Cutoff Values of Prostate Imaging Reporting and Data System Version 2.1 Score in Men With Prostate-specific Antigen Level 4 to 10 ng/mL: Importance of Lesion Location

Chen, Yuanchong; Ruan, Mingjian; Zhou, Binyi; Hu, Xuege; Wang, Hao; Liu, Hua; Liu, Jia; Gang, Song Woon

doi:10.1016/j.clgc.2020.12.007

Cited by 13 publications

(17 citation statements)

References 30 publications

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“…Consistent with another model, ADC was useful for distinguishing TZ cancer from BPH 37 . However, ADC was found to affect diagnostic performance more than T2*, contradicting PI‐RADS 27,28,37 . We consider that this may mean that the importance of DWI images to diagnose TZ cancer might be underestimated in the PI‐RADS scoring system 37 .…”

Section: Discussionsupporting

confidence: 54%

“…21,23 According to the recommendations of PI-RADS, lesions in TZ are scored by T2WI and adjusted by DWI. 26,27 However, the described imaging findings of TZ cancers on T2W-MRI in PI-RADS v2 are subjective, and the reporting process is affected by almost inevitable variability among the different readers, making complete reproducibility impossible. 7,14 Consistent with a previous study, glandular BPH present as hyperintense nodules on T2-weighted imaging, a result of T2 shine-through effects, enabling it easy to differentiate from PCa and stromal BPH on T2*.…”

Section: Discussionmentioning

confidence: 99%

“…37 However, ADC was found to affect diagnostic performance more than T2*, contradicting PI-RADS. 27,28,37 We consider that this may mean that the importance of DWI images to diagnose TZ cancer might be underestimated in the PI-RADS scoring system. 37 Moreover, APTw values was first included in multivariate analyses for identifying TZ PCa and found to be useful as well.…”

Section: Discussionmentioning

confidence: 99%

“…24,25 PI-RADS v2.1 considers T2WI as the most important sequence for detection and characterization of TZ lesions, followed by DWI. 26,27 In theory, the apparent diffusion coefficient (ADC) and quantitative T2* provide important biophysical information that is related to TZ PCa.…”

mentioning

confidence: 99%

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Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate

Guo

Qin

et al. 2022

Magnetic Resonance Imaging

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Background There is an overlap comparing transition zone prostate cancer (TZ PCa) and benign prostatic hyperplasia (BPH) on T2‐weighted imaging (T2WI) and diffusion‐weighted imaging (DWI), creating additional challenges for assessment of TZ tumors on MRI. Purpose To evaluate whether amide proton transfer‐weighted (APTw) imaging provides new diagnostic ideas for TZ PCa. Study type Prospective. Population A total of 51 TZ PCa patients (age, 49–89), 44 stromal BPH (age, 57–92), and 45 glandular BPH patients (age, 56–92). Field Strength/Sequence A 3 T; T2WI turbo spin echo (TSE), quantitative T2*‐weighted imaging, DWI echo planar imaging, 3D APTw TSE. Assessment Differences in APTw, apparent diffusion coefficient (ADC), and T2* among three lesions were compared by one‐way analysis of variance (ANOVA). Regions of interest were drawn by two radiologists (X.Q.Z. and X.Y.Q., with 21 and 15 years of experience, respectively). Statistical Tests Multivariable logistic regression analyses; ANOVA with post hoc testing; receiver operator characteristic curve analysis; Delong test. Significance level: P < 0.05. Results APTw among TZ PCa, stromal BPH, and glandular BPH (3.48% ± 0.83% vs. 2.76% ± 0.49% vs. 2.72% ± 0.45%, respectively) were significantly different except between stromal BPH and glandular BPH (P > 0.99). Significant differences were found in ADC (TZ PCa 0.76 ± 0.16 × 10−3 mm2/sec vs. stromal BPH 0.91 ± 0.14 × 10−3 mm2/sec vs. glandular BPH 1.08 ± 0.18 × 10−3 mm2/sec) among three lesions. APTw (OR = 12.18, 11.80, respectively) and 1/ADC (OR = 703.87, 181.11, respectively) were independent predictors of TZ PCa from BPH and stromal BPH. The combination of APTw and ADC had better diagnostic performance in the identification of TZ PCa from BPH and stromal BPH. Data Conclusion APTw imaging has the potential to be of added value to ADC in differentiating TZ PCa from BPH and stromal BPH. Evidence Level 2 Technical Efficacy Stage 2

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Section: Discussionsupporting

confidence: 54%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate

Guo

Qin

et al. 2022

Magnetic Resonance Imaging

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“…Prostate-speci c antigen (PSA), a glycoprotein almost entirely secreted by the prostate gland, is considered to be one of the most reliable clinical biomarkers for the diagnosis, screening, and risk prediction of prostate cancer, and it was the rst tumor biomarker approved by the Food and Drug Administration (FDA) [3,4]. For healthy individuals, the serum PSA level is extremely low, about 4.0 ng•mL −1 and more than 10 ng•mL −1 , making them prone to developing prostate cancer [5][6][7]. erefore, the sensitive and accurate detection of serum PSA is critical for monitoring early asymptomatic prostate cancer, increasing the chances of cure and reducing its mortality.…”

Section: Introductionmentioning

confidence: 99%

A Sensitive Fluorescent Immunoassay for Prostate Specific Antigen Detection Based on Signal Amplify Strategy of Horseradish Peroxidase and Silicon Dioxide Nanospheres

Zhang

et al. 2022

Journal of Analytical Methods in Chemistry

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A simple, sensitive, and fluorescent immunoassay for the detection of prostate-specific antigen (PSA) based on horseradish peroxidase and silicon dioxide nanospheres as a signal amplification strategy has been described. In the design, the primary antibody (Ab1) of PSA was first immobilized on the 96-well plates via physical adsorption between polystyrene and hydrophobic groups of the antibody molecule. The silicon dioxide nanospheres (SiO2 NSs), with large surface area and good biocompatibility, were loaded with horseradish peroxidase (HRP) and horseradish peroxidase-labeled secondary antibodies (HRP-Ab2) as signal amplification systems. In the presence of PSA, a sandwich-type immunocomplex composed of Ab1-Ag-HRP-Ab2 had been formed. Fluorescence technology was employed to obtain the response signal of the immunoassay in the L-tyrosine and H2O2 systems. Experiment results showed that a strong and stable fluorescent signal at 416 nm (excitation wavelength: 325 nm) was observed, and the changes in fluorescent intensity were related to the levels of PSA. Under the optimal conditions, the relative fluorescence intensity was linear with the logarithm of PSA concentration from 0.03 to 100 ng·mL−1, with a detection limit of 0.01 ng·mL−1 (at a signal/noise ratio of 3). In contrast to other fluorescent immunoassays, the sandwich-type immunoreaction based on the high binding ELISA plates has the advantages of being simple, stable, and easy to operate, high selectivity, small sample quantity, etc., which can be widely used in the selective detection of a variety of targets, from DNA to proteins and small molecules. Such fluorescent immunoassays should be feasible for the fields of molecular diagnosis and other life science fields in the future.

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Deep‐Learning Models for Detection and Localization of Visible Clinically Significant Prostate Cancer on Multi‐Parametric MRI

Sun

Wu²,

Cui

et al. 2023

Magnetic Resonance Imaging

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BackgroundDeep learning for diagnosing clinically significant prostate cancer (csPCa) is feasible but needs further evaluation in patients with prostate‐specific antigen (PSA) levels of 4–10 ng/mL.PurposeTo explore diffusion‐weighted imaging (DWI), alone and in combination with T2‐weighted imaging (T2WI), for deep‐learning‐based models to detect and localize visible csPCa.Study TypeRetrospective.PopulationOne thousand six hundred twenty‐eight patients with systematic and cognitive‐targeted biopsy‐confirmation (1007 csPCa, 621 non‐csPCa) were divided into model development (N = 1428) and hold‐out test (N = 200) datasets.Field Strength/SequenceDWI with diffusion‐weighted single‐shot gradient echo planar imaging sequence and T2WI with T2‐weighted fast spin echo sequence at 3.0‐T and 1.5‐T.AssessmentThe ground truth of csPCa was annotated by two radiologists in consensus. A diffusion model, DWI and apparent diffusion coefficient (ADC) as input, and a biparametric model (DWI, ADC, and T2WI as input) were trained based on U‐Net. Three radiologists provided the PI‐RADS (version 2.1) assessment. The performances were determined at the lesion, location, and the patient level.Statistical TestsThe performance was evaluated using the areas under the ROC curves (AUCs), sensitivity, specificity, and accuracy. A P value <0.05 was considered statistically significant.ResultsThe lesion‐level sensitivities of the diffusion model, the biparametric model, and the PI‐RADS assessment were 89.0%, 85.3%, and 90.8% (P = 0.289–0.754). At the patient level, the diffusion model had significantly higher sensitivity than the biparametric model (96.0% vs. 90.0%), while there was no significant difference in specificity (77.0%. vs. 85.0%, P = 0.096). For location analysis, there were no significant differences in AUCs between the models (sextant‐level, 0.895 vs. 0.893, P = 0.777; zone‐level, 0.931 vs. 0.917, P = 0.282), and both models had significantly higher AUCs than the PI‐RADS assessment (sextant‐level, 0.734; zone‐level, 0.863).Data ConclusionThe diffusion model achieved the best performance in detecting and localizing csPCa in patients with PSA levels of 4–10 ng/mL.Evidence Level3Technical EfficacyStage 2

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Cutoff Values of Prostate Imaging Reporting and Data System Version 2.1 Score in Men With Prostate-specific Antigen Level 4 to 10 ng/mL: Importance of Lesion Location

Cited by 13 publications

References 30 publications

Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate

Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate

A Sensitive Fluorescent Immunoassay for Prostate Specific Antigen Detection Based on Signal Amplify Strategy of Horseradish Peroxidase and Silicon Dioxide Nanospheres

Deep‐Learning Models for Detection and Localization of Visible Clinically Significant Prostate Cancer on Multi‐Parametric MRI

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