Radiomics in prostate cancer: an up-to-date review

Ferro, Matteo; Cobelli, O. De; Musi, Gennaro; Giudice, Francesco Del; Carrieri, Giuseppe; Busetto, Gian Maria; Falagario, Ugo Giovanni; Sciarra, Alessandro; Maggi, Martina; Crocetto, Felice; Barone, Biagio; Caputo, Vincenzo; Marchioni, M.; Lucarelli, Giuseppe; Imbimbo, Ciro; Mistretta, F.A.; Luzzago, Stefano; Vartolomei, Mihai Dorin; Cormio, Luigi; Autorino, Riccardo; Tătaru, Octavian Sabin

doi:10.1177/17562872221109020

Cited by 77 publications

(45 citation statements)

References 232 publications

(388 reference statements)

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“…In these cases, radical metastasectomy might be cardinal to lead to the best treatment, especially when atypical metastasis is found at imaging. 3 While new prognostic scores might become available with the advent of artificial intelligence and omics evolution, 4 this prognostic score could improve patient counseling and care, but external validation studies are required to confirm its clinical benefit and application.…”

Section: Discussionmentioning

confidence: 99%

“…Despite recent attempts at distinguishing renal cell tumor biology and metastasis heterogeneity at the molecular level, routinely assessed histopathological findings remain crucial for decision-making, selection of systemic therapies, and prediction of oncologic outcomes among patients with mRCC. [4][5][6][7][8] Multiple prognostic nomograms for survival among patients with mRCC have been described to date, but none have included histopathological features of the metastasis for prediction of oncologic outcomes. 9-14 Histological subtype, high tumor grade, coagulative necrosis, and sarcomatoid differentiation are wellestablished predictors of poor prognosis among patients with mRCC.…”

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confidence: 99%

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The Impact of Metastasis Histopathology on Oncologic Outcomes for Patients With Surgically Resected Metastatic Renal Cell Carcinoma

et al. 2023

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Purpose: Multiple prognostic models exist to assess survival among patients with metastatic clear cell renal cell carcinoma. However, the relative contribution of histopathological features of the metastasis has not been extensively studied. Herein, we compared models using clinical, primary tumor, and metastatic features to predict cancer-specific survival for patients with surgically resected metastatic clear cell renal cell carcinoma. Materials and Methods: We studied 266 patients who had undergone nephrectomy between 1970 and 2019, and who had a single site of metastasis completely resected. Two versions of the metastatic clear cell renal cell carcinoma score published by Leibovich et al were calculated, using grade and necrosis from the primary tumor and using grade and necrosis from the metastasis. Predictive abilities of these 2 versions and a third model that included metastatic features only were compared using c-indexes from Cox proportional hazards models. Results: A total of 197 patients died from renal cell carcinoma at a median of 2.3 years (IQR 1.1-4.5); median follow-up among survivors was 13.2 years (IQR 10.0-14.5). The Leibovich score using grade and necrosis from the metastasis (c[0.679) had similar predictive ability compared to the original Leibovich score using grade and necrosis from the primary tumor (c[0.675). A third model (c[0.707) demonstrated that metastasectomy within 2 years after nephrectomy, presence of bone metastasis, high grade, and sarcomatoid differentiation in the metastasis were significantly associated with cancer-specific survival. Conclusions: Scoring algorithms calculated using histopathological features of the metastasis can be used to predict cancer-specific survival for patients with surgically resected metastatic clear cell renal cell carcinoma. These findings are of particular importance for instances when primary tumor histopathology is not readily available.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

The Impact of Metastasis Histopathology on Oncologic Outcomes for Patients With Surgically Resected Metastatic Renal Cell Carcinoma

et al. 2023

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“…Radiomics is also being investigated more often as a prognostic marker in other solid tumor; speci cally, Ki-67 has shown clinically signi cant outcomes in the diagnosis of bladder cancer [23], lung cancer [32], and breast cancer [33]. Non-invasive and capable of extracting more dimensional and abstract features, radiomics allows for the extraction of more concealed information in images than conventional radiologist observations, which can be used to construct predictive models analyzing the prognostic heterogeneity of PCa patients [34,35]. As a result, the ndings of our study have signi cant clinical implications, and the AUC of the prediction model constructed using Lasso and SVM is between 0.793 and 0.813 on the validation set.…”

Section: Discussionmentioning

confidence: 99%

Multiparametric MRI Radiomics in Prostate Cancer for Predicting Ki-67 Expression and Gleason Score: a Multicenter Retrospective Study

Zhou

Zhang

Guo

et al. 2023

Preprint

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Purpose Prostate cancers (PCas) with high Ki-67 expression and high Gleason Scores (GS) tend to have aggressive clinicopathological characteristics and a dismal prognosis. In order to predict the Ki-67 expression status and the GS in PCa, we sought to construct and verify MRI-based radiomics signatures.Methods and materials: We collected T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images from 170 PCa patients at three institutions and extracted 321 original radiomic features from each image modality. We used support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) logistic regression to select the most informative radiomic features and built predictive models using up sampling and feature selection techniques. Using receiver operating characteristic (ROC) analysis, the discriminating power of this feature was determined. Subsequent decision curve analysis (DCA) assessed the clinical utility of the radiomic features. The Kaplan-Meier (KM) test revealed that the radiomics-predicted Ki-67 expression status and GS were prognostic factors for PCa survival.Result The hypothesized radiomics signature, which included 15 and 9 selected radiomics features, respectively, was significantly correlated with pathological Ki-67 and GS outcomes in both the training and validation datasets. Areas under the curve (AUC) for the developed model were 0.813 (95% CI:0.681,0.930) and 0.793 (95% CI:0.621, 0.929) for the training and validation datasets, respectively, demonstrating discrimination and calibration performance. The model's clinical usefulness was verified by means of DCA. In both the training and validation sets, high Ki-67 expression and high GS predicted by radiomics using SVM models were substantially linked with poor overall survival (OS).Conclusions Both Ki-67 expression status and high GS correlate with PCa patient survival outcomes; therefore, the ability of the SVM classifier-based model to estimate Ki-67 expression status and the Lasso classifier-based model to assess high GS may enhance clinical decision making.

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“…The centralization of care could be the key to better disease management and advancements in the development of new techniques or protocols. In an era of great technological development, there is currently a lack of studies on innovative radiological scoring and the use of artificial intelligence and deep learning that could bring innovation to lymph node staging of PeCa as evidenced in other tumors of the urogenital system [83,84].…”

Section: Future Prospectivementioning

confidence: 99%

Organ-sparing treatment for T1 and T2 penile cancer: an updated literature review

Scornajenghi

Asero

Bologna

et al. 2023

Current Opinion in Urology

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Purpose of reviewPenile cancer (PeCa) is an orphan disease due to its rare incidence in high-income countries. Traditional surgical options for clinical T1--2 disease, including partial and total penectomy, can dramatically affect patient's quality of life and mental health status. In selected patients, organ-sparing surgery (OSS) has the potential to remove the primary tumor with comparable oncologic outcomes while maintaining penile length, sexual and urinary function. In this review, we aim to discuss the indications, advantages, and outcomes of various OSSs currently available for men diagnosed with PeCa seeking an organ-preserving option. Recent findingsPatient survival largely depends on spotting and treating lymph node metastasis at an early stage. The required surgical and radiotherapy skill sets cannot be expected to be available in all centers. Consequently, patients should be referred to high-volume centers to receive the best available treatments for PeCa. SummaryOSS should be used for small and localized PeCa (T1-T2) as an alternative to partial penectomy to preserve patient's quality of life while maintaining sexual and urinary function and penile aesthetics. Overall, there are different techniques that can be used with different response and recurrence rates. In case of tumor recurrence, partial penectomy or radical penectomy is feasible, without impacting overall survival.

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Radiomics in prostate cancer: an up-to-date review

Cited by 77 publications

References 232 publications

The Impact of Metastasis Histopathology on Oncologic Outcomes for Patients With Surgically Resected Metastatic Renal Cell Carcinoma

The Impact of Metastasis Histopathology on Oncologic Outcomes for Patients With Surgically Resected Metastatic Renal Cell Carcinoma

Multiparametric MRI Radiomics in Prostate Cancer for Predicting Ki-67 Expression and Gleason Score: a Multicenter Retrospective Study

Organ-sparing treatment for T1 and T2 penile cancer: an updated literature review

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