage and selection operator (LASSO) regression algorithm. Samples enrolled were randomly divided into two groups (143 for training and 67 for validation). Discrimination, calibration, and clinical usefulness were validated by analysis of the receiver operating characteristic (ROC) curve, calibration curve, and the decision curve, respectively. The predictive performance was then compared with visual assessments of three radiologists. RESULTS: The radiomics signature yielded an AUC of 0.902 and 0.883 in the training and validation cohort, respectively, and outperformed the visual assessment (AUC: 0.600-0.697) in the validation cohort. Pairwise comparisons demonstrated that the radiomics signature was more sensitive than the radiologists (75.00% vs. 46.88%-50.00%, all P < 0.05), but obtained comparable specificities (91.43% vs. (88.57%-94.29%); P ranged from 0.64-1.00). DATA CONCLUSION: A radiomics signature was developed and validated that outperformed the radiologists' visual assessments in predicting ECE status. LEVEL OF EVIDENCE: 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1914-1925.

An updated approach to incremental nerve sparing for robot-assisted radical prostatectomy.

OBJECTIVES: To update the algorithm for performing incremental nerve sparing (NS) using our multiparametric magnetic resonance imaging (mpMRI)-based nomogram. PATIENTS AND METHODS: We applied the coefficients of the nomogram to the observations extracted from our population of patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015 and who received preoperative mpMRI. The information considered were PSA level, highest side-specific biopsy Gleason grade group, highest ipsilateral percentage core involvement with the highest Gleason grade group, and extracapsular extension (ECE) on mpMRI. The nomogram-derived probability [P (%)], after internal validation, was used as the independent variable on a classification tree to identify the most significant thresholds for ECE prediction. Incremental NS was performed as follows: Grade 1 NS: intrafascial dissection between the peri-prostatic veins and the pseudocapsule of the prostate; Grade 2 NS: inter-fascial dissection along the peri-venous plane; Grade 3 NS: inter-fascial dissection through the outer compartment of the lateral prostatic fascia; Grade 4 NS: extrafascial dissection. RESULTS: Data from 561 patients were considered, and 829 prostatic lobes with biopsy-documented tumour were analysed. Overall, 142 lobes presented ECE that was focal in 27 (19%) cases. The classification tree identified four risk categories. In the low- [P (%) ≤10], intermediate- [P (%) 10-21], high [P (%) 21-73] and very-high-risk [P(%) >73] groups, the ECE rates were 3.3%, 16%, 61.6% and 90%, respectively. Amongst those, ECE was focal in 41.7%, 31.7%, 7.9% and 0%, respectively. CONCLUSION: We suggest that Grade 1 NS (intrafascial) should be performed in the low-risk group. The inter-fascial approach, namely grades 2 and 3 NS, should be performed in the intermediate- and high-risk categories, respectively. Grade 4 NS (extrafascial) should be performed in the very-high-risk group. The current algorithm yields a better accuracy than the previous one; however, prospective validation is warranted.

Lymphovascular invasion and extranodal tumour extension are risk indicators of breast cancer related lymphoedema: an observational retrospective study with long-term follow-up.

BACKGROUND: Breast cancer related lymphoedema (BCRL) occurs in a substantial proportion of breast cancer survivors and is a major contributor to patients' disability. Regrettably, there are no validated predictive biomarkers, diagnostic tools, and strong evidence-supported therapeutic strategies for BCRL. Here, we provide an integrative characterization of a large series of women with node-positive breast cancers and identify new bona fide predictors of BCRL occurrence. METHODS: Three hundred thirty-two cases of surgically-treated node-positive breast cancers were retrospectively collected (2-10.2 years of follow-up). Among them, 62 patients developed BCRL. To identify demographic and clinicopathologic features related to BCRL, Fisher's exact test or Chi-squared test were carried out for categorical variables; the Wilcoxon rank-sum was employed for continuous variables. Factors associated with BCRL occurrence were assessed using a Cox proportional hazards regression model. RESULTS: En-bloc dissection of the axillary lymph nodes but not the type of breast surgery impacted on BCRL development. Most of BCRL patients had a Luminal A-like neoplasm. The median number of lymph nodes involved by metastatic deposits was significantly higher in BCRL compared to the control group (p = 0.04). Both peritumoral lymphovascular invasion (LVI) and extranodal extension (ENE) of the metastasis had a negative impact on BCRL-free survival (p = 0.01). Specifically, patients with LVI and left side localization harboured 4-fold higher risk of developing BCRL, while right axillary nodes metastases with ENE increased the probability of BCRL compared to ENE-negative patients. CONCLUSIONS: Assessment of LVI and ENE should be integrated with clinical and surgical data to improve BCRL risk stratification.

A novel tool for predicting extracapsular extension during graded partial nerve sparing in radical prostatectomy.

OBJECTIVES: To create a statistical tool for the estimation of extracapsular extension (ECE) level of prostate cancer and determine the nerve-sparing (NS) approach that can be safely performed during radical prostatectomy (RP). PATIENTS AND METHODS: A total of 11 794 lobes, from 6 360 patients who underwent robot-assisted RP between 2008 and 2016 were evaluated. Clinicopathological features were included in a statistical algorithm for the prediction of the maximum ECE width. Five multivariable logistic models were estimated for: presence of ECE and ECE width of >1, >2, >3, and >4 mm. A five-zone decision rule based on a lower and upper threshold is proposed. Using a graphical interface, surgeons can view patient's pre-treatment characteristics and a curve showing the estimated probabilities for ECE amount together with the areas identified by the decision rule. RESULTS: Of the 6 360 patients, 1 803 (28.4%) were affected by non-organ-confined disease. ECE was present in 1 351 lobes (11.4%) and extended beyond the capsule for >1, >2, >3, and >4 mm in 498 (4.2%), 261 (2.2%), 148 (1.3%), 99 (0.8%) cases, respectively. ECE width was up to 15 mm (interquartile range 1.00-2.00). The five logistic models showed good predictive performance, the area under the receiver operating characteristic curve was: 0.81 for ECE, and 0.84, 0.85, 0.88, and 0.90 for ECE width of >1, >2, >3, and >4 mm, respectively. CONCLUSION: This novel tool predicts with good accuracy the presence and amount of ECE. Furthermore, the graphical interface available at www.prece.it can support surgeons in patient counselling and preoperative planning.

Development and internal validation of a side-specific, multiparametric magnetic resonance imaging-based nomogram for the prediction of extracapsular extension of prostate cancer.

OBJECTIVES: To develop a nomogram for predicting side-specific extracapsular extension (ECE) for planning nerve-sparing radical prostatectomy. MATERIALS AND METHODS: We retrospectively analysed data from 561 patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015. To develop a side-specific predictive model, we considered the prostatic lobes separately. Four variables were included: prostate-specific antigen; highest ipsilateral biopsy Gleason grade; highest ipsilateral percentage core involvement; and ECE on multiparametric magnetic resonance imaging (mpMRI). A multivariable logistic regression analysis was fitted to predict side-specific ECE. A nomogram was built based on the coefficients of the logit function. Internal validation was performed using 'leave-one-out' cross-validation. Calibration was graphically investigated. The decision curve analysis was used to evaluate the net clinical benefit. RESULTS: The study population consisted of 829 side-specific cases, after excluding negative biopsy observations (n = 293). ECE was reported on mpMRI and final pathology in 115 (14%) and 142 (17.1%) cases, respectively. Among these, mpMRI was able to predict ECE correctly in 57 (40.1%) cases. All variables in the model except highest percentage core involvement were predictors of ECE (all P ≤ 0.006). All variables were considered for inclusion in the nomogram. After internal validation, the area under the curve was 82.11%. The model demonstrated excellent calibration and improved clinical risk prediction, especially when compared with relying on mpMRI prediction of ECE alone. When retrospectively applying the nomogram-derived probability, using a 20% threshold for performing nerve-sparing, nine out of 14 positive surgical margins (PSMs) at the site of ECE resulted above the threshold. CONCLUSION: We developed an easy-to-use model for the prediction of side-specific ECE, and hope it serves as a tool for planning nerve-sparing radical prostatectomy and in the reduction of PSM in future series.

Evaluation of extracapsular extension in prostate cancer using qualitative and quantitative multiparametric MRI.

PURPOSE: To investigate the value of multiparametric magnetic resonance imaging (mpMRI) for extracapsular extension (ECE) in prostate cancer (PCa). MATERIALS AND METHODS: In all, 292 patients who received radical prostatectomy and underwent preoperative mpMRI at 3T were enrolled retrospectively. For determining the associations with ECE, the likelihood of ECE was assessed qualitatively on T2 -weighted imaging (T2 WI) and combined T2 WI and diffusion-weighted imaging (DWI) or dynamic contrast-enhanced imaging (DCEI). Quantitative MRI parameters were measured in PCa based on histopathological findings. Two models for detecting ECE including imaging and clinical parameters were developed using multivariate analysis: Model 1 excluding combined T2 WI and DWI and DCEI and Model 2 excluding combined T2 WI and DWI, and combined T2 WI and DCEI. Diagnostic performance of imaging parameters and models was evaluated using the area under the receiver operating characteristics curve (Az). RESULTS: For detecting ECE, the specificity, accuracy, and Az of combined T2 WI and DWI or DCEI were statistically better than those of T2 WI (P < 0.05), and all quantitative MRI parameters showed a statistical difference between the patients with and without ECE (P < 0.05). On multivariate analysis, significant independent markers in Model 1 were combined T2 WI and DWI, combined T2 WI and DCEI, and Ktrans (P < 0.05). In Model 2, significant markers were combined T2 WI and DWI and DCEI, Ktrans , Kep , and Ve (P < 0.05). The Az values of models 1 and 2 were 0.944 and 0.957, respectively. CONCLUSION: mpMRI may be useful to improve diagnostic accuracy of the models for determining the associations with ECE in PCa. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;45:1760-1770.

Impact of the Prostate Imaging Reporting and Data System, Version 2, on MRI Diagnosis for Extracapsular Extension of Prostate Cancer.

OBJECTIVE: The purpose of this study is to validate the Prostate Imaging Reporting and Data System, version 2 (PI-RADSv2), in assessing extracapsular extension (ECE), compared with PI-RADS, version 1 (PI-RADSv1). MATERIALS AND METHODS: A total of 210 patients with clinically localized prostate cancer underwent MRI and radical prostatectomy. Two readers independently interpreted the MR images. In PI-RADSv1, 5-point ECE risk scoring was used. In PI-RADSv2, ECE criteria included morphologic features and a tumor-capsule contact length (CL) greater than 10 mm. The diagnostic performance of each PI-RADS version and the cutoff CL were evaluated. RESULTS: ECE was found in 56 patients (26.7%). In PI-RADSv1, maximal accuracy was achieved with a risk score of 3 or greater. At this threshold, positive findings on PI-RADSv1 and PI-RADSv2 were identified in 21.0-34.3% and 49.0-51.4% of patients, respectively. Compared with PI-RADSv1, PI-RADSv2 had higher negative predictive values (84.9-89.1% vs 96.3-97.1%, respectively; p = 0.003 and 0.021, for each reader). PI-RADSv1 and PI-RADSv2 had positive predictive values of 56.9-70.5% and 49.1-50.5%, respectively (p = 0.025 and 0.300, respectively). Interobserver kappa values for PI-RADSv1 and PI-RADSv2 were 0.511 and 0.781, respectively. The best cutoff CL was greater than 10 mm among patients without morphologic features of ECE. For patients positive for ECE on the basis of PI-RADSv2 but not PI-RADSv1, 73.3-74.1% of prostate cancer cases with a biopsy Gleason score of 7 or less and 35.7-44.4% of cases with a biopsy Gleason score of 8 or higher were overstaged. CONCLUSION: PI-RADSv2 reduces understaging and improves interobserver agreement in ECE assessment. However, overstaging is a concern, and the biopsy Gleason score may have a complementary role in reducing overstaging.

Length of capsular contact on prostate MRI as a predictor of extracapsular extension: which is the most optimal sequence?

Background Length of capsular contact (LCC) is a promising biomarker for predicting extracapsular extension (ECE), but the most optimal magnetic resonance imaging (MRI) sequence for measuring LCC is yet to be determined. Purpose To evaluate LCC using different MRI sequences for determining ECE in prostate cancer. Material and Methods A total of 185 patients underwent prostate MRI followed by radical prostatectomy. LCC was measured separately on T2-weighted (T2W) images, apparent diffusion coefficient (ADC) maps, and dynamic contrast-enhanced (DCE) MRI. LCCs (LCCT2, LCCADC, LCCDCE, and LCCmax [greatest value of 3 LCCs]) were compared between sequences using Wilcoxon signed rank test and was tested for determining ECE using the Mann-Whitney U test, ROC curve analysis, and logistic regression analysis. Results There were no significant differences among LCCs ( P = 0.333-0.837). All LCCs were significantly greater in patients with ECE ( P < 0.001). The optimal threshold value for predicting ECE was >14, >13, >12, and >14 mm for LCCT2, LCCADC, LCCDCE, and LCCmax, respectively. LCCmax yielded the highest area under the curve (0.895) which was significantly greater than that by LCCADC (0.858, P = 0.030). Otherwise, there were no significant difference between LCCs ( P = 0.052-0.985). At univariate analysis, age, clinical stage, PSA, Gleason score, and all LCCs were significantly associated with ECE ( P < 0.001-0.040). At multivariate analysis, GS ( P ≤ 0.008) and all LCCs ( P < 0.001) were independently predictive factors. Conclusion LCC measured on any sequence was significantly different in patients with and without ECE and was independently associated with the presence of ECE. Although LCCmax showed the greatest ability to predict ECE, there was relatively equivalent performance among different MRI sequences.