scholarly journals Association of visual and quantitative heterogeneity of 18F-FDG PET images with treatment response in locally advanced rectal cancer: A feasibility study

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242597
Author(s):  
Paula Martin-Gonzalez ◽  
Estibaliz Gomez de Mariscal ◽  
M. Elena Martino ◽  
Pedro M. Gordaliza ◽  
Isabel Peligros ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Fdg Pet ◽  
Tumor Heterogeneity ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Advanced Rectal Cancer ◽  
Locally Advanced Rectal Cancer ◽  
Metabolic Parameters ◽  
Response To Treatment ◽  
Tumor Regression Grade

Background and purpose Few tools are available to predict tumor response to treatment. This retrospective study assesses visual and automatic heterogeneity from 18F-FDG PET images as predictors of response in locally advanced rectal cancer. Methods This study included 37 LARC patients who underwent an 18F-FDG PET before their neoadjuvant therapy. One expert segmented the tumor from the PET images. Blinded to the patient´s outcome, two experts established by consensus a visual score for tumor heterogeneity. Metabolic and texture parameters were extracted from the tumor area. Multivariate binary logistic regression with cross-validation was used to estimate the clinical relevance of these features. Area under the ROC Curve (AUC) of each model was evaluated. Histopathological tumor regression grade was the ground-truth. Results Standard metabolic parameters could discriminate 50.1% of responders (AUC = 0.685). Visual heterogeneity classification showed correct assessment of the response in 75.4% of the sample (AUC = 0.759). Automatic quantitative evaluation of heterogeneity achieved a similar predictive capacity (73.1%, AUC = 0.815). Conclusion A response prediction model in LARC based on tumor heterogeneity (assessed either visually or with automatic texture measurement) shows that texture features may complement the information provided by the metabolic parameters and increase prediction accuracy.

scholarly journals Radiotherapy Scheme Effect on PD-L1 Expression for Locally Advanced Rectal Cancer

Cells ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 2071
Author(s):  
Jihane Boustani ◽  
Valentin Derangère ◽  
Aurélie Bertaut ◽  
Olivier Adotevi ◽  
Véronique Morgand ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Tumor Regression ◽  
Checkpoint Inhibitors ◽  
Objective Response ◽  
Locally Advanced ◽  
Progression Free Survival ◽  
Advanced Rectal Cancer ◽  
Locally Advanced Rectal Cancer ◽  
Tumor Regression Grade ◽  
The Impact

In locally advanced rectal cancer, radiotherapy (RT) followed by surgery have improved locoregional control, but distant recurrences remain frequent. Although checkpoint inhibitors have demonstrated objective response in several cancers, the clinical benefit of PD-1/PD-L1 blockade remains uncertain in rectal cancer. We collected data from biopsies and surgical specimens in 74 patients. The main objective was to evaluate the impact of neoadjuvant RT and fractionation on PD-L1 expression. Secondary objectives were to study the relation between PD-L1 expression and tumor regression grade (TRG), progression-free survival (PFS), overall survival (OS), and CD8 TILs infiltration. Median rates of cells expressing PD-L1 pre- and post-RT were 0.15 (range, 0–17) and 0.5 (range, 0–27.5), respectively (p = 0.0005). There was no effect of RT fractionation on PD-L1+ cell rates. We found no relation between CD8+ TILs infiltration and PD-L1 expression and no difference between high-PD-L1 or low-PD-L1 expression and TRG. High-to-high PD-L1 expression profile had none significant higher OS and PFS compared to all other groups (p = 0.06). Median OS and PFS were higher in biopsies with >0.08 PD-L1+ cells. High-to-high PD-L1 profile and ypT0-2 were significantly associated with higher OS and PFS. This study did not show the differential induction of PD-L1 expression according to fractionation.

The prognosis valve of tumor regression grade in the same ypStage patients after neoadjuvant treatment in locally advanced rectal cancer: Post-hoc analysis of a prospective trial.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16129-e16129
Author(s):  
Jianwei Zhang ◽  
Yue Cai ◽  
Huabin Hu ◽  
Zehua Wu ◽  
Xiaoyu Xie ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Prospective Trial ◽  
Neoadjuvant Treatment ◽  
Disease Free Survival ◽  
Advanced Rectal Cancer ◽  
Locally Advanced Rectal Cancer ◽  
Tumor Regression Grade ◽  
Prognosis Factor

e16129 Background: The ypStage after neoadjuvant treatment was an important prognosis factor in locally advanced rectal cancer (LARC). pCR or ypStage 0 showed best prognosis, while ypStage II-III showed poor prognosis and further adjuvant chemotherapy with FOLFOX was recommended. Tumor regression grade (TRG) was another factor to evaluate the response to neoadjuvant treatment. Even in the same ypStage, the TRG could be different. Here, we tried to analyze the prognosis valve of TRG in the same ypStage after neoadjuvant treatment in LARC from a prospective trial (FOWARC study). Methods: Patients with stage II/III rectal cancer were randomly assigned (1:1:1) to five cycles of infusional fluorouracil plus radiotherapy followed by surgery and seven cycles of infusional fluorouracil as adjuvant treatment, the same treatment plus intravenous oxaliplatin 85 mg/m2 on day 1 of each cycle (mFOLFOX6), or four to six cycles of mFOLFOX6 followed by surgery and six to eight cycles of mFOLFOX6. The primary end point was 3-year disease-free survival (DFS). Survival analysis was performed on different ypStage and TRG (WHO classification) group. Results: In total, 495 patients were randomly assigned to different neoadjuvant treatment. 444 patients received surgery with a median follow-up of 45.2 months. The 3-year disease free survival (DFS) in ypStage 0, ypStage I, ypStage II and ypStage III was 95.8%, 89.2%, 71.7% and 55.1%, respectively (P < 0.0001). In TRG 0, 1, 2 and 3, the 3-year DFS was 93.3%, 83.2%, 68.4% and 63.6%, respectively (P < 0.0001). In ypStage I subgroup, TRG was not an independent prognosis factor, the 3-year DFS for TRG 1, 2 and 3 was 90.0%, 90.7% and 76.2%, respectively (P = 0.277). In ypStage II population, the 3-year DFS for TRG 1, 2 and 3 was 78.6%, 70.3% and 64.7%, respectively (P = 0.184). The ypStage III group showed great heterogeneity, the 3-year DFS for TRG 0-3 was 60.0%, 70.0%, 41.8% and 59.5%, respectively (P = 0.067). Conclusions: Both ypStage and TRG was strong prognosis factor for rectal cancer after neoadjuvant treatment. However, TRG was not an independent prognosis factor in the same ypStage after neoadjuvant treatment. Clinical trial information: NCT01211210 .

Modified 3-Point MRI-Based Tumor Regression Grade Incorporating DWI for Locally Advanced Rectal Cancer

2017 ◽  
Vol 209 (6) ◽  
pp. 1247-1255 ◽  
Author(s):  
Min A Lee ◽  
Seung Hyun Cho ◽  
An Na Seo ◽  
Hye Jung Kim ◽  
Kyung-Min Shin ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Advanced Rectal Cancer ◽  
Locally Advanced Rectal Cancer ◽  
Tumor Regression Grade ◽  
Regression Grade

scholarly journals DPYD,TYMS,TYMP,TK1, andTK2Genetic Expressions as Response Markers in Locally Advanced Rectal Cancer Patients Treated with Fluoropyrimidine-Based Chemoradiotherapy

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Ming-Yii Huang ◽  
Chan-Han Wu ◽  
Chun-Ming Huang ◽  
Fu-Yen Chung ◽  
Ching-Wen Huang ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Disease Free Survival ◽  
High Sensitivity ◽  
Response Prediction ◽  
Advanced Rectal Cancer ◽  
Locally Advanced Rectal Cancer ◽  
Tumor Regression Grade ◽  
Genetic Biomarkers

This study is to investigate multiple chemotherapeutic agent- and radiation-related genetic biomarkers in locally advanced rectal cancer (LARC) patients following fluoropyrimidine-based concurrent chemoradiotherapy (CCRT) for response prediction. We initially selected 6 fluoropyrimidine metabolism-related genes (DPYD, ORPT, TYMS, TYMP, TK1, andTK2) and 3 radiotherapy response-related genes (GLUT1,HIF-1α, andHIF-2α) as targets for gene expression identification in 60 LARC cancer specimens. Subsequently, a high-sensitivity weighted enzymatic chip array was designed and constructed to predict responses following CCRT. After CCRT, 39 of 60 (65%) LARC patients were classified as responders (pathological tumor regression grade2~4). Using a panel of multiple genetic biomarkers (chip), includingDPYD,TYMS,TYMP,TK1, andTK2, at a cutoff value for 3 positive genes, a sensitivity of 89.7% and a specificity of 81% were obtained (AUC: 0.915; 95% CI: 0.840–0.991). Negative chip results were significantly correlated to poor CCRT responses (TRG 0-1) (P=0.014, hazard ratio: 22.704, 95% CI: 3.055–235.448 in multivariate analysis). Disease-free survival analysis showed significantly better survival rate in patients with positive chip results (P=0.0001). We suggest that a chip includingDPYD,TYMS,TYMP,TK1, andTK2genes is a potential tool to predict response in LARC following fluoropyrimidine-based CCRT.

scholarly journals Pre-Treatment T2-WI Based Radiomics Features for Prediction of Locally Advanced Rectal Cancer Non-Response to Neoadjuvant Chemoradiotherapy: A Preliminary Study

Cancers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1894 ◽  
Author(s):  
Bianca Petresc ◽  
Andrei Lebovici ◽  
Cosmin Caraiani ◽  
Diana Sorina Feier ◽  
Florin Graur ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Neoadjuvant Chemoradiotherapy ◽  
Advanced Rectal Cancer ◽  
Locally Advanced Rectal Cancer ◽  
Imaging Biomarkers ◽  
Tumor Regression Grade ◽  
Pre Treatment

Locally advanced rectal cancer (LARC) response to neoadjuvant chemoradiotherapy (nCRT) is very heterogeneous and up to 30% of patients are considered non-responders, presenting no tumor regression after nCRT. This study aimed to determine the ability of pre-treatment T2-weighted based radiomics features to predict LARC non-responders. A total of 67 LARC patients who underwent a pre-treatment MRI followed by nCRT and total mesorectal excision were assigned into training (n = 44) and validation (n = 23) groups. In both datasets, the patients were categorized according to the Ryan tumor regression grade (TRG) system into non-responders (TRG = 3) and responders (TRG 1 and 2). We extracted 960 radiomic features/patient from pre-treatment T2-weighted images. After a three-step feature selection process, including LASSO regression analysis, we built a radiomics score with seven radiomics features. This score was significantly higher among non-responders in both training and validation sets (p < 0.001 and p = 0.03) and it showed good predictive performance for LARC non-response, achieving an area under the curve (AUC) = 0.94 (95% CI: 0.82–0.99) in the training set and AUC = 0.80 (95% CI: 0.58–0.94) in the validation group. The multivariate analysis identified the radiomics score as an independent predictor for the tumor non-response (OR = 6.52, 95% CI: 1.87–22.72). Our results indicate that MRI radiomics features could be considered as potential imaging biomarkers for early prediction of LARC non-response to neoadjuvant treatment.

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