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.

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.

scholarly journals Incremental Role of 18F-FDG PET with contrast enhanced CT (PET-CECT) in detection of recurrence of carcinoma cervix

2016 ◽  
Author(s):  
S. Dash ◽  
A. Goel ◽  
S. Sogani
Keyword(s):  
Fdg Pet ◽  
Carcinoma Cervix ◽  
Histopathological Correlation ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Radiologic Imaging ◽  
18F Fdg

Purpose: To evaluate the role of 18F-FDG PET with contrast enhanced CT (PET-CECT) in early detection of recurrence in follow up patients of carcinoma cervix. Methods: Patients with histopathologically proven carcinoma cervix who underwent chemotherapy, radiotherapy and/or surgery and on follow up were recruited in the study. Fifty-two patients underwent 18F-FDG PET-CECT for detection of recurrence. The median age was 51.5 (average = 53.4) years. PET-CECT studies were evaluated and analyzed separately by an experienced nuclear medicine physician and a radiologist independently. The physicians were blinded for the patient history. PET-CECT results were validated with histopathological correlation, conventional radiologic imaging/follow up PET-CECT study and clinical follow up. Results: Out of 52 patients, 34 patients were reported as positive for recurrence, 17 of these were having active local recurrence and 31 patients had regional lymph nodal metastases, 14 patients had distant metastases (out of them 6 patients had distant lymph node metastases, 6 had pulmonary metastases, 4 had skeletal metastases and two had liver metastases). Remaining 18 patients were reported as negative for recurrence. The lung was the most common site for distant metastasis. Patient were then further evaluated based on histopathological correlation, conventional radiologic imaging and follow up PET-CECT scan and five were found to be false positive and one patient was identified as false negative. The sensitivity, specificity, positive and negative predictive value were derived to be 96.7%, 77.3%, 85.3% and 94.4%, respectively. Accuracy was calculated to be 88.5%. Conclusions: 18F-FDG PET-CECT is a very useful non-invasive modality for the early detection of recurrence and metastatic workup in patients with carcinoma cervix with a very high sensitivity and negative predictive value. It is also useful in targeting biopsy sites in suspected cases of recurrence.

Machine learning for lung texture analysis on thin-section CT: Capability for assessments of disease severity and therapeutic effect for connective tissue disease patients in comparison with expert panel evaluations

2021 ◽  
pp. 028418512110449
Author(s):  
Yoshiharu Ohno ◽  
Kota Aoyagi ◽  
Daisuke Takenaka ◽  
Takeshi Yoshikawa ◽  
Yasuko Fujisawa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Texture Analysis ◽  
Disease Severity ◽  
Thin Section ◽  
Ct Scans ◽  
Normal Lung ◽  
Quantitative Index ◽  
Serial Ct ◽  
Ct Texture Analysis

Background The need for quantitative assessment of interstitial lung involvement on thin-section computed tomography (CT) has arisen in interstitial lung diseases including connective tissue disease (CTD). Purpose To evaluate the capability of machine learning (ML)-based CT texture analysis for disease severity and treatment response assessments in comparison with qualitatively assessed thin-section CT for patients with CTD. Material and Methods A total of 149 patients with CTD-related ILD (CTD-ILD) underwent initial and follow-up CT scans (total 364 paired serial CT examinations), pulmonary function tests, and serum KL-6 level tests. Based on all follow-up examination results, all paired serial CT examinations were assessed as “Stable” (n = 188), “Worse” (n = 98) and “Improved” (n = 78). Next, quantitative index changes were determined by software, and qualitative disease severity scores were assessed by consensus of two radiologists. To evaluate differences in each quantitative index as well as in disease severity score between paired serial CT examinations, Tukey's honestly significant difference (HSD) test was performed among the three statuses. Stepwise regression analyses were performed to determine changes in each pulmonary functional parameter and all quantitative indexes between paired serial CT scans. Results Δ% normal lung, Δ% consolidation, Δ% ground glass opacity, Δ% reticulation, and Δdisease severity score showed significant differences among the three statuses ( P < 0.05). All differences in pulmonary functional parameters were significantly affected by Δ% normal lung, Δ% reticulation, and Δ% honeycomb (0.16 ≤r2 ≤0.42; P < 0.05). Conclusion ML-based CT texture analysis has better potential than qualitatively assessed thin-section CT for disease severity assessment and treatment response evaluation for CTD-ILD.

Tumor, immune, and stromal characteristics associated with clinical outcomes with atezolizumab (atezo) + platinum-based chemotherapy (PBC) or atezo monotherapy (mono) versus PBC in metastatic urothelial cancer (mUC) from the phase III IMvigor130 study.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 5011-5011 ◽  
Author(s):  
Matt D. Galsky ◽  
Romain Banchereau ◽  
Habib Rahman Hamidi ◽  
Ning Leng ◽  
Will Harris ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Urothelial Cancer ◽  
Phase Iii ◽  
Rna Seq ◽  
Metastatic Urothelial Cancer ◽  
Platinum Based Chemotherapy ◽  
Tumor Mutational Burden ◽  
Predictive Role ◽  
Clinical Trial Information

5011 Background: Tumor mutational burden (TMB), PD-L1 expression, T-effector gene expression (GE) and a fibroblast TGF-β–response signature (F-TBRS) are associated with clinical outcomes with atezo mono in mUC (Mariathasan, Nature, 2018). Here we explore the potential predictive role of these biomarkers and APOBEC mutagenesis in IMvigor130. Methods: Pts receiving first-line (1L) mUC treatment (tx) were randomized 1:1:1 to atezo + PBC, atezo mono, or placebo + PBC. Coprimary efficacy endpoints were PFS and OS. Planned exploratory biomarker analyses included PD-L1 expression, TMB (FoundationOne), and T-effector GE (RNA-seq). Results: The 851 biomarker-evaluable pts (BEP) were representative of the 1200 ITT pts. Biomarker results are shown in Table. PD-L1 IC2/3 was associated with significantly longer OS for atezo mono vs placebo + PBC and a combination of PD-L1 IC2/3, and high TMB (> 10 muts/Mb) identified a pt subset (≈ 14% of BEP) with particularly favorable outcomes with atezo mono vs placebo + PBC; similar results for PD-L1 and TMB were not seen with atezo + PBC vs placebo + PBC. APOBEC mutagenesis was associated with improved OS with atezo-containing regimens whereas high F-TBRS was associated with inferior OS with atezo mono. Conclusions: These results reinforce the potential predictive nature of biomarkers associated with response/resistance to atezo and highlight potentially distinct biology driving benefit with atezo and atezo + PBC. These findings suggest a possible biomarker-directed approach to 1L mUC tx that warrants mechanistic interrogation and prospective validation. Clinical trial information: NCT02807636 . [Table: see text]

MP61-10 PROGNOSTIC ROLE OF FGFR ALTERATIONS AND FGFR MRNA EXPRESSION IN METASTATIC UROTHELIAL CANCER TREATED WITH ANTI-PD(L1) INHIBITORS IN FIRST AN SECOND LINE SETTING

2020 ◽  
Vol 203 ◽  
pp. e939
Author(s):  
Florian Roghmann* ◽  
Ralph M Wirtz ◽  
Ademi Santiago-Walker ◽  
Jonas Jarczyk ◽  
Maximilian C Kiregmair ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Urothelial Cancer ◽  
Second Line ◽  
Prognostic Role ◽  
Metastatic Urothelial Cancer ◽  
Line Setting

scholarly journals Quantitative CT texture analysis in predicting PD-L1 expression in locally advanced or metastatic NSCLC patients

2021 ◽  
Author(s):  
Stefano Bracci ◽  
Miriam Dolciami ◽  
Claudio Trobiani ◽  
Antonella Izzo ◽  
Angelina Pernazza ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Advanced Nsclc ◽  
Validation Cohort ◽  
Locally Advanced ◽  
Area Under The Curve ◽  
Gray Level ◽  
Quantitative Ct ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Ct Texture Analysis

Abstract Purpose The assessment of Programmed death-ligand 1 (PD-L1) expression has become a game changer in the treatment of patients with advanced non-small cell lung cancer (NSCLC). We aimed to investigate the ability of Radiomics applied to computed tomography (CT) in predicting PD-L1 expression in patients with advanced NSCLC. Methods By applying texture analysis, we retrospectively analyzed 72 patients with advanced NSCLC. The datasets were randomly split into a training cohort (2/3) and a validation cohort (1/3). Forty radiomic features were extracted by manually drawing tumor volumes of interest (VOIs) on baseline contrast-enhanced CT. After selecting features on the training cohort, two predictive models were created using binary logistic regression, one for PD-L1 values ≥ 50% and the other for values between 1 and 49%. The two models were analyzed with ROC curves and tested in the validation cohort. Results The Radiomic Score (Rad-Score) for PD-L1 values ≥ 50%, which consisted of Skewness and Low Gray-Level Zone Emphasis (GLZLM_LGZE), presented a cut-off value of − 0.745 with an area under the curve (AUC) of 0.811 and 0.789 in the training and validation cohort, respectively. The Rad-Score for PD-L1 values between 1 and 49% consisted of Sphericity, Skewness, Conv_Q3 and Gray Level Non-Uniformity (GLZLM_GLNU), showing a cut-off value of 0.111 with AUC of 0.763 and 0.806 in the two population, respectively. Conclusion Rad-Scores obtained from CT texture analysis could be useful for predicting PD-L1 expression and guiding the therapeutic choice in patients with advanced NSCLC.

Neoadjuvant chemotherapy with DD-MVAC and bevacizumab in high-risk urothelial cancer: Results from a phase II trial at the M. D. Anderson Cancer Center.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 261-261 ◽  
Author(s):  
Arlene O. Siefker-Radtke ◽  
Ashish M. Kamat ◽  
Paul G. Corn ◽  
Surena F. Matin ◽  
H. Barton Grossman ◽  
...  
Keyword(s):  
High Risk ◽  
Neoadjuvant Chemotherapy ◽  
Phase Ii ◽  
Urothelial Cancer ◽  
Cancer Center ◽  
Upper Tract ◽  
Metastatic Urothelial Cancer ◽  
Eligibility Requirements ◽  
Grade 3

261 Background: DD-MVAC has shown an improved 5-year survival in metastatic urothelial cancer; however, there is no prospective data on its use in the neoadjuvant setting. Previous work suggested that over-expression of VEGF was associated with a high risk of relapse in our neoadjuvant patients, leading to the hypothesis that combining a VEGFR inhibitor with chemotherapy may improve patient outcomes. Methods: Between 8/07 and 12/10, 60 patients with urothelial carcinoma of the bladder or upper tract tumor were enrolled on a prospective phase II clinical trial. Eligibility requirements included at least one of the following: 3-D mass on EUA (cT3b disease), LVI, hydronephrosis, micropapillary features, tumor in a diverticula, and for upper tract tumors a high grade tumor or radiographically measurable sessile mass. The primary endpoint was pathologic down-staging to <=pT1N0M0. Results: Forty-four patients with bladder/urethral tumors and 16 patients with upper tract tumors were enrolled. Pathologic down-staging to <= pT1N0M0 occurred in 53% of patients overall (bladder/urethra 45%, upper tract 75%), and to <= pT0N0M0 in 38% overall (bladder/urethra 39%, upper tract 38%). At a median follow-up of 21 months, the 2-year OS and DSS was 78% and 85%, respectively (bladder 2-yr OS and DSS 75%, 82%; upper tract 93%, 93%). The median OS and DSS have not yet been reached. The most common grade 3 or greater toxicity was neutropenia in 27% of patients, followed by fatigue in 10%. The following grade 3 toxicities were observed in < 10% of patients: mucositis, DVT/PE, hypertension, nausea/vomiting, thrombocytopenia. One patient experienced cardiac ischemia. Conclusions: Neoadjuvant chemotherapy leads to pathologic down-staging in 45% of patients with bladder cancer. DD-MVAC appears an acceptable alternative to traditional M-VAC in the neoadjuvant setting. Although bevacizumab did not impact down-staging based upon historical expectations, determining the effect on recurrence requires longer follow-up.

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