Rotating frame relaxation imaging of prostate cancer: Repeatability, cancer detection, and Gleason score prediction

2015 ◽  
Vol 75 (1) ◽  
pp. 337-344 ◽  
Author(s):  
Ivan Jambor ◽  
Marko Pesola ◽  
Pekka Taimen ◽  
Harri Merisaari ◽  
Peter J. Boström ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
Rotating Frame ◽  
Rotating Frame Relaxation

scholarly journals Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet

2019 ◽  
Vol 38 (11) ◽  
pp. 2496-2506 ◽  
Author(s):  
Ruiming Cao ◽  
Amirhossein Mohammadian Bajgiran ◽  
Sohrab Afshari Mirak ◽  
Sepideh Shakeri ◽  
Xinran Zhong ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
Prostate Cancer Detection

scholarly journals Multiparametric MR imaging of peripheral zone prostate cancer: effect of postbiopsy haemorrhage on cancer detection according to Gleason score and tumour volume

2018 ◽  
pp. 20180001 ◽  
Author(s):  
Sung Il Jung ◽  
Sung Il Jung ◽  
Hae Jeong Jeon ◽  
Hee Sun Park ◽  
Mi Hye Yu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mr Imaging ◽  
Gleason Score ◽  
Cancer Detection ◽  
Peripheral Zone ◽  
Tumour Volume

Targeted Biopsy of the Prostate: The Impact of Color Doppler Imaging and Elastography on Prostate Cancer Detection and Gleason Score

Urology ◽  
2007 ◽  
Vol 70 (6) ◽  
pp. 1136-1140 ◽  
Author(s):  
Eric D. Nelson ◽  
Craig B. Slotoroff ◽  
Leonard G. Gomella ◽  
Ethan J. Halpern
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
Color Doppler ◽  
Color Doppler Imaging ◽  
Doppler Imaging ◽  
Targeted Biopsy ◽  
Prostate Cancer Detection ◽  
The Impact

scholarly journals Extended 14-core schematic diagram mapping prostate biopsy increases both the cancer detection rate and the accuracy of Gleason Score

10.52786/a.11 ◽  
2020 ◽  
Vol 41 (2) ◽  
pp. 75-80
Author(s):  
Krittin Naravejsaku ◽  
Bhapapak Na song-kha ◽  
Wiroj Raksakul ◽  
Thitiwat Wongumpornwat ◽  
Umaphorn Nuanthaisong
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
Prostate Biopsy ◽  
Detection Rate ◽  
Elevated Serum ◽  
Cancer Detection Rate ◽  
Schematic Diagram ◽  
Group I ◽  
Group Ii

Objective: To evaluate the effectiveness of extended 14-core schematic diagram mapping prostate biopsy for improving the cancer detection rate (CDR) and accuracy of Gleason score. Material and Method: This study included 184 patients who underwent transrectal ultrasound (TRUS)-guided lateral sextant biopsy (group I) and 196 patients who underwent extended 14-core biopsy (group II). Inclusion criteria for prostate biopsy were elevated serum prostate-specific antigen (PSA) levels (>4.0 ng/ml) and/or suspicious digital rectal examination (DRE). Results: Median patient age was 69.68 years (±7.89) and 70.07 years (±8.83) for group I and II, respectively. Median pre-biopsy PSA was 18.04 (range: 8.42-22.35) and 15.83 ng/ml (range: 6.54-21.72) for group I and II. Out of the first group, 65 (35.3%) patients had prostate cancer, whereas 78 (40.0%) patients of group II had cancers. The overall cancer detection rate was significantly higher in group II (40.0%) than group I (35.3%), p=0.034, and in particular showed a significant increase in the cancer detection rate in the subgroup with PSA level between 4-10 ng/ml. Moreover, rising Gleason sum after radical prostatectomy was 1 in 3 (11.1%) patients and 2 in 1 (3.7%) patient. Conclusion: Extended 14-core schematic diagram mapping prostate biopsy significantly increased the cancer detection rate of prostate cancer and increased the accuracy of biopsy Gleason score. Thus, schematic diagram mapping prostate biopsy should be the standard ultrasound guided prostate biopsy in our institute for increasing the cancer detection rate and also for planning treatments.

scholarly journals MRI-Targeted Biopsies versus Systematic Transrectal Ultrasound Guided Biopsies for the Diagnosis of Localized Prostate Cancer in Biopsy Naïve Men

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Alexandre Peltier ◽  
Fouad Aoun ◽  
Marc Lemort ◽  
Félix Kwizera ◽  
Marianne Paesmans ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
Detection Rate ◽  
Transrectal Ultrasound ◽  
Cancer Detection Rate ◽  
Targeted Biopsy ◽  
Clinically Significant ◽  
A Prospective Study ◽  
Significant Disease

Introduction. To compare, in the same cohort of men, the detection of clinically significant disease in standard (STD) cores versus multiparametric magnetic resonance imaging (mpMRI) targeted (TAR) cores.Material and Methods. A prospective study was conducted on 129 biopsy naïve men with clinical suspicion of prostate cancer. These patients underwent prebiopsy mpMRI with STD systematic biopsies and TAR biopsies when lesions were found. The agreement between the TAR and the STD protocols was measured using Cohen’s kappa coefficient.Results. Cancer detection rate of MRI-targeted biopsy was 62.7%. TAR protocol demonstrated higher detection rate of clinically significant disease compared to STD protocol. The proportion of cores positive for clinically significant cancer in TAR cores was 28.9% versus 9.8% for STD cores (P<0.001). The proportion of men with clinically significant cancer and the proportion of men with Gleason score 7 were higher with the TAR protocol than with the STD protocol (P=0.003;P=0.0008, resp.).Conclusion. mpMRI improved clinically significant prostate cancer detection rate compared to STD protocol alone with less tissue sampling and higher Gleason score. Further development in imaging as well as multicentre studies using the START recommendation is needed to elucidate the role of mpMRI targeted biopsy in the management of prostate cancer.

1486: Prostate Cancer Detection Rate and Changes in Gleason Score in Regard to Patients Age: 12 Year Experience

2006 ◽  
Vol 175 (4S) ◽  
pp. 480-480
Author(s):  
Jasmin Bektic ◽  
Andreas P. Berger ◽  
Alexandre E. Pelzer ◽  
Georg Bartsch ◽  
Wolfgang Horninger
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
Detection Rate ◽  
Cancer Detection Rate ◽  
Prostate Cancer Detection

1012 PROSTATE CANCER DETECTION RATE AND CHANGES IN GLEASON SCORE IN REGARD TO PATIENTS AGE: 12 YEAR EXPERIENCE

2007 ◽  
Vol 6 (2) ◽  
pp. 275
Author(s):  
J. Bektic ◽  
A.E. Pelzer ◽  
N. Leonhartsberger ◽  
G.E. Pinggera ◽  
G. Bartsch ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
Detection Rate ◽  
Cancer Detection Rate ◽  
Prostate Cancer Detection

A multivariate index analyte (MIA) assay for differentiating aggressive from nonaggressive prostate cancer.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. e588-e588
Author(s):  
Douglas Campbell ◽  
Vicki Velonas ◽  
Julie T Soon ◽  
Sandra Wissmueller ◽  
David Gillatt ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Cancer Detection ◽  
The Other ◽  
P Value ◽  
Serum Samples ◽  
Protein Marker ◽  
Aggressive Prostate Cancer ◽  
Prostate Cancer Detection ◽  
Aggressive Cancer

e588 Background: Biomarkers that can assist clinicians and patients to proceed when PSA and /or DRE are equivocal. Such biomarkers should establish both sensitivity and specificity for prostate cancer detection in order to improve go-forward decisions to perform prostate biopsy. Following the successful use of a three-protein marker panel to increase the specificity of prostate cancer detection1 we have now used the same technology to examine whether an MIA assay can assist in differentiating aggressive from non-aggressive cancer in prostate cancer patients. Methods: Samples from patients with either aggressive prostate cancer or non- aggressive prostate cancer were obtained from two sources. The cohort criteria comprised of serum samples where blood was drawn from patients with adenocarcinoma and a PSA greater than or equal to 2ng/mL. All men were Caucasian with the exception of 3 who were African American. Non-aggressive prostate cancer was defined as having a Gleason score of 6 (n = 35) and aggressive prostate cancer was characterized as Gleason score 7 and above (n = 69). Biomarker levels were determined using a plate based ELISA for GPC-12 and a bead-based MIA assay for the other markers. Results: By using biostatistical analysis (Simplicity Bio, Switzerland) two models were identified that were able to differentiate between aggressive and non-aggressive prostate cancer. One consisted of a combination of 5 analytes and the other used 6 analytes. Model 1 containing PSA and GPC-1 plus 4 analytes produced a combined sensitivity of 81% and specificity of 78% (AUC 0.81). The second model comprising of GPC-1 with an additional 4 analytes achieved a sensitivity of 72% with a specificity of 76% (AUC 0.76). Both models had a p value of less than 0.05. By itself PSA was a poor predictor of prostate cancer with a sensitivity of 58% and specificity of 43% (AUC 0.55). Conclusions: The analytes identified by the two statistical models demonstrate potential utility for using the combined markers as a new means of differentiating aggressive prostate cancer from non-aggressive cancer. An additional study to further validate these models is currently being constructed.

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