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Identification of residual metabolic-active areas within individual NSCLC tumours using a pre-radiotherapy (18)Fluorodeoxyglucose-PET-CT scan.

ABSTRACT: Non-small cell lung cancer (NSCLC) tumours are mostly heterogeneous. We hypothesized that areas within the tumour with a high pre-radiation (18)F-deoxyglucose (FDG) uptake, could identify residual metabolic-active areas, ultimately enabling selective-boosting of tumour sub-volumes.Fifty-five patients with inoperable stage I-III NSCLC treated with chemo-radiation or with radiotherapy alone were included. For each patient one pre-radiotherapy and one post-radiotherapy FDG-PET-CT scans were available. Twenty-two patients showing persistent FDG uptake in the primary tumour after radiotherapy were analyzed. Overlap fractions (OFs) were calculated between standardized uptake value (SUV) threshold-based auto-delineations on the pre- and post-radiotherapy scan.Patients with residual metabolic-active areas within the tumour had a significantly worse survival compared to individuals with a complete metabolic response (p=0.002). The residual metabolic-active areas within the tumour largely corresponded (OF>70%) with the 50%SUV high FDG uptake area of the pre-radiotherapy scan. The hotspot within the residual area (90%SUV) was completely within the GTV (OF=100%), and had a high overlap with the pre-radiotherapy 50%SUV threshold (OF>84%).The location of residual metabolic-active areas within the primary tumour after therapy corresponded with the original high FDG uptake areas pre-radiotherapy. Therefore, a single pre-treatment FDG-PET-CT scan allows for the identification of residual metabolic-active areas.

SUBMITTER: Aerts HJ

PROVIDER: S-EPMC4693609 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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Identification of residual metabolic-active areas within individual NSCLC tumours using a pre-radiotherapy (18)Fluorodeoxyglucose-PET-CT scan.

Aerts Hugo J W L HJ van Baardwijk Angela A W AA Petit Steven F SF Offermann Claudia C Loon Judith van Jv Houben Ruud R Dingemans Anne-Marie C AM Wanders Rinus R Boersma Liesbeth L Borger Jacques J Bootsma Gerben G Geraedts Wiel W Pitz Cordula C Simons Jean J Wouters Bradly G BG Oellers Michel M Lambin Philippe P Bosmans Geert G Dekker Andre L A J AL De Ruysscher Dirk D

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 20090328 3

<h4>Background and purpose</h4>Non-small cell lung cancer (NSCLC) tumours are mostly heterogeneous. We hypothesized that areas within the tumour with a high pre-radiation (18)F-deoxyglucose (FDG) uptake, could identify residual metabolic-active areas, ultimately enabling selective-boosting of tumour sub-volumes.<h4>Material and methods</h4>Fifty-five patients with inoperable stage I-III NSCLC treated with chemo-radiation or with radiotherapy alone were included. For each patient one pre-radiothe ...[more]

PMID: 19329207

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Project description:PurposeTo investigate the performance of pretreatment fluorine 18 (18F) fluorodeoxyglucose PET/CT radiomics in predicting severe immune-related adverse events (irSAEs) among patients with advanced non-small cell lung cancer (NSCLC) treated with immunotherapy, which is important in optimizing treatment plans and alleviating future complications with early interventions.Materials and methodsThe retrospective arm of this study included 146 patients with histologically confirmed stage IIIB-IV NSCLC who were treated with immune checkpoint blockade between June 2011 and December 2017 and who were split into training (n = 97) and test (n = 49) cohorts. A prospective validation arm enrolled 48 patients before initiation of immunotherapy between January 2018 and June 2019 as an independent test cohort. Radiomics features extracted from baseline (preimmunotherapy treatment) PET, CT, and PET/CT fusion images were used to generate a radiomics score (RS) to quantify patient risk for developing irSAEs by an improved least absolute shrinkage and selection operator method. Weighted multivariable logistic regression analysis was then used to develop a nomogram model to predict irSAEs, which was assessed by its calibration, discrimination, and clinical usefulness.ResultsThe radiomics nomogram, incorporating the RS, type of immune checkpoint blockade, and dosing schedule, was able to predict patients with and without irSAEs with area under the receiver operating characteristic curve of 0.92 (95% confidence interval [CI]: 0.86, 0.98), 0.92 (95% CI: 0.86, 0.99), and 0.88 (95% CI: 0.78, 0.97) in the training, test, and prospective validation cohorts, respectively. Decision curve analysis showed that the radiomics nomogram model had the highest overall net benefit.ConclusionA high RS is a significant risk factor for development of irSAEs, demonstrating the value of PET/CT images in predicting irSAEs. By the identification, at baseline, of patients with NSCLC most likely to have irSAEs, treatment plans can be optimized before initiation of immunotherapy.Supplemental material is available for this article.© RSNA, 2020See also the commentary by Yousefi.

Project description:To compare the interobserver agreement and degree of confidence in anatomical localisation of lesions using 2-[fluorine-18]fluoro-2-deoxy-D-glucose ((18)F-FDG) positron emission tomography (PET)/computed tomography (CT) and (18)F-FDG PET alone in patients with head and neck tumours. A prospective study of 24 patients (16 male, eight female, median age 59 years) with head and neck tumours was undertaken. (18)F-FDG PET/CT was performed for staging purposes. 2D images were acquired over the head and neck area using a GE Discovery LS PET/CT scanner. (18)F-FDG PET images were interpreted by three independent observers. The observers were asked to localise abnormal (18)F-FDG activity to an anatomical territory and score the degree of confidence in localisation on a scale from 1 to 3 (1=exact region unknown; 2=probable; 3=definite). For all (18)F-FDG-avid lesions, standardised uptake values (SUVs) were also calculated. After 3 weeks, the same exercise was carried out using (18)F-FDG PET/CT images, where CT and fused volume data were made available to observers. The degree of interobserver agreement was measured in both instances. A total of six primary lesions with abnormal (18)F-FDG uptake (SUV range 7.2-22) were identified on (18)F-FDG PET alone and on (18)F-FDG PET/CT. In all, 15 nonprimary tumour sites were identified with (18)F-FDG PET only (SUV range 4.5-11.7), while 17 were identified on (18)F-FDG PET/CT. Using (18)F-FDG PET only, correct localisation was documented in three of six primary lesions, while (18)F-FDG PET/CT correctly identified all primary sites. In nonprimary tumour sites, (18)F-FDG PET/CT improved the degree of confidence in anatomical localisation by 51%. Interobserver agreement in assigning primary and nonprimary lesions to anatomical territories was moderate using (18)F-FDG PET alone (kappa coefficients of 0.45 and 0.54, respectively), but almost perfect with (18)F-FDG PET/CT (kappa coefficients of 0.90 and 0.93, respectively). We conclude that (18)F-FDG PET/CT significantly increases interobserver agreement and confidence in disease localisation of (18)F-FDG-avid lesions in patients with head and neck cancers.

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Dataset Information

Identification of residual metabolic-active areas within individual NSCLC tumours using a pre-radiotherapy (18)Fluorodeoxyglucose-PET-CT scan.

Publications

Identification of residual metabolic-active areas within individual NSCLC tumours using a pre-radiotherapy (18)Fluorodeoxyglucose-PET-CT scan.

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