Inter-Rater Variability of Prostate Lesion Segmentation on Multiparametric Prostate MRI.

INTRODUCTION: External radiotherapy is a major treatment for localized prostate cancer (PCa). Dose escalation to the whole prostate gland increases biochemical relapse-free survival but also acute and late toxicities. Dose escalation to the dominant index lesion (DIL) only is of growing interest. It requires a robust delineation of the DIL. In this context, we aimed to evaluate the inter-observer variability of DIL delineation. MATERIAL AND METHODS: Two junior radiologists and a senior radiation oncologist delineated DILs on 64 mpMRIs of patients with histologically confirmed PCa. For each mpMRI and each reader, eight individual DIL segmentations were delineated. These delineations were blindly performed from one another and resulted from the individual analysis of the T2, apparent diffusion coefficient (ADC), b2000, and dynamic contrast enhanced (DCE) sequences, as well as the analysis of combined sequences (T2ADC, T2ADCb2000, T2ADCDCE, and T2ADCb2000DCE). Delineation variability was assessed using the DICE coefficient, Jaccard index, Hausdorff distance measure, and mean distance to agreement. RESULTS: T2, ADC, T2ADC, b2000, T2 + ADC + b2000, T2 + ADC + DCE, and T2 + ADC + b2000 + DCE sequences obtained DICE coefficients of 0.51, 0.50, 0.54, 0.52, 0.54, 0.55, 0.53, respectively, which are significantly higher than the perfusion sequence alone (0.35, p < 0.001). The analysis of other similarity metrics lead to similar results. The tumor volume and PI-RADS classification were positively correlated with the DICE scores. CONCLUSION: Our study showed that the contours of prostatic lesions were more reproducible on certain sequences but confirmed the great variability of prostatic contours with a maximum DICE coefficient calculated at 0.55 (joint analysis of T2, ADC, and perfusion sequences).

Research on texture images and radiomics in urology: a review of urological MR imaging applications.

PURPOSE OF REVIEW: Tumor volume and heterogenicity are associated with diagnosis and prognosis of urological cancers, and assessed by conventional imaging. Quantitative imaging, Radiomics, using advanced mathematical analysis may contain information imperceptible to the human eye, and may identify imaging-based biomarkers, a new field of research for individualized medicine. This review summarizes the recent literature on radiomics in kidney and prostate cancers and the future perspectives. RECENT FINDINGS: Radiomics studies have been developed and showed promising results in diagnosis, in characterization, prognosis, treatment planning and recurrence prediction in kidney tumors and prostate cancer, but its use in guiding clinical decision-making remains limited at present due to several limitations including lack of external validations in most studies, lack of prospective studies and technical standardization. SUMMARY: Future challenges, besides developing prospective and validated studies, include automated segmentation using artificial intelligence deep learning networks and hybrid radiomics integrating clinical data, combining imaging modalities and genomic features. It is anticipated that these improvements may allow identify these noninvasive, imaging-based biomarkers, to enhance precise diagnosis, improve decision-making and guide tailored treatment.

Optimal PSA density threshold and predictive factors for the detection of clinically significant prostate cancer in patient with a PI-RADS 3 lesion on MRI.

INTRODUCTION: While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions usually justify prostate biopsy (PBx), the management of a PI-RADS 3 lesion can be discussed. The aim of our study was to determine the optimal prostate-specific antigen density (PSAD) threshold and predictive factors of clinically significant prostate cancer (csPCa) in patients with a PI-RADS 3 lesion on MRI. PATIENTS AND METHODS: Using our prospectively maintained database, we conducted a monocentric retrospective study, including all patients with a clinical suspicious of prostate cancer (PCa), all of them had a PI-RADS 3 lesion on the mpMRI prior to PBx. Patients under active surveillance or displaying suspicious digital rectal examination were excluded. Clinically significant (csPCa) was defined as PCa with any ISUP grade group ≥ 2 (Gleason ≥ 3 + 4). RESULTS: We included 158 patients. The detection rate of csPCa was 22.2%. In case of PSAD ≤ 0.15 ng/ml/cm3, PBx would be omitted in 71.5% (113/158) of men at the cost of missing 15.0% (17/113) of csPCa. With a threshold of 0.15 ng/ml/cm3, the sensitivity and the specificity were 0.51 and 0.78 respectively. The positive predictive value was 0.40 and the negative predictive value was 0.85. According to multivariate analysis, age (OR = 1.10, CI95% 1.03-1.19, P = 0.007), and PSAD ≥ 0.15 ng/ml/cm3 (OR = 3.59, CI95% 1.41-9.47, P = 0.008) were independent predictive factors of csPCa. Previous negative PBx was negatively associated with csPCa (OR = 0.24, CI 95% 0.07-0.66, P = 0.01). CONCLUSION: Our result suggests that the optimal PSAD threshold was 0.15 ng/ml/cm3. However, in this case omitting PBx in 71.5% of cases would be at the cost of missing 15.0% of csPCa. PSAD should not be used alone, other predictive factors as age and PBx history should also be considered in the discussion with the patient, to avoid PBx while missing few csPCa.

A Novel Nomogram to Identify Candidates for Focal Therapy Among Patients with Localized Prostate Cancer Diagnosed via Magnetic Resonance Imaging-Targeted and Systematic Biopsies: A European Multicenter Study.

BACKGROUND: Suitable selection criteria for focal therapy (FT) are crucial to achieve success in localized prostate cancer (PCa). OBJECTIVE: To develop a multivariable model that better delineates eligibility for FT and reduces undertreatment by predicting unfavorable disease at radical prostatectomy (RP). DESIGN, SETTING, AND PARTICIPANTS: Data were retrospectively collected from a prospective European multicenter cohort of 767 patients who underwent magnetic resonance imaging (MRI)-targeted and systematic biopsies followed by RP in eight referral centers between 2016 and 2021. The Imperial College of London eligibility criteria for FT were applied: (1) unifocal MRI lesion with Prostate Imaging-Reporting and Data System score of 3-5; (2) prostate-specific antigen (PSA) ≤20 ng/ml; (3) cT2-3a stage on MRI; and (4) International Society of Urological Pathology grade group (GG) 1 and ≥6 mm or GG 2-3. A total of 334 patients were included in the final analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was unfavorable disease at RP, defined as GG ≥4, and/or lymph node invasion, and/or seminal vesicle invasion, and/or contralateral clinically significant PCa. Logistic regression was used to assess predictors of unfavorable disease. The performance of the models including clinical, MRI, and biopsy information was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis. A coefficient-based nomogram was developed and internally validated. RESULTS AND LIMITATIONS: Overall, 43 patients (13%) had unfavorable disease on RP pathology. The model including PSA, clinical stage on digital rectal examination, and maximum lesion diameter on MRI had an AUC of 73% on internal validation and formed the basis of the nomogram. Addition of other MRI or biopsy information did not significantly improve the model performance. Using a cutoff of 25%, the proportion of patients eligible for FT was 89% at the cost of missing 30 patients (10%) with unfavorable disease. External validation is required before the nomogram can be used in clinical practice. CONCLUSIONS: We report the first nomogram that improves selection criteria for FT and limits the risk of undertreatment. PATIENT SUMMARY: We conducted a study to develop a better way of selecting patients for focal therapy for localized prostate cancer. A novel predictive tool was developed using the prostate-specific antigen (PSA) level measured before biopsy, tumor stage assessed via digital rectal examination, and lesion size on magnetic resonance imaging (MRI) scans. This tool improves the prediction of unfavorable disease and may reduce the risk of undertreatment of localized prostate cancer when using focal therapy.

Impact of age on the Quadrella index assessing oncological and functional results after prostate brachytherapy: A 6-year analysis.

Purpose: As the oncological results of prostate brachytherapy (BT) are excellent for low-risk (LR) or favorable intermediate-risk (FIR) prostate cancer (PCa), evaluating the side effects has become a major issue, especially for young men. The objective of the study was to compare the oncologic and functional results of BT using Quadrella index for patients aged 60 or less compared with older patients. Material and methods: From June, 2007 to June, 2017, 222 patients, including 70 ≤ 60 years old and 152 > 60 years old, underwent BT for LR-FIR PCa, with good erectile function at baseline according to International Index of Erectile Function-5 (IIEF-5) > 16. Quadrella index was achieved under the following circumstances: 1) Absence of biological recurrence (Phoenix criteria); 2) Absence of erectile dysfunction (ED) (IIEF-5 > 16); 3) No urinary toxicity (international prostate score symptom) IPSS < 15 or IPSS > 15, and ΔIPSS < 5; 4) No rectal toxicity (RT) (Radiation Therapy Oncology Group, RTOG = 0). Patients were treated on demand with phosphodiesterase inhibitors (PDE5i) post-operatively. Results: The Quadrella index was satisfied for about 40-80% of patients ≤ 60 years vs. 33-46% for older patients during 6-year follow-up (significant difference from the second year). At year 5, 100% of evaluable patients aged ≤ 60 and 91.8% > 60 (p = 0.29) reached Phoenix criteria. The criterion of ED (IIEF-5 < 16) largely explained the validity rate of Quadrella alone. There was no ED for 67.2-81.4% of patients ≤ 60 years compared with 40.0-56.1% for patients > 60 (significant difference since year 4 in favor of young men). After two years of follow-up, more than 90% of patients in both the groups showed neither urinary nor rectal toxicities. Conclusions: For young men displaying LR-FIR PCa, BT appears to be a first-class therapeutic option, as the oncological results were at least equivalent to those of older patients with good long-term tolerance.

Impact of a megacity on the water quality of a tropical estuary assessed by a combination of chemical analysis and in-vitro bioassays.

Tropical estuaries are threatened by rapid urbanization, which leads to the spread of thousands of micropollutants and poses an environmental risk to such sensitive aqueous ecosystems. In the present study, a combination of chemical and bioanalytical water characterization was applied to investigate the impact of Ho Chi Minh megacity (HCMC, 9.2 million inhabitants in 2021) on the Saigon River and its estuary and provide a comprehensive water quality assessment. Water samples were collected along a 140-km stretch integrating the river-estuary continuum from upstream HCMC down to the estuary mouth in the East Sea. Additional water samples were collected at the mouth of the four main canals of the city center. Chemical analysis was performed targeting up to 217 micropollutants (pharmaceuticals, plasticizers, PFASs, flame retardants, hormones, pesticides). Bioanalysis was performed using six in-vitro bioassays for hormone receptor-mediated effects, xenobiotic metabolism pathways and oxidative stress response, respectively, all accompanied by cytotoxicity measurement. A total of 120 micropollutants were detected and displayed high variability along the river continuum with total concentration ranging from 0.25 to 78 µg L-1. Among them, 59 micropollutants were ubiquitous (detection frequency ≥ 80 %). An attenuation was observed in concentration and effect profiles towards the estuary. The urban canals were identified as major sources of micropollutants and bioactivity to the river, and one canal (Ben Nghé) exceeded the effect-based trigger values derived for estrogenicity and xenobiotic metabolism. Iceberg modelling apportioned the contribution of the quantified and the unknown chemicals to the measured effects. Diuron, metolachlor, chlorpyrifos, daidzein, genistein, climbazole, mebendazole and telmisartan were identified as main risk drivers of the oxidative stress response and xenobiotic metabolism pathway activation. Our study reinforced the need for improved wastewater management and deeper evaluations of the occurrence and fate of micropollutants in urbanized tropical estuarine environments.

Optimizing multiparametric magnetic resonance imaging-targeted biopsy and prostate cancer grading accuracy.

PURPOSE: To assess the most efficient biopsy method to improve International Society of Urological Pathology (ISUP) grade group accuracy with final pathology of the radical prostatectomy (RP) specimen in the era of magnetic resonance imaging (MRI)-driven pathway. METHODS: A total of 753 patients diagnosed by transrectal MRI-targeted and systematic biopsies (namely "standard method"), treated by RP, between 2016 and 2021 were evaluated. Biopsy methods included MRI-targeted biopsy, side-specific systematic biopsies relative to index MRI lesion and combination of both. Number of MRI-targeted biopsy cores and positive cores needed per index MRI lesion were assessed. Multivariable analysis was performed to analyze predictive factors of upgrading using MRI targeted and ipsilateral systematic biopsies method. RESULTS: Overall, ISUP grade group accuracy varied among biopsy methods with upgrading rate of 35%, 49%, 27%, and 24% for MRI targeted, systematic, MRI targeted and ipsilateral systematic biopsies and standard methods, respectively (p < 0.001). A minimum of two positive MRI-targeted biopsies cores per index MRI lesion were required when testing MRI targeted and ipsilateral systematic biopsies method to reach equivalent accuracy compared to standard method. Omitting contralateral systematic biopsies spared an average of 5.9 cores per patient. At multivariable analysis, only the number of positive MRI-targeted biopsy cores per index MRI lesion was predictive of upgrading. CONCLUSION: MRI targeted and ipsilateral systematic biopsies allowed an accurate definition of ISUP grade group and appears to be an interesting alternative when compared with standard method, reducing total number of biopsy cores needed.

External Validation of Models for Prediction of Side-specific Extracapsular Extension in Prostate Cancer Patients Undergoing Radical Prostatectomy.

BACKGROUND: Predicting the risk of side-specific extracapsular extension (ECE) is essential for planning nerve-sparing radical prostatectomy (RP) in patients with prostate cancer (PCa). OBJECTIVE: To externally validate available models for prediction of ECE. DESIGN, SETTING, AND PARTICIPANTS: Sixteen models were assessed in a cohort of 737 consecutive PCa patients diagnosed via multiparametric magnetic resonance imaging (MRI)-targeted and systematic biopsies and treated with RP between January 2016 and November 2021 at eight referral centers. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Model performance was evaluated in terms of discrimination using area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA). RESULTS AND LIMITATIONS: Overall, ECE was identified in 308/1474 (21%) prostatic lobes. Prostatic lobes with ECE had higher side-specific clinical stage on digital rectal examination and MRI, number of positive biopsy cores, and International Society of Urological Pathology grade group in comparison to those without ECE (all p < 0.0001). Less optimistic performance was observed in comparison to previous published studies, although the models described by Pak, Patel, Martini, and Soeterik achieved the highest accuracy (AUC ranging from 0.73 to 0.77), adequate calibration for a probability threshold <40%, and the highest net benefit for a probability threshold >8% on DCA. Inclusion of MRI-targeted biopsy data and MRI information in models improved patient selection and clinical usefulness. Using model-derived cutoffs suggested by their authors, approximately 15% of positive surgical margins could have been avoided. Some available models were not included because of missing data, which constitutes a limitation of the study. CONCLUSIONS: We report an external validation of models predicting ECE and identified the four with the best performance. These models should be applied for preoperative planning and patient counseling. PATIENT SUMMARY: We validated several tools for predicting extension of prostate cancer outside the prostate gland. These tools can improve patient selection for surgery that spares nerves affecting recovery of sexual potency after removal of the prostate. They could potentially reduce the risk of finding cancer cells at the edge of specimens taken for pathology, a finding that suggests that not all of the cancer has been removed.

Impact of Multiparametric MRI and PSA Density on the Initial Indication or the Maintaining in Active Surveillance During Follow-Up in low-Risk Prostate Cancer.

INTRODUCTION: A greater selection of candidates for active surveillance (AS) of prostate cancer (PCa) may decrease the rate of delayed treatment. We aimed to study: 1) the impact of MRI and PSA density (PSAd) at baseline on the final status, and 2) the impact of bio-clinical features during the follow-up on pursuing AS. MATERIALS AND METHODS: This retrospective, monocentric study between June 2013 and July 2020, included 99 patients in AS (median follow-up: 19 months [18-92]). All MRI were reviewed by a single radiologist. Lost to follow-up were 17 patients and 6 patients chose treatment by themselves. Treatment was proposed in case of upgrading (≥ GG2) or increasing PCa volume. RESULTS: Impact of MRI and PSAd at baseline:  Combining PSAd ≤ 0.15 and PIRADS ≤ 3, the probability to remain in AS was 72%. This rate reached 83% when PSAd ≤ 0.10 was associated to normal MRI.  During follow-up:  One hundred fifty-seven prostatic biopsies (PBx) were performed and 38 (24%) found PCa upgrading. The association between negative MRI and PSAd ≤ 0.10, during follow-up, had an excellent NPV to predict treatment (95%). This combination concerned 25% (37/151) of surveillance biopsies that could have been avoided at the cost of delaying upgrading in 3% (1/37). In multivariate analysis, only PIRADS ≥ 4 before PBx was associated to a risk of treatment during follow-up (OR, 10.4 [95% CI, 4.2-25.8]; P < .0001). CONCLUSION: Using PSAd and MRI at baseline to select patients showed excellent performances to predict the maintenance in AS. During follow-up, MRI PIRADS ≥ 4 was associated to an increased risk of treatment.

Preclinical Immune Response and Safety Evaluation of the Protein Subunit Vaccine Nanocovax for COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global health concern. The development of vaccines with high immunogenicity and safety is crucial for controlling the global COVID-19 pandemic and preventing further illness and fatalities. Here, we report the development of a SARS-CoV-2 vaccine candidate, Nanocovax, based on recombinant protein production of the extracellular (soluble) portion of the spike (S) protein of SARS-CoV-2. The results showed that Nanocovax induced high levels of S protein-specific IgG and neutralizing antibodies in three animal models: BALB/c mouse, Syrian hamster, and a non-human primate (Macaca leonina). In addition, a viral challenge study using the hamster model showed that Nanocovax protected the upper respiratory tract from SARS-CoV-2 infection. Nanocovax did not induce any adverse effects in mice (Mus musculus var. albino) and rats (Rattus norvegicus). These preclinical results indicate that Nanocovax is safe and effective.

Development of a Radiomic-Based Model Predicting Lymph Node Involvement in Prostate Cancer Patients.

Significant advances in lymph node involvement (LNI) risk modeling in prostate cancer (PCa) have been achieved with the addition of visual interpretation of magnetic resonance imaging (MRI) data, but it is likely that quantitative analysis could further improve prediction models. In this study, we aimed to develop and internally validate a novel LNI risk prediction model based on radiomic features extracted from preoperative multimodal MRI. All patients who underwent a preoperative MRI and radical prostatectomy with extensive lymph node dissection were retrospectively included in a single institution. Patients were randomly divided into the training (60%) and testing (40%) sets. Radiomic features were extracted from the index tumor volumes, delineated on the apparent diffusion coefficient corrected map and the T2 sequences. A ComBat harmonization method was applied to account for inter-site heterogeneity. A prediction model was trained using a neural network approach (Multilayer Perceptron Network, SPSS v24.0©) combining clinical, radiomic and all features. It was then evaluated on the testing set and compared to the current available models using the Receiver Operative Characteristics and the C-Index. Two hundred and eighty patients were included, with a median age of 65.2 y (45.3-79.6), a mean PSA level of 9.5 ng/mL (1.04-63.0) and 79.6% of ISUP ≥ 2 tumors. LNI occurred in 51 patients (18.2%), with a median number of extracted nodes of 15 (10-19). In the testing set, with their respective cutoffs applied, the Partin, Roach, Yale, MSKCC, Briganti 2012 and 2017 models resulted in a C-Index of 0.71, 0.66, 0.55, 0.67, 0.65 and 0.73, respectively, while our proposed combined model resulted in a C-Index of 0.89 in the testing set. Radiomic features extracted from the preoperative MRI scans and combined with clinical features through a neural network seem to provide added predictive performance compared to state of the art models regarding LNI risk prediction in PCa.

Sedimentological and geochemical data in bed sediments from a tropical river-estuary system impacted by a developing megacity, Ho Chi Minh City - Vietnam.

Sedimentological and geochemical data were obtained for bed sediments from a tropical estuary environment in Vietnam in October 2014, January 2016, and November 2016. The data include grain-size distribution, percentage of clay, silt and sand, percentage of organic matter, concentration of total particulate phosphorus (TPP), concentration of particulate inorganic phosphorus (PIP), concentration of particulate organic phosphorus (POP), percentage of total nitrogen (TN), percentage of total carbon (TC), trace metals concentrations (V, Cr, Co, Ni, Cu, Zn, As, Mo, Cd, Pb) and major elements (Al, Fe, Mn). Geochemical indexes (Enrichment factor EF and Geo-accumulation Index I-geo) and sediment quality guideline (mean Effect Range Median quotients) were calculated.