scholarly journals US lesion visibility predicts clinically significant upgrade of prostate cancer by systematic biopsy

2022 ◽  
Author(s):  
Nathan Velarde ◽  
Antonio C. Westphalen ◽  
Hao G. Nguyen ◽  
John Neuhaus ◽  
Katsuto Shinohara ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Medical Center ◽  
Conditional Logistic Regression ◽  
Academic Medical Center ◽  
Gleason Grade ◽  
Targeted Biopsy ◽  
Academic Medical ◽  
Visible Lesion ◽  
Clinically Significant ◽  
Systematic Biopsy

Abstract Purpose To identify predictors of when systematic biopsy leads to a higher overall prostate cancer grade compared to targeted biopsy. Methods and materials 918 consecutive patients who underwent prostate MRI followed by MRI/US fusion biopsy and systematic biopsies from January 2015 to November 2019 at a single academic medical center were retrospectively identified. The outcome was upgrade of PCa by systematic biopsy, defined as cases when systematic biopsy led to a Gleason Grade (GG) ≥ 2 and greater than the maximum GG detected by targeted biopsy. Generalized linear regression and conditional logistic regression were used to analyze predictors of upgrade. Results At the gland level, the presence of an US-visible lesion was associated with decreased upgrade (OR 0.64, 95% CI 0.44–0.93, p = 0.02). At the sextant level, upgrade was more likely to occur through the biopsy of sextants with MRI-visible lesions (OR 2.58, 95% CI 1.87–3.63, p < 0.001), US-visible lesions (OR 1.83, 95% CI 1.14–2.93, p = 0.01), and ipsilateral lesions (OR 3.89, 95% CI 2.36–6.42, p < 0.001). Conclusion Systematic biopsy is less valuable in patients with an US-visible lesion, and more likely to detect upgrades in sextants with imaging abnormalities. An approach that takes additional samples from regions with imaging abnormalities may provide analogous information to systematic biopsy.

scholarly journals Cognitive mpMRI/TRUS biopsy of the prostate with using strain elastography

2019 ◽  
pp. 100-108
Author(s):  
A. V. Vasilev ◽  
A. V. Mishchenko ◽  
R. A. Kadyrleev ◽  
A. S. Petrova ◽  
A. K. Nosov ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
False Positive ◽  
Detection Rate ◽  
Peripheral Zone ◽  
Additional Parameter ◽  
Gleason Grade ◽  
Targeted Biopsy ◽  
Fusion Biopsy ◽  
Clinically Significant ◽  
Systematic Biopsy

Purpose. To evaluate the effectiveness of prostate cancer detection with method of cognitive mpMRI/TRUS fusion biopsy using strain sonoelastography.Materials and methods. Cognitive transrectal fusion biopsy of prostate was performed in 32 patients. According to the data of a preliminary conducted mpMRI, 33 foci suspicious of prostate cancer were included (PIRADSv2 = 3–5). Before the biopsy, all patients underwent ultrasound planning using compression sonoelastography.Results. The overall sensitivity was 76% for the targeted biopsy, and 49% for systematic biopsy. The number of biopsy specimens with a clinically significant Gleason grade in the targeted biopsy group was 85% of all columns with cancer specimens, in the systematic biopsy group this number was 68%. On average, the Gleason grade after targeted biopsy was 7.5 ± 0.9, and it was 7.2 ± 0.9 in the columns after systematic biopsy. On average, the percentage of tumor in the columns after targeted biopsy was 72% ± 29% and it was 55% ± 35% in the columns after systematic biopsy. The false positive for mpMRI was 15%. The overall sensitivity for the strain sonoelastography was 69% in this study, clinically significant cancer was detected in 71% of all columns with cancer specimens. False positive for elastography was observed in 18% of cases.Conclusion. Comparing with systematic biopsy, cognitive mpMRI / TRUS fusion biopsy can improve the detection rate of clinically significant prostate cancer and reduce the number of detected cases of clinically insignificant cancer. In cases of a total or subtotal tumor lesion in the peripheral zone detected on mpMRI, it is possible to take fewer columns for morphological verification of the tumor. The use of compression sonoelastography as an additional parameter of navigation in cognitive mpMRI/TRUS fusion biopsy can be considered as a promising way to increase the detection rate of clinically significant prostate cancer.

scholarly journals Evaluation of the Ginsburg Scheme: Where Is Significant Prostate Cancer Missed?

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2502
Author(s):  
August Sigle ◽  
Cordula A. Jilg ◽  
Timur H. Kuru ◽  
Nadine Binder ◽  
Jakob Michaelis ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Detection ◽  
Logistic Regression Analysis ◽  
Anterior Region ◽  
Targeted Biopsy ◽  
Detection Rates ◽  
Clinically Significant ◽  
Systematic Biopsy

Background: Systematic biopsy (SB) according to the Ginsburg scheme (GBS) is widely used to complement MRI-targeted biopsy (MR-TB) for optimizing the diagnosis of clinically significant prostate cancer (sPCa). Knowledge of the GBS’s blind sectors where sPCa is missed is crucial to improve biopsy strategies. Methods: We analyzed cancer detection rates in 1084 patients that underwent MR-TB and SB. Cancerous lesions that were missed or underestimated by GBS were re-localized onto a prostate map encompassing Ginsburg sectors and blind-sectors (anterior, central, basodorsal and basoventral). Logistic regression analysis (LRA) and prostatic configuration analysis were applied to identify predictors for missing sPCa with the GBS. Results: GBS missed sPCa in 39 patients (39/1084, 3.6%). In 27 cases (27/39, 69.2%), sPCa was missed within a blind sector, with 17/39 lesions localized in the anterior region (43.6%). Neither LRA nor prostatic configuration analysis identified predictors for missing sPCa with the GBS. Conclusions: This is the first study to analyze the distribution of sPCa missed by the GBS. GBS misses sPCa in few men only, with the majority localized in the anterior region. Adding blind sectors to GBS defined a new sector map of the prostate suited for reporting histopathological biopsy results.

Hemodynamic Effects of Ketamine Compared With Propofol or Dexmedetomidine as Continuous ICU Sedation

2021 ◽  
pp. 106002802110510
Author(s):  
Evan Atchley ◽  
Eljim Tesoro ◽  
Robert Meyer ◽  
Alexia Bauer ◽  
Mark Pulver ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical ◽  
Clinically Significant ◽  
Critically Ill Adults ◽  
Icu Sedation ◽  
Ill Adults ◽  
Positive Effect

Background Ketamine has seen increased use for sedation in the intensive care unit. In contrast to propofol or dexmedetomidine, ketamine may provide a positive effect on hemodynamics. Objective The objective of this study was to compare the development of clinically significant hypotension or bradycardia (ie, negative hemodynamic event) between critically ill adults receiving sedation with ketamine and either propofol or dexmedetomidine. Methods This was a retrospective cohort study of adults admitted to an intensive care unit at an academic medical center between January 2016 and January 2021. Results Patients in the ketamine group (n = 78) had significantly less clinically significant hypotension or bradycardia compared with those receiving propofol or dexmedetomidine (n = 156) (34.6% vs 63.5%; P < 0.001). Patients receiving ketamine also experienced smaller degree of hypotension observed by percent decrease in mean arterial pressure (25.3% [17.4] vs 33.8% [14.5]; P < 0.001) and absolute reduction in systolic blood pressure (26.5 [23.8] vs 42.0 [37.8] mm Hg; P < 0.001) and bradycardia (15.5 [24.3] vs 32.0 [23.0] reduction in beats per minute; P < 0.001). In multivariate logistic regression modeling, receipt of propofol or dexmedetomidine was the only independent predictor of a negative hemodynamic event (odds ratio [OR]: 3.3, 95% confidence interval [CI], 1.7 to 6.1; P < 0.001). Conclusion and Relevance Ketamine was associated with less clinically relevant hypotension or bradycardia when compared with propofol or dexmedetomidine, in addition to a smaller absolute decrease in hemodynamic parameters. The clinical significance of these findings requires further investigation.

scholarly journals Disparities in PET imaging for prostate cancer at a tertiary academic medical center

2020 ◽  
pp. jnumed.120.251751
Author(s):  
Matthew D. Bucknor ◽  
Daphne Y. Lichtensztajn ◽  
Tracy K. Lin ◽  
Hala T. Borno ◽  
Scarlett L. Gomez ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Pet Imaging ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical

mpMRI-targeted biopsy versus systematic biopsy for clinically significant prostate cancer diagnosis

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Willy Baccaglini ◽  
Felipe P.A. Glina ◽  
Cristiano L. Pazeto ◽  
Wanderley M. Bernardo ◽  
Rafael Sanchez-Salas
Keyword(s):  
Prostate Cancer ◽  
Cancer Diagnosis ◽  
Targeted Biopsy ◽  
Prostate Cancer Diagnosis ◽  
Clinically Significant ◽  
Systematic Biopsy

scholarly journals Magnetic resonance/ultrasound fusion targeted biopsy of the prostate can be improved by adding systematic biopsy

2021 ◽  
Author(s):  
Victor Mihail Cauni ◽  
Dan Stanescu ◽  
Florin Tanase ◽  
Bogdan Mihai ◽  
Cristian Persu
Keyword(s):  
Prostate Cancer ◽  
Magnetic Resonance ◽  
Cancer Detection ◽  
Detection Rate ◽  
Specific Antigen ◽  
Cancer Detection Rate ◽  
Targeted Biopsy ◽  
Detection Rates ◽  
Clinically Significant ◽  
Systematic Biopsy

Aim: Magnetic resonance/ ultrasound fusion targeted biopsy (Tbs) is widely used for diagnosing prostate cancer (PCa). The aim of our study was to compare the cancer detection rate (CDR) and the clinically significant prostate cancer detection rate (csPCa) of the magnetic resonance/ultrasound fusion targeted biopsy with those of the standard systematic biopsy (Sbs) and of the combination of both techniques.Material and methods: A total of 182 patients underwent magnetic resonance/ultrasound fusion Tbs on the prostate for PCa suspicion based on multiparametric magnetic resonance imaging (mMRI) detection of lesions with PI-RADSv2 score ≥3. A total of 78 patients had prior negative biopsies. Tb was performed by taking 2-4 cores from each suspected lesion, followed by Sb with 12 cores. We evaluated the overall detection rate of PCa and clinically significant prostate cancer, defined as any PCa with Gleason score ≥3+4.Results: Median prostate specific antigen (PSA) level pre-biopsy was 7.4 ng/ml and median free-PSA/PSA ratio was 10.2%. Patient median age was 62 years old. PIRADSv2 score was 3 in 54 cases, 4 in 96 cases and 5 in 32 cases. PI-RADS-dependent detection rate of Tbs for scores 3, 4 and 5 was 25.9%, 65.6% and 84.4%, respectively, with csPCa detection rates of 24.1%, 54.2%, and 71.9%. Overall detection rate was 57.1% for Tbs, which increased to 60.4% by adding Sbs results. Detection rate for clinically significant prostate cancer (csPCa) was 48.4% and increased to 51.1% by adding Sbs. Overall detection rate for repeated biopsy was 50% and 68.3% for biopsy in naïve patients. Sbs detection rate was 55.5%, 8 patients having a negative biopsy on Tbs.Conclusions: When Tbs is considered due to a PI-RADS ≥3 lesion on mMRI, combined Tbs + Sbs increases the overall CDR and csPCa detection rates.

The best prostate biopsy sampling system—fusion and systematic biopsy: A single center experience

2021 ◽  
pp. 039156032110371
Author(s):  
Alfonso Califano ◽  
Alessandro Caputo ◽  
Antonio D’Antonio ◽  
Vincenzo Ciccone ◽  
Marco Fabiano ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Diagnostic Performance ◽  
Targeted Biopsy ◽  
Sampling System ◽  
Single Center Experience ◽  
Prostate Biopsies ◽  
Clinically Significant ◽  
Prostate Cancers ◽  
Systematic Biopsy

Background: Prostate cancer is the second most commonly diagnosed cancer in men. The diagnostic accuracy in prostate cancer can be increased by employing a preliminary multiparametric MRI followed by a fusion-targeted biopsy. Methods: To compare the diagnostic accuracy of fusion-targeted biopsy with the standard systematic biopsy in prostate cancer patients, we enrolled 139 patients on which we performed 139 prostate biopsies consisting of three targeted samples followed by 12 regular systematic samples. Based on histology, we analyzed the diagnostic performance of the two methods. Results: Both methods were equally good at detecting clinically significant cancer (83.3%, 50/60), while systematic biopsy detected more clinically insignificant cancers. However, the best diagnostic performance is obtained by combining the two methods. Conclusion: The two methods are best seen as synergistic, and the addition of fusion biopsy can be used to detect more clinically significant prostate cancers than systematic biopsy alone.

scholarly journals Clinically significant prostate cancer detection and segmentation in low-risk patients using a convolutional neural network on multi-parametric MRI

2020 ◽  
Vol 30 (12) ◽  
pp. 6582-6592
Author(s):  
Muhammad Arif ◽  
Ivo G. Schoots ◽  
Jose Castillo Tovar ◽  
Chris H. Bangma ◽  
Gabriel P. Krestin ◽  
...  
Keyword(s):  
Neural Network ◽  
Prostate Cancer ◽  
Active Surveillance ◽  
Deep Neural Network ◽  
Low Risk ◽  
Targeted Biopsy ◽  
Risk Patients ◽  
Clinically Significant ◽  
Systematic Biopsy ◽  
Group 1

Abstract Objectives To develop an automatic method for identification and segmentation of clinically significant prostate cancer in low-risk patients and to evaluate the performance in a routine clinical setting. Methods A consecutive cohort (n = 292) from a prospective database of low-risk patients eligible for the active surveillance was selected. A 3-T multi-parametric MRI at 3 months after inclusion was performed. Histopathology from biopsies was used as reference standard. MRI positivity was defined as PI-RADS score ≥ 3, histopathology positivity was defined as ISUP grade ≥ 2. The selected cohort contained four patient groups: (1) MRI-positive targeted biopsy-positive (n = 116), (2) MRI-negative systematic biopsy-negative (n = 55), (3) MRI-positive targeted biopsy-negative (n = 113), (4) MRI-negative systematic biopsy-positive (n = 8). Group 1 was further divided into three sets and a 3D convolutional neural network was trained using different combinations of these sets. Two MRI sequences (T2w, b = 800 DWI) and the ADC map were used as separate input channels for the model. After training, the model was evaluated on the remaining group 1 patients together with the patients of groups 2 and 3 to identify and segment clinically significant prostate cancer. Results The average sensitivity achieved was 82–92% at an average specificity of 43–76% with an area under the curve (AUC) of 0.65 to 0.89 for different lesion volumes ranging from > 0.03 to > 0.5 cc. Conclusions The proposed deep learning computer-aided method yields promising results in identification and segmentation of clinically significant prostate cancer and in confirming low-risk cancer (ISUP grade ≤ 1) in patients on active surveillance. Key Points • Clinically significant prostate cancer identification and segmentation on multi-parametric MRI is feasible in low-risk patients using a deep neural network. • The deep neural network for significant prostate cancer localization performs better for lesions with larger volumes sizes (> 0.5 cc) as compared to small lesions (> 0.03 cc). • For the evaluation of automatic prostate cancer segmentation methods in the active surveillance cohort, the large discordance group (MRI positive, targeted biopsy negative) should be included.

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