Combined Endorectal and Phased-Array MRI in the Prediction of Pelvic Lymph Node Metastasis in Prostate Cancer

Wang, Liang; Hricak, Hedvig; Kattan, Michael W.; Schwartz, Lawrence H.; Eberhardt, Steven C.; Chen, Hui Ni; Scardino, Peter T.

doi:10.2214/ajr.04.1682

Cited by 82 publications

(49 citation statements)

References 36 publications

(62 reference statements)

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“…Limitations in the accuracy of existing tools confirm that there is a need for novel biomarkers and imaging tools that are associated with the biologic behavior of PCa to enhance the predictive accuracy of current tools. 33,49,50 Catalogue of Available Predictive Tools Predicting prostate cancer on initial biopsy Table 1 shows nomograms for predicting PCa on initial biopsy. Eastham et al developed the first nomogram for predicting PCa on initial biopsy in men who had a c-index of 0.75.…”

Section: Suboptimal Predictive Accuracymentioning

confidence: 99%

An updated catalog of prostate cancer predictive tools

Shariat

Karakiewicz

Roehrborn

et al. 2008

Cancer

Self Cite

242

197

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Accurate estimates of risk are essential for physicians if they are to recommend a specific management to patients with prostate cancer. Accurate risk estimates also are required for clinical trial design to ensure that homogeneous, high-risk patient groups are used to investigate new cancer therapeutics. Using the MED-LINE database, a literature search was performed on prostate cancer predictive tools from January 1966 to July 2007. The authors recorded input variables, the prediction form, the number of patients used to develop prediction tools, the outcome being predicted, prediction tool-specific features, predictive accuracy, and whether validation was performed. Each prediction tool was classified into patient clinical disease state and the outcome being predicted. First, the authors described the criteria for evaluation (predictive accuracy, calibration, generalizability, head-to-head comparison, and level of complexity) and the limitations of current predictive tools. The literature search generated 109 published prediction tools, including only 68 that had undergone validation. An increasing number of predictive tools addressed important endpoints, such as disease recurrence, metastasis, and survival. Despite their limitations and the limitations of data, predictive tools are essential for individualized, evidence-based medical decision making. Moreover, the authors recommend wider adoption of risk-prediction models in the design and implementation of clinical trials. Among prediction tools, nomograms provide superior, individualized, disease-related risk estimations that facilitate management-related decisions. Nevertheless, many more predictive tools, comparisons between them, and improvements to existing tools are needed.

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Section: Suboptimal Predictive Accuracymentioning

confidence: 99%

An updated catalog of prostate cancer predictive tools

Shariat

Karakiewicz

Roehrborn

et al. 2008

Cancer

Self Cite

242

197

View full text Add to dashboard Cite

show abstract

“…They found that the 1997 Partin tables's AUC for predicting LNI was 0.818-0.837, while the 2001 tables AUC was 0.807. Work was completed in an effort to compare the AUC of MRI findings alone to the 2001 Partin table nomogram, in patients undergoing standard pelvic lymph node dissection (pLND) after RP [101]. On multivariate analysis, significant predictors of LNI were MRI findings (p = 0.002), PSA (p = 0.004), greatest percent of cancer in all biopsy cores (p = 0.007) and GS (p = 0.007).…”

Section: • Ecementioning

confidence: 99%

Risk Stratification of Prostate Cancer: Integrating Multiparametric MRI, Nomograms and Biomarkers

et al. 2016

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Accurate risk stratification of prostate cancer is achieved with a number of existing tools to ensure the identification of at-risk patients, characterization of disease aggressiveness, prediction of cancer burden and extrapolation of treatment outcomes for appropriate management of the disease. Statistical tables and nomograms using classic clinicopathological variables have long been the standard of care. However, the introduction of multiparametric MRI, along with fusion-guided targeted prostate biopsy and novel biomarkers, are being assimilated into clinical practice. The majority of studies to date present the outcomes of each in isolation. The current review offers a critical and objective assessment regarding the integration of multiparametric MRI and fusion-guided prostate biopsy with novel biomarkers and predictive nomograms in contemporary clinical practice.

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“…The sensitivity of MRI for LNM may be increased through use of these compounds, since they appear to permit detection of metastases in normal-sized nodes [73,75] . A study of 411 consecutive patients [32] showed that MRI was an independent statistically significant predictor of LNM Wang L. MRI and management of prostate cancer (P = 0.002), with sensitivity and specificity of 27.27% and 98.46%, respectively, and positive predictive value and negative predictive value of 50% and 95.99%, respectively. On multivariate analysis, prediction of lymph node status using the model that included all MRI variables (ECE, SVI, and LNM) along with the Partin nomogram results had a significantly greater AUC than the univariate model that included only MRI LNM findings (AUC = 0.892 vs 0.633, respectively, P < 0.01).…”

Section: Detection Of Lnmmentioning

confidence: 99%

“…Moreover, the nomograms are limited because they do not incorporate the results of imaging studies that could guide interventions to control local disease. Thus, a technique that noninvasively demonstrates the presence, extent, and biologic potential of prostate cancer could contribute incremental value to clinical nomograms and variables and make a substantial contribution to the decision-making process for individualized treatment [32,33] . Magnetic resonance imaging (MRI) is a technique which makes safer, more individualized therapies possible due to high spatial resolution, superior contrast resolution, multiplanar capability ( Figure 1) [34][35][36][37][38] .…”

Section: Introductionmentioning

confidence: 99%

Incremental value of magnetic resonance imaging in the advanced management of prostate cancer

Wang¹

2009

WJR

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Prostate cancer is a major public health burden throughout the world. The high incidence of prostate cancer, combined with earlier detection and downstaging at the time of diagnosis, and the slow natural progression and biological heterogeneity of the disease, has made its management a complex and controversial issue. There is growing demand for patient-specific therapies that can minimize treatment morbidity while maximizing treatment benefits. There are a number of clinical parameters and clinical nomograms to help with the choice of treatment. Magnetic resonance imaging (MRI) is a technique which makes safer, more individualized therapies possible due to high spatial resolution, superior contrast resolution, multiplanar capability, and a large field of view. Other MRI techniques such as MR spectroscopic imaging, dynamic contrast-enhanced MRI or perfusion MRI, and diffusion-weighted imaging complement MRI by reflecting tissue biochemistry, Brownian motion of water molecules, and capillary wall permeability, respectively. This editorial review highlights the incremental value of MRI in the advanced management of prostate cancer to non-invasively improve cancer staging, biologic potential, treatment planning, therapy response, local recurrence, and to guide target biopsy for clinical suspected cancer with previous negative biopsy. Finally, some future prospects for MRI in prostate cancer management are given.

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Combined Endorectal and Phased-Array MRI in the Prediction of Pelvic Lymph Node Metastasis in Prostate Cancer

Abstract: Incorporation of the Partin nomogram results and MRI findings regarding both extracapsular extension and seminal vesicle invasion improves the MR prediction of LNM in patients with prostate cancer.

Cited by 82 publications

References 36 publications

An updated catalog of prostate cancer predictive tools

An updated catalog of prostate cancer predictive tools

Risk Stratification of Prostate Cancer: Integrating Multiparametric MRI, Nomograms and Biomarkers

Incremental value of magnetic resonance imaging in the advanced management of prostate cancer

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