Three-Dimensional Deep Noninvasive Radiomics for the Prediction of Disease Control in Patients With Metastatic Urothelial Carcinoma treated With Immunotherapy

Rundo, Francesco; Bersanelli, Melissa; Urzia, Valeria; Friedlaender, Alex; Cantale, Ornella; Calcara, Giacomo; Addeo, Alfredo; Banna, Giuseppe Luigi

doi:10.1016/j.clgc.2021.03.012

Cited by 15 publications

(19 citation statements)

References 43 publications

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“…Because there are currently no biomarkers that can be used to identify individuals who are candidates for this treatment, researchers have turned to artificial intelligence models [ 130 ]. Convolutional neural networks and radiomics have thus been used to investigate immunotherapy patients who have progressed after receiving first-line platinum-based chemotherapy, to identify those with a high possibility of responding (complete, partial response, or stable disease), from those who were likely to manifest disease progression; the proposed model demonstrated a 92% accuracy in distinguishing between the two categories of patients [ 131 ].…”

Section: Artificial Intelligencementioning

confidence: 99%

Computed Tomography Urography: State of the Art and Beyond

et al. 2023

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Computed Tomography Urography (CTU) is a multiphase CT examination optimized for imaging kidneys, ureters, and bladder, complemented by post-contrast excretory phase imaging. Different protocols are available for contrast administration and image acquisition and timing, with different strengths and limits, mainly related to kidney enhancement, ureters distension and opacification, and radiation exposure. The availability of new reconstruction algorithms, such as iterative and deep-learning-based reconstruction has dramatically improved the image quality and reducing radiation exposure at the same time. Dual-Energy Computed Tomography also has an important role in this type of examination, with the possibility of renal stone characterization, the availability of synthetic unenhanced phases to reduce radiation dose, and the availability of iodine maps for a better interpretation of renal masses. We also describe the new artificial intelligence applications for CTU, focusing on radiomics to predict tumor grading and patients’ outcome for a personalized therapeutic approach. In this narrative review, we provide a comprehensive overview of CTU from the traditional to the newest acquisition techniques and reconstruction algorithms, and the possibility of advanced imaging interpretation to provide an up-to-date guide for radiologists who want to better comprehend this technique.

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Section: Artificial Intelligencementioning

confidence: 99%

Computed Tomography Urography: State of the Art and Beyond

et al. 2023

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“…Since the first studies evaluating radiomics to predict the immune microenvironment in 2017, 55 an increasing number of radiomic studies have confirmed the potential of imaging biomarkers for use in immuno-oncology (table 1). Promising results have been obtained using a wide variety of approaches on many different tumors types, such as lung cancers, [56][57][58][59][60][61] head and neck cancers, 62 melanoma, 56 63 64 urothelial [65][66][67] and renal cancers, 68 with either CT scans, 56-58 69 PET-CTs, 60 70 or MRIs 71 72 (figure 1).…”

Section: Imaging To Increase Knowledge To Predict Responses and To Gu...mentioning

confidence: 99%

Imaging approaches and radiomics: toward a new era of ultraprecision radioimmunotherapy?

Sun

Henry

Laville

et al. 2022

J Immunother Cancer

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Strong rationale and a growing number of preclinical and clinical studies support combining radiotherapy and immunotherapy to improve patient outcomes. However, several critical questions remain, such as the identification of patients who will benefit from immunotherapy and the identification of the best modalities of treatment to optimize patient response. Imaging biomarkers and radiomics have recently emerged as promising tools for the non-invasive assessment of the whole disease of the patient, allowing comprehensive analysis of the tumor microenvironment, the spatial heterogeneity of the disease and its temporal changes. This review presents the potential applications of medical imaging and the challenges to address, in order to help clinicians choose the optimal modalities of both radiotherapy and immunotherapy, to predict patient’s outcomes and to assess response to these promising combinations.

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“…Radiomics has been reported as a promising approach to predict the response and survival outcomes in patients with NSCLC and melanoma receiving ICIs [ 109 , 110 ]. Three retrospective analyses investigated radiomics from baseline contrast-enhanced computed tomography (CT) images in patients with mUC receiving anti-PDL1 or anti-PD1 monotherapy [ 111 , 112 , 113 ].…”

Section: Radiomicsmentioning

confidence: 99%

“…Artificial intelligence algorithms may also allow us to combine the information obtained by the image features with other clinical and laboratory prognostic factors, thus increasing the diagnostic accuracy of predictive models [ 112 , 113 ].…”

Section: Radiomicsmentioning

confidence: 99%

Prognostic and Predictive Factors in Advanced Urothelial Carcinoma Treated with Immune Checkpoint Inhibitors: A Review of the Current Evidence

Rebuzzi

Banna

Murianni

et al. 2021

Cancers

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In recent years, the treatment landscape of urothelial carcinoma has significantly changed due to the introduction of immune checkpoint inhibitors (ICIs), which are the standard of care for second-line treatment and first-line platinum-ineligible patients with advanced disease. Despite the overall survival improvement, only a minority of patients benefit from this immunotherapy. Therefore, there is an unmet need to identify prognostic and predictive biomarkers or models to select patients who will benefit from ICIs, especially in view of novel therapeutic agents. This review describes the prognostic and predictive role, and clinical readiness, of clinical and tumour factors, including new molecular classes, tumour mutational burden, mutational signatures, circulating tumour DNA, programmed death-ligand 1, inflammatory indices and clinical characteristics for patients with urothelial cancer treated with ICIs. A classification of these factors according to the levels of evidence and grades of recommendation currently indicates both a prognostic and predictive value for ctDNA and a prognostic relevance only for concomitant medications and patients’ characteristics.

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Three-Dimensional Deep Noninvasive Radiomics for the Prediction of Disease Control in Patients With Metastatic Urothelial Carcinoma treated With Immunotherapy

Cited by 15 publications

References 43 publications

Computed Tomography Urography: State of the Art and Beyond

Computed Tomography Urography: State of the Art and Beyond

Imaging approaches and radiomics: toward a new era of ultraprecision radioimmunotherapy?

Prognostic and Predictive Factors in Advanced Urothelial Carcinoma Treated with Immune Checkpoint Inhibitors: A Review of the Current Evidence

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