Prostate cancer discrimination in the peripheral zone with a reduced field-of-view T2-mapping MRI sequence

In the prostate, water diffusion is faster when moving parallel to duct and gland walls than when moving perpendicular to them, but these data are not currently utilized in multiparametric magnetic resonance imaging (mpMRI) for prostate cancer (PCa) detection. Diffusion tensor imaging (DTI) can quantify the directional diffusion of water in tissue and is applied in brain and breast imaging. Our aim was to determine whether DTI may improve PCa detection. We scanned patients undergoing mpMRI for suspected PCa with a DTI sequence. We calculated diffusion metrics from DTI and diffusion weighted imaging (DWI) for suspected lesions and normal-appearing prostate tissue, using specialized software for DTI analysis, and compared predictive values for PCa in targeted biopsies, performed when clinically indicated. DTI scans were performed on 78 patients, 42 underwent biopsy and 16 were diagnosed with PCa. The median age was 62 (IQR 54.4–68.4), and PSA 4.8 (IQR 1.3–10.7) ng/mL. DTI metrics distinguished PCa lesions from normal tissue. The prime diffusion coefficient (λ1) was lower in both peripheral-zone (p < 0.0001) and central-gland (p < 0.0001) cancers, compared to normal tissue. DTI had higher negative and positive predictive values than mpMRI to predict PCa (positive predictive value (PPV) 77.8% (58.6–97.0%), negative predictive value (NPV) 91.7% (80.6–100%) vs. PPV 46.7% (28.8–64.5%), NPV 83.3% (62.3–100%)). We conclude from this pilot study that DTI combined with T2-weighted imaging may have the potential to improve PCa detection without requiring contrast injection.

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Is PSA density of the peripheral zone as a useful predictor for prostate cancer in patients with gray zone PSA levels?

BMC Cancer ◽

10.1186/s12885-021-08216-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jaegeun Lee ◽

Seung Woo Yang ◽

Long Jin ◽

Chung Lyul Lee ◽

Ji Yong Lee ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Diagnosis ◽

Prostate Biopsy ◽

Peripheral Zone ◽

Transitional Zone ◽

Gray Zone ◽

Prostate Cancer Diagnosis ◽

Psa Density ◽

Diagnosis Group ◽

Predictive Rate

Abstract Background Serum prostate-specific antigen (PSA) is widely used in screening tests for prostate cancer. As the low specificity of PSA results in unnecessary and invasive prostate biopsies, we evaluated the clinical significance of various PSAs and PSA density (PSAD) related to peripheral zones in patients with gray zone PSA level (4–10 ng/mL). Methods A total of 1300 patients underwent transrectal ultrasonography-guided prostate biopsy from 2014 to 2019. Among them, 545 patients in the gray zone were divided into the prostate cancer diagnosis group and the non-prostate cancer diagnosis group, and PSA, relative extra transitional zone PSA (RETzPSA), estimated post holmium laser enucleation of the prostate PSA (EPHPSA), PSAD, peripheral zone PSA density (PZPSAD) and extra-transitional zone density (ETzD) were compared and analyzed using receiver-operating characteristics (ROC) analysis after 1:1 matching using propensity score. Results Area under the ROC curve values of PSA, EPHPSA, RETzPSA, PSA density, ETzD, and PZPSAD were 0.553 (95% CI: 0.495–0.610), 0.611 (95% CI: 0.554–0.666), 0.673 (95% CI: 0.617–0.725), 0.745 (95% CI: 0.693–0.793), 0.731 (95% CI: 0.677–0.780) and 0.677 (95% CI: 0.611–0.719), respectively. PSAD had 67.11% sensitivity, 71.71% specificity, and 70.34% positive predictive rate at 0.18 ng/mL/cc. ETzD had 69.08% sensitivity, 64.47% specificity, and 66.04% positive predictive rate at 0.04 ng/mL/cc. When the cut-off value of PSAD was increased to 0.18 ng/mL/cc, the best results were obtained with an odds ratio of 5.171 (95% CI: 3.171–8.432), followed by ETzD with 4.054 (95% CI: 2.513–6.540). Conclusions These results suggested that volume-adjusted parameters (ETzD and PSAD) might be more sensitive and accurate than various PSA in gray zone patients who required prostate biopsy to reduce unnecessary biopsy.

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A fully automatic computer aided diagnosis system for peripheral zone prostate cancer detection using multi-parametric magnetic resonance imaging

Computerized Medical Imaging and Graphics ◽

10.1016/j.compmedimag.2015.09.001 ◽

2015 ◽

Vol 46 ◽

pp. 219-226 ◽

Cited By ~ 30

Author(s):

Valentina Giannini ◽

Simone Mazzetti ◽

Anna Vignati ◽

Filippo Russo ◽

Enrico Bollito ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Prostate Cancer ◽

Cancer Detection ◽

Peripheral Zone ◽

Resonance Imaging ◽

Automatic Computer ◽

Prostate Cancer Detection ◽

Computer Aided ◽

Fully Automatic ◽

Aided Diagnosis

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Predicting the aggressiveness of peripheral zone prostate cancer using a fractional order calculus diffusion model

European Journal of Radiology ◽

10.1016/j.ejrad.2021.109913 ◽

2021 ◽

Vol 143 ◽

pp. 109913

Author(s):

Zhihua Li ◽

Guangyu Dan ◽

Vikram Tammana ◽

Scott Johnson ◽

Zheng Zhong ◽

...

Keyword(s):

Prostate Cancer ◽

Diffusion Model ◽

Fractional Order ◽

Peripheral Zone ◽

Fractional Order Calculus

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Prostate Cancer: Comparison of Dynamic Contrast-Enhanced MRI Techniques for Localization of Peripheral Zone Tumor

American Journal of Roentgenology ◽

10.2214/ajr.12.9737 ◽

2013 ◽

Vol 201 (3) ◽

pp. W471-W478 ◽

Cited By ~ 38

Author(s):

Andrew B. Rosenkrantz ◽

Amy Sabach ◽

James S. Babb ◽

Brent W. Matza ◽

Samir S. Taneja ◽

...

Keyword(s):

Prostate Cancer ◽

Peripheral Zone ◽

Dynamic Contrast Enhanced Mri ◽

Dynamic Contrast Enhanced ◽

Enhanced Mri ◽

Contrast Enhanced ◽

Contrast Enhanced Mri

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Prostate cancer topography and tumour conspicuity on multiparametric magnetic resonance imaging: A systematic review and meta-analysis

10.7244/cmj.2021.04.001.2 ◽

2021 ◽

Author(s):

Pranav Satish ◽

Alex Freeman ◽

Daniel Kelly ◽

Alex Kirkham ◽

Clement Orczyk ◽

...

Keyword(s):

Prostate Cancer ◽

Systematic Review ◽

Meta Analysis ◽

Peripheral Zone ◽

Transitional Zone ◽

Dynamic Contrast Enhancement ◽

Significant Difference ◽

Prisma Statement ◽

Tumour Location ◽

The Relationship

Introduction The implications of tumour location on mpMRI conspicuity are not fully understood. Identifying topographical correlates that influence conspicuity may improve outcomes. Here, we present the first systematic review and meta-analysis describing the effect of tumour location on prostate cancer conspicuity on mpMRI. Methods Medline, PubMed, EMBASE and Cochrane databases were systematically searched and results were assessed as per the PRISMA statement. Differential tumour conspicuity on mpMRI was compared between cancers in the peripheral zone (PZ), transitional zone (TZ), base, apex, anterior and posterior. Meta-analysis was conducted to compare diagnostic odds ratios (DOR) of mpMRI detection for tumours in the PZ and TZ. PROSPERO registration: CRD42021228087. Results Thematic synthesis showed apical and basal tumours had reduced conspicuity compared to mid-gland tumours. Cancer in the TZ demonstrated increased conspicuity on T2-weighted imaging, whilst PZ cancers had higher conspicuity on diffusion-weighted and dynamic contrast enhancement imaging. mpMRI had better diagnostic accuracy for PZ lesions, albeit higher specificity for TZ lesions. Meta-analysis showed an increased DOR for PZ tumours (OR: 7.206 [95% CI: 4.991;10.403], compared to TZ (OR: 5.310 [95% CI: 3.082; 9.151]). However, the test for subgroup differences was not significant (p = 0.2743). Conclusions Cancer in the apex or base of the prostate may be less conspicuous than mid-gland tumours. Similarly, TZ cancer appears to have reduced conspicuity compared to PZ cancer, however, meta-analysis did not show a significant difference between DOR. Future larger studies with prospective datasets are required to clarify the relationship between tumour position and conspicuity.

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Hormonal therapy of prostate cancer

Oxford Textbook of Endocrinology and Diabetes ◽

10.1093/med/9780199235292.003.1149 ◽

2011 ◽

pp. 1622-1634

Author(s):

Ciara O’Hanlon Brown ◽

Jonathan Waxman

Keyword(s):

Prostate Cancer ◽

Androgen Receptor ◽

Specific Antigen ◽

Intraepithelial Neoplasia ◽

Peripheral Zone ◽

Molecular Feature ◽

Molecular Defects ◽

Psa Testing ◽

Seer Data ◽

Prostate Cancers

Prostate cancer is the most common cancer to effect men and the second most common cause of cancer-related death. Premalignant change or prostatic intraepithelial neoplasia has been detected within the prostate glands of men under 30 years of age. The incidence of prostate cancer remains negligible until men reach their 40s from whence it rises steadily and by 80 years 70% of men have detectable tumours at autopsy (1). A majority of prostate cancers arise from the peripheral zone of the prostate and rarely cause obstructive symptoms. Consequently, prostate cancers have historically presented late, with symptoms of metastatic disease. The advent of prostate-specific antigen (PSA) testing has produced a stage shift so that at present over 90% of prostate cancers are diagnosed as organ-confined disease. PSA diagnosis has unmasked a subset of prostate tumours that exhibit an indolent growth pattern and appear destined to remain organ-confined tumours the patient dies with, and not from. US SEER data estimates a 50-year-old man has a 42% chance of developing prostate cancer but only a 3.6% chance of dying from the disease. Features, either clinical or molecular, which would allow clinicians to clearly differentiate indolent from aggressive disease while still at the organ-confined stage, have yet to be identified (1). Adenocarcinoma is the predominant histological subtype of prostate cancer, accounting for 95% of tumours. Prostatic adenocarcinomas arise from androgen receptor-positive epithelial cells. On histological examination, prostate cancers appear multifocal and demonstrate heterogeneity both within individual tumours and across populations. This has created an obstacle as researchers attempt to subclassify prostate cancer and identify the molecular defects responsible for driving prostatic carcinogenesis (1). Of prostate cancers, 80–90% are androgen receptor-positive at diagnosis (2), thus to date the androgen–androgen receptor axis is the sole molecular feature of this disease that has been successfully harnessed as a therapeutic target.

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