scholarly journals DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Jinrong Qu ◽  
Ling Ma ◽  
Yanan Lu ◽  
Zhaoqi Wang ◽  
Jia Guo ◽  
...  
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Vascular Permeability ◽  
Tumor Regression ◽  
Response Prediction ◽  
Response Assessment ◽  
Tumor Regression Grade ◽  
Dce Mri ◽  
A Prospective Study ◽  
Radiomics Signature ◽  
Response To Neoadjuvant Chemotherapy

Abstract Objectives To assess volumetric DCE-MRI radiomics nomogram in predicting response to neoadjuvant chemotherapy (nCT) in EC patients. Methods This retrospective analysis of a prospective study enrolled EC patients with stage cT1N + M0 or cT2-4aN0-3M0 who received DCE-MRI within 7 days before chemotherapy, followed by surgery. Response assessment was graded from 1 to 5 according to the tumor regression grade (TRG). Patients were stratified into responders (TRG1 + 2) and non-responders (TRG3 + 4 + 5). 72 radiomics features and vascular permeability parameters were extracted from DCE-MRI. The discriminating performance was assessed with ROC. Decision curve analysis (DCA) was used for comparing three different models. Results This cohort included 82 patients, and 72 tumor radiomics features and vascular permeability parameters acquired from DCE-MRI. mRMR and LASSO were performed to choose the optimized subset of radiomics features, and 3 features were selected to create the radiomics signature that were significantly associated with response (P < 0.001). AUC of combining radiomics signature and DCE-MRI performance in the training (n = 41) and validation (n = 41) cohort was 0.84 (95% CI 0.57–1) and 0.86 (95% CI 0.74–0.97), respectively. This combined model showed the best discrimination between responders and non-responders, and showed the highest positive and positive predictive value in both training set and test set. Conclusions The radiomics features are useful for nCT response prediction in EC patients.

scholarly journals Genomic Analysis of Response to Neoadjuvant Chemotherapy in Esophageal Adenocarcinoma

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3394
Author(s):  
Fereshteh Izadi ◽  
Benjamin Sharpe ◽  
Stella Breininger ◽  
Maria Secrier ◽  
Jane Gibson ◽  
...  
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Esophageal Adenocarcinoma ◽  
Copy Number ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Genomic Analysis ◽  
Tumor Regression Grade ◽  
Comparative Genomic ◽  
Mutation Burden ◽  
Response To Neoadjuvant Chemotherapy

Neoadjuvant therapy followed by surgery is the standard of care for locally advanced esophageal adenocarcinoma (EAC). Unfortunately, response to neoadjuvant chemotherapy (NAC) is poor (20–37%), as is the overall survival benefit at five years (9%). The EAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. To identify associations between genomic events and response to NAC in EAC, a comparative genomic analysis was performed in 65 patients with extensive clinical and pathological annotation using whole-genome sequencing (WGS). We defined response using Mandard Tumor Regression Grade (TRG), with responders classified as TRG1–2 (n = 27) and non-responders classified as TRG4–5 (n =38). We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs. 1.70/Mb, p = 0.036) and elevated copy number variation in non-responders (282 vs. 136/patient, p < 0.001). We identified copy number variants unique to each group in our cohort, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of note, NAV3 mutations were exclusively present in the non-responder group with a frequency of 22%. Thus, lower mutation burden, higher chromosomal instability and specific copy number alterations are associated with resistance to NAC.

scholarly journals Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma

2021 ◽  
Author(s):  
Fereshteh Izadi ◽  
Benjamin P Sharpe ◽  
Stella P Breininger ◽  
Maria Secrier ◽  
Jane Gibson ◽  
...  
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Esophageal Adenocarcinoma ◽  
Copy Number ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Genomic Analysis ◽  
Tumor Regression Grade ◽  
Comparative Genomic ◽  
Mutation Burden ◽  
Response To Neoadjuvant Chemotherapy

Neoadjuvant therapy followed by surgery is the standard of care for locally advanced esophageal adenocarcinoma (EAC). Unfortunately, response to neoadjuvant chemotherapy (NAC) is poor (<20%), as is the overall survival benefit at 5 years (5%). The EAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. To identify associations between genomic events and response to NAC in EAC, a comparative genomic analysis was performed in 65 patients with extensive clinical and pathological annotation using whole-genome sequencing (WGS). We defined response using Mandard Tumor Regression Grade (TRG), with responders classified as TRG1-2 (n=27) and non-responders classified as TRG4-5 (n=38). We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs 1.70/Mb, P=0.036) and elevated copy number variation in non-responders (282 vs 136/patient, P<0.001). We identified copy number variants unique to each group in our cohort, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of note, NAV3 mutations were exclusively present in the non-responder group with a frequency of 22%. Thus, lower mutation burden, higher chromosomal instability and specific copy number alterations are associated with resistance to NAC.

scholarly journals 474 GENOMIC ANALYSIS OF RESPONSE TO NEOADJUVANT CHEMOTHERAPY IN ESOPHAGEAL ADENOCARCINOMA

2020 ◽  
Vol 33 (Supplement_1) ◽  
Author(s):  
F Izadi ◽  
G Devonshire ◽  
R Walker ◽  
M Lloyd ◽  
J Gibson ◽  
...  
Keyword(s):  
Dna Damage ◽  
Neoadjuvant Chemotherapy ◽  
Esophageal Adenocarcinoma ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Chemotherapy Resistance ◽  
Treatment Modalities ◽  
Tumor Regression Grade ◽  
Driver Genes ◽  
The Impact

Abstract   In the UK, neoadjuvant chemotherapy (NAC) for locally advanced esophageal adenocarcinoma (EAC) is the standard of care. Unfortunately, response to NAC, following surgery is often low (&lt;30%) and survival benefit at 2 years is only 5.1%. The EAC genome is complex and heterogeneous between patients, where specific mutagenic processes and mutations may result in chemotherapy resistance. Here we report preliminary results from whole-genome sequencing (WGS) of 48 patients who were subsequently treated with NAC. Methods We defined response as Mandard Tumor Regression Grade (TRG) 1-2 (n = 15) and non-response as TRG4-5 (n = 33). WGS of 50x coverage and calling of genomic events (Strelka2, SCAT/GISTIC) was performed according to Frankell Nat Genet 2019 with modifications, to differentiate driver from passenger mutations (dNdScv, oncodriveCLUST), determine variant allele frequencies (VAF; copy number-adjusted) and mutation signatures (NMF R-package). Following stringent variant QC (Phred score ≥ 30), filtering (VAF &gt;0.02) and annotation (ANNOVAR, cancer census/helper, the 77 known EAC drivers and false positive genes) and visualisation in maftools, we evaluated the data for associations between genomic events and response to NAC. Results COSMIC mutation signatures 2 (TRG1-2; Cosθ = 0.89) and 6 (TRG4-5; Cosθ = 0.82) were enriched, suggesting defective mismatch repair in non-responders. Using 5,193 high-confidence non-silent mutations (TRG1-2,n = 1969; TRG4-5, n = 3224), we identified 39 mutated driver genes (Figure-1) with a median of 2.9(0-5) (TRG1-2) and 2.7(0-9) (TRG4-5) driver events/patient. Shared dysregulated pathways, included DNA-damage (TP53), cell cycle (CDKN2A), TGF-β (SMAD4) and chromatin regulation (ARID1A). There was no difference in the prognostic of SMAD4 and GATA4 genes. Interestingly, NAV3 mutations were only present in non-responders (21%,7/33); and in responders TP53 incidence was higher (93% vs. 58%) with a concomitant reduction in clonal cell fraction (0.25 vs. 0.39;Wilcoxon, p &lt; 0.0001). Conclusion The data suggest that specific genomic events, such as NAV3 mutation and the intra-tumoral heterogeneity of mutated DNA-damage response genes may offer additional predictive value. Ongoing work includes analysis of the impact of non-coding variation on response. While our analysis is limited by sample size and requires validation in additional cohorts, it demonstrates the potential of genomic sequencing to identify NAC response biomarkers and may guide alternative or novel treatment modalities for chemo-resistant tumours.

scholarly journals Does GRASP affect DCE-MRI for assessing response to neoadjuvant chemotherapy in patients with esophageal cancer?

2019 ◽  
Author(s):  
Yanan Lu ◽  
Ling Ma ◽  
Jianjun QIN ◽  
Zhaoqi Wang ◽  
Jia Guo ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Magnetic Resonance Images ◽  
Wilcoxon Test ◽  
Dce Mri ◽  
Low Correlation ◽  
Golden Angle ◽  
Response Groups ◽  
Response To Neoadjuvant Chemotherapy ◽  
Golden Angle Radial

Abstract Purpose To compare the value of two dynamic contrast-enhanced Magnetic Resonance Images (DCE-MRI) reconstruction approaches, namely golden-angle radial sparse parallel (GRASP) and view-sharing with golden-angle radial profile (VS-GR) reconstruction, and explore their values in assessing response to neoadjuvant chemotherapy (nCT) in esophageal cancer (EC). Methods The study prospectively enrolled EC patients receiving nCT before surgery. DCE-MRI scanning was performed after nCT and within 1 week before surgery. Chemotherapy response was assessed according to Tumor Regression Grade (TRG), and patients were stratified into a responsive group (TRG1+2) and a non-responsive group (TRG3+4+5). Wilcoxon test was utilized for comparing GRASP and VS-GR reconstruction, and Kruskal-Wallis and Mann-Whitney test was performed for each parameter to assess response, and Spearman test was performed for analyzing correlation between parameters and TRGs, as well as responder and non-responder. Results Among the 64 patients included in this cohort (52 male, 12 female; average age of 59.1±7.9 years), 4 patients showed TRG1, 4 patients were TRG2, 7 patients were TRG3, 11 patients were TRG4, and 38 patients were TRG5. They were stratified into 8 responders and 56 non-responders. A total of 15 parameters were calculated from each tumor. With VSGR, 10/15 parameters significantly correlated with TRG and response groups. Of these, only AUCmax showed moderate correlation with TRG, 7 showed low correlation and 2 showed negligible correlation with TRG. 8 showed low correlation and 2 showed negligible correlation with response groups. With GRASP, 13/15 parameters significantly correlated with TRG and response groups. Of these, 10 showed low correlation and 3 showed negligible correlation with TRG. 11 showed low correlation and 2 showed negligible correlation with TRG. Conclusion In patients with esophageal cancer on neoadjuvant chemotherapy, several parameters can differentiate responders from non-responders, using both GRASP and VS-GR techniques. GRASP may be able to better differentiate these two groups compared to VS-GR.

scholarly journals 3T DCE-MRI Radiomics Improves Predictive Models of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Stefania Montemezzi ◽  
Giulio Benetti ◽  
Maria Vittoria Bisighin ◽  
Lucia Camera ◽  
Chiara Zerbato ◽  
...  
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Predictive Models ◽  
Clinical Decision Making ◽  
Complete Response ◽  
Clinical Decision ◽  
Feature Reduction ◽  
Support Vector ◽  
Dce Mri ◽  
Neo Adjuvant Chemotherapy ◽  
Response To Neoadjuvant Chemotherapy

ObjectivesTo test whether 3T MRI radiomics of breast malignant lesions improves the performance of predictive models of complete response to neoadjuvant chemotherapy when added to other clinical, histological and radiological information.MethodsWomen who consecutively had pre-neoadjuvant chemotherapy (NAC) 3T DCE-MRI between January 2016 and October 2019 were retrospectively included in the study. 18F-FDG PET-CT and histological information obtained through lesion biopsy were also available. All patients underwent surgery and specimens were analyzed. Subjects were divided between complete responders (Pinder class 1i or 1ii) and non-complete responders to NAC. Geometric, first order or textural (higher order) radiomic features were extracted from pre-NAC MRI and feature reduction was performed. Five radiomic features were added to other available information to build predictive models of complete response to NAC using three different classifiers (logistic regression, support vector machines regression and random forest) and exploring the whole set of possible feature selections.ResultsThe study population consisted of 20 complete responders and 40 non-complete responders. Models including MRI radiomic features consistently showed better performance compared to combinations of other clinical, histological and radiological information. The AUC (ROC analysis) of predictors that did not include radiomic features reached up to 0.89, while all three classifiers gave AUC higher than 0.90 with the inclusion of radiomic information (range: 0.91-0.98).ConclusionsRadiomic features extracted from 3T DCE-MRI consistently improved predictive models of complete response to neo-adjuvant chemotherapy. However, further investigation is necessary before this information can be used for clinical decision making.

scholarly journals Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Mucinous Adenocarcinoma Using an MRI-Based Radiomics Nomogram

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhihui Li ◽  
Shuai Li ◽  
Shuqin Zang ◽  
Xiaolu Ma ◽  
Fangying Chen ◽  
...  
Keyword(s):  
Treatment Response ◽  
Mucinous Adenocarcinoma ◽  
Tumor Regression ◽  
Neoadjuvant Chemoradiotherapy ◽  
Roc Curves ◽  
Quantitative Mri ◽  
Tumor Regression Grade ◽  
Patient Variables ◽  
Validation Set ◽  
Radiomics Signature

ObjectiveTo build and validate an MRI-based radiomics nomogram to predict the therapeutic response to neoadjuvant chemoradiotherapy (nCRT) in rectal mucinous adenocarcinoma (RMAC).MethodsTotally, 92 individuals with pathologically confirmed RMAC administered surgical resection upon nCRT in two different centers were assessed retrospectively (training set, n = 52, validation set, n = 40). Rectal MRI was performed pre-nCRT. Radiomics parameters were obtained from high-resolution T2-weighted images and selected to construct a radiomics signature. Then, radiomics nomogram construction integrated patient variables and the radiomics signature. The resulting radiomics nomogram was utilized to assess the tumor regression grade (TRG). Diagnostic performance was determined by generating receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsSix optimal features related to TRG were obtained to construct a radiomics signature. The nomogram combining the radiomics signature with age and mucin deposit outperformed the radiomics signature alone in the training (AUC, 0.950 vs 0.843, p &lt; 0.05) and validation (AUC, 0.868 vs 0.719, p &lt; 0.05) cohorts. DCA demonstrated a clinical utility for the radiomics nomogram model.ConclusionsThe established quantitative MRI-based radiomics nomogram is effective in predicting treatment response to neoadjuvant therapy in patients with RMAC.

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