Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Martin-Gonzalez P

PROVIDER: S-EPMC7704000 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Martin-Gonzalez Paula P de Mariscal Estibaliz Gomez EG Martino M Elena ME Gordaliza Pedro M PM Peligros Isabel I Carreras Jose Luis JL Calvo Felipe A FA Pascau Javier J Desco Manuel M Muñoz-Barrutia Arrate A

PloS one 20201130 11

<h4>Background and purpose</h4>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.<h4>Methods</h4>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 scor ...[more]

PMID: 33253194

Similar Datasets

Project description:Purpose:Hematologic toxicity (HT) during chemoradiation therapy (CRT) for anal cancer can lead to treatment breaks that compromise efficacy. We hypothesized that CRT-induced HT correlates with changes in active bone marrow (ABM) characterized by pre-/post-CRT positron emission tomography (PET)/computed tomography. Methods and materials:Data from 36 patients with anal cancer who were treated with 18F-fluorodeoxyglucose PET/computed tomography scans 2 weeks before and 6 to 16 weeks after CRT were analyzed. Complete blood counts with differential within 2 weeks from, weekly during, and 2 week after treatment were obtained. HT was defined as baseline complete blood count change to nadir and posttreatment recovery. Total bone marrow was segmented into 2 subregions: lumbosacral (LS) pelvis (L5 vertebrae, sacrum, and coccyx) and lower pelvis (LP) (ilium, femoral head/neck, and greater and lesser trochanter). PET ABM was characterized as the volume having standard uptake value (SUV) greater than the mean uptake of unirradiated extrapelvic bone marrow. PET variables of pre-/post-CRT and HT predictors were analyzed by linear regression. Results:Average pelvic ABM was significantly reduced from 52% to 41% in pre- to post-CRT PET scans for all patients (P = .0012). Regional analysis indicated significant post-CRT reduction of LS-ABM (P < .0001) and LP-ABM (P = .006). Linear regression analysis identified post-CRT SUVmean, differential ?SUVmean, and ?ABM as correlating significantly with pre- and posttreatment HT. ?WBC linearly correlated with ?ABM of LS and LP pelvis (P = .033 and P = .028, respectively). Dosimetrically, ABM was sensitive to higher radiation doses (>50 Gy) in terms of acute hematologic ?WBC (P = .021) and ?ANC(P = .028). HT increased with increasing volume of ABM receiving 40 Gy. The results also suggest that ABM V40 Gy ? 20% to 25% may significantly reduce the risk of HT. Conclusions:HT was significantly associated with ?ABM in patients with anal cancer who were treated with CRT. LS-ABM was a robust surrogate for evaluating CRT-induced HT. Our results suggest implementation of ABM dosimetric constraints, V40 Gy ? 20-25%, may significantly reduce HT and lead to decreased treatment delays associated with clinical outcomes.

Project description:Previous studies have demonstrated how imaging of the breast with patients lying prone using a supportive positioning device markedly facilitates longitudinal and/or multimodal image registration. In this contribution, the authors' primary objective was to determine if there are differences in the standardized uptake value (SUV) derived from [(18)F]fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) in breast tumors imaged in the standard supine position and in the prone position using a specialized positioning device.A custom positioning device was constructed to allow for breast scanning in the prone position. Rigid and nonrigid phantom studies evaluated differences in prone and supine PET. Clinical studies comprised 18F-FDG-PET of 34 patients with locally advanced breast cancer imaged in the prone position (with the custom support) followed by imaging in the supine position (without the support). Mean and maximum values (SUVpeak and SUVmax, respectively) were obtained from tumor regions-of-interest for both positions. Prone and supine SUV were linearly corrected to account for the differences in 18F-FDG uptake time. Correlation, Bland-Altman, and nonparametric analyses were performed on uptake time-corrected and uncorrected data.SUV from the rigid PET breast phantom imaged in the prone position with the support device was 1.9% lower than without the support device. In the nonrigid PET breast phantom, prone SUV with the support device was 5.0% lower than supine SUV without the support device. In patients, the median (range) difference in uptake time between prone and supine scans was 16.4 min (13.4-30.9 min), which was significantly-but not completely-reduced by the linear correction method. SUVpeak and SUVmax from prone versus supine scans were highly correlated, with concordance correlation coefficients of 0.91 and 0.90, respectively. Prone SUVpeak and SUVmax were significantly lower than supine in both original and uptake time-adjusted data across a range of index times (P < < 0.0001, Wilcoxon signed rank test). Before correcting for uptake time differences, Bland-Altman analyses revealed proportional bias between prone and supine measurements (SUVpeak and SUVmax) that increased with higher levels of FDG uptake. After uptake time correction, this bias was significantly reduced (P < 0.01). Significant prone-supine differences, with regard to the spatial distribution of lesions relative to isocenter, were observed between the two scan positions, but this was poorly correlated with the residual (uptake time-corrected) prone-supine SUVpeak difference (P = 0.78).Quantitative 18F-FDG-PET/CT of the breast in the prone position is not deleteriously affected by the support device but yields SUV that is consistently lower than those obtained in the standard supine position. SUV differences between scans arising from FDG uptake time differences can be substantially reduced, but not removed entirely, with the current correction method. SUV from the two scan orientations is quantitatively different and should not be assumed equivalent or interchangeable within the same subject. These findings have clinical relevance in that they underscore the importance of patient positioning while scanning as a clinical variable that must be accounted for with longitudinal PET measurement, for example, in the assessment of treatment response.

Project description:UnlabelledIn a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on (18)F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information.MethodsPatients with locally advanced NSCLC underwent (18)F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient's primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address overfitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan-Meier curves and log-rank testing were used to compare outcomes among patient groups.ResultsTwo hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm(3), and the optimal SumMean cutpoint for tumors above 93.3 cm(3) was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P < 0.001).ConclusionWe have described an appropriate methodology to evaluate the prognostic value of textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted.

Project description:We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 (18)F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75 ± 1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV(max) (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV(max). We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16).

Project description:BACKGROUND:There is an increasing interest in developing predictive biomarkers of tissue hypoxia using functional imaging for personalised radiotherapy in patients with rectal cancer that are considered for neoadjuvant chemoradiotherapy (CRT). The study explores [18F]fluoromisonidazole ([18F]FMISO) positron emission tomography (PET) scans for predicting clinical response in rectal cancer patients receiving neoadjuvant CRT. METHODS:Patients with biopsy-proven rectal adenocarcinoma were imaged at 0-45 min, 2 and 4 h, at baseline and after 8-10 fractions of CRT (week 2). The first 6 patients did not receive an enema (the non-enema group) and the last 4 patients received an enema before PET-CT scan (the enema group). [18F]FMISO production failed on 2 occasions. Static PET images at 4 h were analysed using tumour-to-muscle (T:M) SUVmax and tumour-to-blood (T:B) SUVmax. The 0-45 min dynamic PET scans were analysed using Casciari model to report hypoxia and perfusion. Akaike information criteria (AIC) were used to compare data fittings for different pharmacokinetic models. Pathological tumour regression grade was scored using American Joint Committee on Cancer (AJCC) 7.0. Shapiro-Wilk test was used to evaluate the normality of the data. RESULTS:Five out of eleven (5/11) patients were classed as good responders (AJCC 0/1 or good clinical response) and 6/11 as poor responders (AJCC 2/3 or poor clinical response). The median T:M SUVmax was 2.14 (IQR 0.58) at baseline and 1.30 (IQR 0.19) at week 2, and the corresponding median tumour hypoxia volume was 1.08 (IQR 1.31) cm3 and 0 (IQR 0.15) cm3, respectively. The median T:B SUVmax was 2.46 (IQR 1.50) at baseline and 1.61 (IQR 0.14) at week 2, and the corresponding median tumour hypoxia volume was 5.68 (IQR 5.86) cm3 and 0.76 (IQR 0.78) cm3, respectively. For 0-45 min tumour modelling, the median hypoxia was 0.92 (IQR 0.41) min-1 at baseline and 0.70 (IQR 0.10) min-1 at week 2. The median perfusion was 4.10 (IQR 1.71) ml g-1 min-1 at baseline and 2.48 (IQR 3.62) ml g-1 min-1 at week 2. In 9/11 patients with both PET scans, tumour perfusion decreased in non-responders and increased in responders except in one patient. None of the changes in other PET parameters showed any clear trend with clinical outcome. CONCLUSIONS:This pilot study with small number of datasets revealed significant challenges in delivery and interpretation of [18F]FMISO PET scans of rectal cancer. There are two principal problems namely spill-in from non-tumour tracer activity from rectal and bladder contents. Emphasis should be made on reducing spill-in effects from the bladder to improve data quality. This preliminary study has shown fundamental difficulties in the interpretation of [18F]FMISO PET scans for rectal cancer, limiting its clinical applicability.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets