Overview of current multiparametric magnetic resonance imaging approach in the diagnosis and staging of prostate cancer

Aydın, Hasan; Kızılgöz, Volkan; Tekin, Berna Okudan

doi:10.1016/j.kjms.2015.01.002

Cited by 10 publications

(8 citation statements)

References 72 publications

(368 reference statements)

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“…In recent years, mpMRI has been increasingly applied for the qualitative evaluation of PCa ( 26 , 27 ). The PI-RADS was proposed for better standardization of prostate MRI performance and image interpretation.…”

Section: Discussionmentioning

confidence: 99%

Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL

Huang

et al. 2022

Front. Oncol.

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PurposeTo investigate the predictive performance of the combined model by integrating clinical variables and radiomic features for the accurate detection of prostate cancer (PCa) in patients with prostate-specific antigen (PSA) serum levels of 4-10 ng/mL.MethodsA retrospective study of 136 males (mean age, 67.3 ± 8.4 years) with Prostate Imaging-Reporting and Data System (PI-RADS) v2.1 category ≤3 lesions and PSA serum levels of 4-10 ng/mL were performed. All patients underwent multiparametric MRI at 3.0T and transrectal ultrasound-guided systematic prostate biopsy in their clinical workup. Radiomic features were extracted from axial T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) maps of each patient using PyRadiomics. Pearson correlation coefficient (PCC) and recursive feature elimination (RFE) were implemented to identify the most significant radiomic features. Independent clinic-radiological factors were identified via univariate and multivariate regression analyses. Seven machine-learning algorithms were compared to construct a single-layered radiomic score (ie, radscore) and multivariate regression analysis was applied to construct the fusion radscore. Finally, the radiomic nomogram was further developed by integrating useful clinic-radiological factors and fusion radscore using multivariate regression analysis. The discriminative power of the nomogram was evaluated by area under the curve (AUC), DeLong test, calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC).ResultsThe transitional zone-specific antigen density was identified as the only independent clinic-radiological factor, which yielded an AUC of 0.592 (95% confidence interval [CI]: 0.527-0.657). The ADC radscore based on six features and Naive Bayes achieved an AUC of 0.779 (95%CI: 0.730-0.828); the T2WI radscore based on 13 features and Support Vector Machine yielded an AUC of 0.808 (95%CI: 0.761-0.855). The fusion radscore obtained an improved AUC of 0.844 (95%CI: 0.801-0.887), which was higher than the single-layered radscores (both P<0.05). The radiomic nomogram achieved the highest value among all models (all P<0.05), with an AUC of 0.872 (95%CI: 0.835-0.909). Calibration curve showed good agreement and DCA together with CIC confirmed the clinical benefits of the radiomic nomogram.ConclusionThe radiomic nomogram holds the potential for accurate and noninvasive identification of PCa in patients with PI-RADS ≤3 lesions and PSA of 4-10 ng/mL, which could reduce unnecessary biopsy.

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Section: Discussionmentioning

confidence: 99%

Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL

Huang

et al. 2022

Front. Oncol.

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“…Distant metastasis during tumor development is the most common reason for therapy failure in most PCa patients 86 . Metastasis requires cancer cells to circulate in the peripheral blood system in order to spread to distant organs with bone and blood metastasis prevailing 87,88 …”

Section: Urinary Liquid Biopsymentioning

confidence: 99%

“…The use of positron emission tomography (PET), magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound are the standard methods to diagnose PCa. However, these imaging technologies lack the capability to provide information about PCa types and stages, making it difficult to gain a complete assessment of the disease and selection of treatment 87 . As a result, there is a high demand for accurate PCa screening technologies.…”

Section: Nano Diagnosticsmentioning

confidence: 99%

“…86 Metastasis requires cancer cells to circulate in the peripheral blood system in order to spread to distant organs with bone and blood metastasis prevailing. 87,88 Castration-resistant PCa (CRPC) patients can have their androgen receptor (AR) and other associated genes measured at the subcellular level in CTCs from their peripheral blood. CTC enumeration has been studied extensively in both localized and metastatic prostate cancer.…”

Section: Circulating Tumor Cells (Ctcs)mentioning

confidence: 99%

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Nurturing the marriages of urinary liquid biopsies and nano‐diagnostics for precision urinalysis of prostate cancer

Liao

Chen

et al. 2023

Smart Medicine

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Prostate cancer remains the second-most common cancer diagnosed in men, despite the increasingly widespread use of serum prostate-specific antigen (PSA) screening. The controversial clinical implications and cost benefits of PSA screening have been highlighted due to its poor specificity, resulting in a high rate of overdiagnosis and underdiagnosis. Thus, the development of novel biomarkers for prostate cancer detection remains an intriguing challenge. Urine is emerging as a source for prostate cancer biomarker discovery.Currently, new urine biomarkers already outperform serum PSA in clinical diagnosis. Meanwhile, the advances in nanotechnology have provided a suite of diagnostic tools to study prostate cancer in more detail, sparking a new era of biomarker discoveries. In this review, we envision that future prostate cancer diagnosis will probably integrate multiplex nano-diagnostic approaches to detect novel urinary biomarkers. However, challenges remain in differentiating indolent from aggressive cancers to better inform treatment decisions, and clinical translation still needs to be overcome.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Multi-parametric magnetic resonance imaging (MP-MRI) can aid in the detection and characterization of PCa combining anatomical, functional and molecular imaging, providing improved support for decision-making regarding clinical treatment [4,5]. This MP-MRI approach includes the use of diffusion-weighted imaging (DWI) for studying the prostate.…”

Section: Introductionmentioning

confidence: 99%

Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue

et al. 2018

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Overview of current multiparametric magnetic resonance imaging approach in the diagnosis and staging of prostate cancer

Cited by 10 publications

References 72 publications

Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL

Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL

Nurturing the marriages of urinary liquid biopsies and nano‐diagnostics for precision urinalysis of prostate cancer

Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue

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