scholarly journals Tocilizumab effects in COVID-19 pneumonia: role of CT texture analysis in quantitative assessment of response to therapy

2021 ◽  
Author(s):  
Giorgio Maria Masci ◽  
Franco Iafrate ◽  
Fabio Ciccarelli ◽  
Giacomo Pambianchi ◽  
Valeria Panebianco ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Quantitative Assessment ◽  
Response To Therapy ◽  
Ct Texture Analysis

Predictive role of CT texture analysis in patients with metastatic urothelial cancer treated with PD-1/PD-L1 inhibitors.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 424-424
Author(s):  
Francesco Alessandrino ◽  
Rahul Gujrathi ◽  
Amin Nassar ◽  
Arwa Alzaghal ◽  
Arvind Ravi ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Urothelial Cancer ◽  
Stepwise Logistic Regression ◽  
Stepwise Logistic Regression Analysis ◽  
Contrast Enhanced Ct ◽  
Specificity And Sensitivity ◽  
Metastatic Urothelial Cancer ◽  
Ct Texture Analysis

424 Background: Reliable biomarkers to predict response of urothelial cancer to PD-1/PD-L1 inhibitors are still being investigated. Texture analysis represents underlying tumor heterogeneity and may serve as a predictor of response in urothelial cancer. The purpose of this study was to assess predictive ability of CT texture analysis for disease progression in patients with metastatic urothelial cancer treated with PD-1/PD-L1 inhibitor. Methods: In this IRB-approved HIPAA-compliant retrospective study, from total 93 consecutive patients with metastatic urothelial cancer treated with PD-1/PD-L1 inhibitors from 2013-2018, 43 patients with measurable disease per RECIST 1.1 criteria who had contrast-enhanced CT performed within three months after starting treatment were included. Progression-free survival was calculated based on serial follow-up CTs, and 11 patients without progression who did not reach 1 year follow-up were excluded. Texture features of measurable lesions on first follow-up CT were extracted (TexRAD Ltd, Feedback Plc, Cambridge, UK). Stepwise logistic regression analysis to identify patients who had progressive disease (PD) at 12 months was performed and performance assessed using receiver operator curves. Results: Of 32 included patients (24 men, 8 women; median age: 65 years) who had total 80 measurable lesions, 22 progressed by 12 months. On first follow-up CT, the entropy and mean of the lesions were higher (p = 0.04, p = 0.02) for patients with PD by 12 months. Calculated specificity and sensitivity of entropy (AUC = 0.79) were 90%, and 63%; of mean (AUC = 0.81) were 90%, and 50%. A predictive model including mean and entropy yielded 95% sensitivity, 80% specificity, 91% PPV, 89% NPV and 91% accuracy (AUC = 0.863) to identify patients with PD at 12 months. Conclusions: Texture analysis of CT performed within three months after starting PD-1/PD-L1 can help predict patients who progress by 12 months with high accuracy. Further studies investigating the correlation of texture analysis with survival endpoints may help validate the role of texture analysis as a biomarker to predict response to PD1/PD-L1 inhibitors.

Radiomics features on CT scans to predict response to HER2-targeted therapy of hepatic metastases from colorectal cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15086-e15086
Author(s):  
Valentina Giannini ◽  
Simone Mazzetti ◽  
Arianna Defeudis ◽  
Giovanni Cappello ◽  
Lorenzo Vassallo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Texture Analysis ◽  
Hepatic Metastases ◽  
Texture Features ◽  
Response To Therapy ◽  
Ct Scans ◽  
Imaging Biomarkers ◽  
Test Set ◽  
Extended Analysis ◽  
Ct Texture Analysis

e15086 Background: Metastatic Colorectal cancer (mCRC) is the 2nd cause of cancer death worldwide. Repeated cycles of therapies, combined with surgery in oligo-metastatic cases, are the therapeutic standard in mCRC. However, this strategy is seldom resolutive. Different lesions in in the same patient could have different responses to systemic therapy. Recently, CT texture analysis (CTTA) had been shown to potentially provide with prognostic and predictive markers, overcoming the limitations of biopsy sampling in defining tumor heterogeneity. The aim of this study is to use CT texture analysis (CTTA) to identify imaging biomarkers of HER2+ mCRC able to predict lesion response to therapy. Methods: The dataset is composed of 39 extended RAS wild type patients with amplified HER2 mCRC enrolled in the HERACLES trial (NCT03225937) that received either a lapatinib+trastuzumab treatment (n = 23) or a pertuzumab+ trastuzumab-emtansine treatment (n = 16). All patients underwent CT examination every 8 weeks, until disease progression. All mCRC on baseline CT were semi-automatically segmented and quantitative features extracted: size, mean, percentiles, 28 texture features. A logistic regression model was created using: (i) the whole dataset of mCRC as training and test set and (ii) 100 randomly generated training sets (with 70% of responder (R+) mCRC and an equal number of non-responder (R-) mCRC), and 100 test sets including the remaining mCRC. A mCRC was classified as R+ if size decreased (-10%) or was stable (±10%); as R- if size increased (+10%), during subsequent CT scans. Results: A total of 199 metastases were included (75R+ and 124R-). The training set was composed of 53R+ and 53R- mCRC and the test set of 22R+ and 71R- mCRC. Using the whole dataset, the model reached an AUC = 0.82 (sensitivity = 84%, specificity = 70%), while it reached a mean AUC of 0.70 (sensitivity = 68%, specificity = 67%) within the 100 repetitions. Conclusions: CTTA might help in stratifying different behaviors of mCRC, opening the way for lesion-specific therapies, with conceivable cost and life savings. Further extended analysis is needed to better characterize and validate predictive value of these biomarkers.

scholarly journals CT texture analysis of Abdominal Lesions – Part II.: Tumors of the Kidney and Pancreas

Imaging ◽  
2021 ◽  
Author(s):  
Veronica Frank ◽  
Sonaz Shariati ◽  
Bettina Katalin Budai ◽  
Bence Fejér ◽  
Ambrus Tóth ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Pancreatic Tumors ◽  
Short Report ◽  
Kidney Tumors ◽  
Texture Parameters ◽  
Ct Texture Analysis ◽  
Abdominal Lesions ◽  
Significant Attention

ABSTRACTIt has been proven in a few early studies that radiomic analysis offers a promising opportunity to detect or differentiate between organ lesions based on their unique texture parameters. Recently, the utilization of CT texture analysis (CTTA) has been receiving significant attention, especially for response evaluation and prognostication of different oncological diagnoses. In this review article, we discuss the unique ability of radiomics and its subfield CTTA to diagnose lesions in the pancreas and kidney. We review studies in which CTTA was used for the classification of histology grades in pancreas and kidney tumors. We also review the role of radiogenomics in the prediction of the molecular and genetic subtypes of pancreatic tumors. Furthermore, we provide a short report on recent advancements of radiomic analysis in predicting prognosis and survival of patients with pancreatic and renal cancers.

PD-L1 Inhibitors for the Treatment of Prostate Cancer

2020 ◽  
Vol 21 (15) ◽  
pp. 1558-1565
Author(s):  
Matteo Santoni ◽  
Francesco Massari ◽  
Liang Cheng ◽  
Alessia Cimadamore ◽  
Marina Scarpelli ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Trials ◽  
T Lymphocytes ◽  
Chronic Inflammation ◽  
Immune Cells ◽  
Response To Therapy ◽  
Complex Series

The carcinogenesis of prostate cancer (PCa) results from a complex series of events. Chronic inflammation and infections are crucial in this context. Infiltrating M2 type macrophages, as well as neutrophils and T lymphocytes, contribute to PCa development, progression and response to therapy. The preliminary findings on the efficacy of immunotherapy in patients with PCa were not encouraging. However, a series of studies investigating anti-PD-L1 agents such as Atezolizumab, Avelumab and Durvalumab used alone or in combination with other immunotherapies, chemotherapy or locoregional approaches are in course in this tumor. In this review, we illustrate the role of immune cells and PD-L1 expression during PCa carcinogenesis and progression, with a focus on ongoing clinical trials on anti-PD-L1 agents in this context.

scholarly journals Cancer, Retrogenes, and Evolution

Life ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 72
Author(s):  
Klaudia Staszak ◽  
Izabela Makałowska
Keyword(s):  
Specific Resistance ◽  
Neoplastic Transformation ◽  
Resistance Mechanisms ◽  
Response To Therapy ◽  
Additional Gene ◽  
Cancer Subtypes ◽  
Gene Copies ◽  
Specific Cancer ◽  
Evolution Of Genomes

This review summarizes the knowledge about retrogenes in the context of cancer and evolution. The retroposition, in which the processed mRNA from parental genes undergoes reverse transcription and the resulting cDNA is integrated back into the genome, results in additional copies of existing genes. Despite the initial misconception, retroposition-derived copies can become functional, and due to their role in the molecular evolution of genomes, they have been named the “seeds of evolution”. It is convincing that retrogenes, as important elements involved in the evolution of species, also take part in the evolution of neoplastic tumors at the cell and species levels. The occurrence of specific “resistance mechanisms” to neoplastic transformation in some species has been noted. This phenomenon has been related to additional gene copies, including retrogenes. In addition, the role of retrogenes in the evolution of tumors has been described. Retrogene expression correlates with the occurrence of specific cancer subtypes, their stages, and their response to therapy. Phylogenetic insights into retrogenes show that most cancer-related retrocopies arose in the lineage of primates, and the number of identified cancer-related retrogenes demonstrates that these duplicates are quite important players in human carcinogenesis.

scholarly journals The role of FDG PET/CT or PET/MRI in assessing response to neoadjuvant therapy for patients with borderline or resectable pancreatic cancer: a systematic literature review

2021 ◽  
Author(s):  
Laura Evangelista ◽  
Pietro Zucchetta ◽  
Lucia Moletta ◽  
Simone Serafini ◽  
Gianluca Cassarino ◽  
...  
Keyword(s):  
Neoadjuvant Therapy ◽  
Fdg Pet ◽  
Standardized Uptake Value ◽  
Response To Therapy ◽  
Ductal Adenocarcinoma ◽  
Resectable Pancreatic Cancer ◽  
Number Of Patients ◽  
Pet Ct ◽  
Fdg Pet Ct

AbstractThe aim of the present systematic review is to examine the role of fluorodeoxyglucose (FDG) positron emission tomography (PET) associated with computed tomography (CT) or magnetic resonance imaging (MRI) in assessing response to preoperative chemotherapy or chemoradiotherapy (CRT) for patients with borderline and resectable pancreatic ductal adenocarcinoma (PDAC). Three researchers ran a database query in PubMed, Web of Science and EMBASE. The total number of patients considered was 488. The most often used parameters of response to therapy were the reductions in the maximum standardized uptake value (SUVmax) or the peak standardized uptake lean mass (SULpeak). Patients whose SUVs were higher at the baseline (before CRT) were associated with a better response to therapy and a better overall survival. SUVs remaining high after neoadjuvant therapy correlated with a poor prognosis. Available data indicate that FDG PET/CT or PET/MRI can be useful for predicting and assessing response to CRT in patients with resectable or borderline PDAC.

scholarly journals Value of contrast-enhanced CT texture analysis in predicting IDH mutation status of intrahepatic cholangiocarcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yong Zhu ◽  
Yingfan Mao ◽  
Jun Chen ◽  
Yudong Qiu ◽  
Yue Guan ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Ct Images ◽  
Textural Features ◽  
Mutation Status ◽  
Portal Venous Phase ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Venous Phase ◽  
Ct Texture Analysis

AbstractTo explore the value of contrast-enhanced CT texture analysis in predicting isocitrate dehydrogenase (IDH) mutation status of intrahepatic cholangiocarcinomas (ICCs). Institutional review board approved this study. Contrast-enhanced CT images of 138 ICC patients (21 with IDH mutation and 117 without IDH mutation) were retrospectively reviewed. Texture analysis was performed for each lesion and compared between ICCs with and without IDH mutation. All textural features in each phase and combinations of textural features (p < 0.05) by Mann–Whitney U tests were separately used to train multiple support vector machine (SVM) classifiers. The classification generalizability and performance were evaluated using a tenfold cross-validation scheme. Among plain, arterial phase (AP), portal venous phase (VP), equilibrium phase (EP) and Sig classifiers, VP classifier showed the highest accuracy of 0.863 (sensitivity, 0.727; specificity, 0.885), with a mean area under the receiver operating characteristic curve of 0.813 in predicting IDH mutation in validation cohort. Texture features of CT images in portal venous phase could predict IDH mutation status of ICCs with SVM classifier preoperatively.

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