The complex relationship between lung tumor volume and survival in patients with non-small cell lung cancer treated by definitive radiotherapy: A prospective, observational prognostic factor study of the Trans-Tasman Radiation Oncology Group (TROG 99.05)

Ball, David; Fisher, Richard; Burmeister, Bryan; Poulsen, Michael; Graham, Peter; Penniment, Michael; Vinod, Shalini; Krawitz, Hedley; Joseph, David; Wheeler, Greg; McClure, Bev

doi:10.1016/j.radonc.2012.12.003

Cited by 67 publications

(57 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast to these and our own results, is the work of Ball et al (24) who did not find significant prognostic information provided by tumor volume in the RT of NSCLC.…”

Section: Opn T0 To T1 ----------------------------------------------contrasting

confidence: 99%

The relationship between tumor volume changes and serial plasma osteopontin detection during radical radiotherapy of non-small-cell lung cancer

et al. 2016

View full text Add to dashboard Cite

Abstract. The prognostic quality of increased osteopontin (OPN) plasma levels has been demonstrated for the chemotherapy and surgery of lung cancer. There is also evidence in the literature that tumor volume impacts prognosis in definitive radiotherapy (RT) of (lung) cancer. We previously demonstrated that elevated plasma levels of OPN before, and increasing OPN plasma levels after RT significantly correlate with survival and outcome after curative-intent RT of non-small-cell lung cancer (NSCLC). Tumor volume was also associated with prognosis. The present prospective clinical study investigated the prognostic interrelation of OPN plasma levels and tumor volume and their changes in the radical RT of NSCLC. We evaluated a subset of patients (n=27) with inoperable, non-metastasized NSCLC of the previously published patient collective. Patients were treated with radical radiochemotherapy (2 Gy ad 66 Gy). OPN plasma concentrations were determined by ELISA before (t0), at the end (t1), and 4 weeks after RT (t2). GTV was delineated PET-and CT-correlated before RT (GTV1) and after 40 Gy (GTV2). The course of OPN during and after RT and the change of GTV during RT was monitored over time and correlated with prognosis. Median GTV2 after 40 Gy (63 ml) was significantly lower than pre-RT GTV1 (90 ml, P<0.0001). Median OPN before (t0), at the end of (t1) and four weeks after RT (t2) was 846, 777 and 624 ng/ml and not significantly different. GTV significantly declined by 39 ml during RT (P<0.0001) and OPN non-significantly decreased by 56 ng/ml during (t0 to t1) and by 54 ng/ml after RT (t1 to t2). No correlations were determined between absolute OPN and GTV values or their relative changes during RT. In univariate analysis, only GTV2 significantly predicted overall survival (OS, P=0.03). In multivariate analysis, both OPN t1 (P<0.001) and GTV2 (P= 0.001) remained significant predictors of OS. Relative OPN plasma level changes after (t1 to t2) and GTV changes during RT (GTV 1 to GTV 2) significantly predicted OS (P=0.02). The combination of absolute GTV values before RT (GTV1) and GTV changes during RT (GTV1 to 2) were significantly associated with OS in both uni-and multivariate analysis (P=0.03). The combination of absolute OPN plasma levels and their changes with GTV and its changes did not reach statistical significance. The lack of a significant correlation between OPN and GTV together with the finding that OPN and GTV remained independent predictors of survival outcome but were not associated with OS in combination supports the hypothesis that tumor volume (GTV) and OPN plasma levels (both their changes and absolute values) are not interrelated in terms of prognosis but do possess each parameter separately, a prognostic quality in the radical RT of NSCLC which justifies further prospective studies to validate these results.

show abstract

“…In contrast to these and our own results, is the work of Ball et al (24) who did not find significant prognostic information provided by tumor volume in the RT of NSCLC.…”

Section: Opn T0 To T1 ----------------------------------------------contrasting

confidence: 99%

The relationship between tumor volume changes and serial plasma osteopontin detection during radical radiotherapy of non-small-cell lung cancer

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Routinely, basic metrics are extracted from these images to utilize as a prognostic factor [27–30], or to assess treatment response. However, there is much more tumor phenotypic information captured in these images.…”

Section: Discussionmentioning

confidence: 99%

“…We evaluated the ability of radiomic features to predict DM or overall survival, and how these features compare with basic metrics (e.g. volume, diameter) as prognostic factors [27–30]. …”

Section: Introductionmentioning

confidence: 99%

CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

Coroller

Großmann

Hou

et al. 2015

Radiotherapy and Oncology

594

467

View full text Add to dashboard Cite

Background and Purpose Radiomics provides opportunities to quantify the tumor phenotype non-invasively by applying a large number of quantitative imaging features. This study evaluates computed-tomography (CT) radiomic features for their capability to predict distant metastasis (DM) for lung adenocarcinoma patients. Material and Methods We included two datasets: 98 patients for discovery and 84 for validation. The phenotype of the primary tumor was quantified on pre-treatment CT-scans using 635 radiomic features. Univariate and multivariate analysis was performed to evaluate radiomics performance using the concordance index (CI). Results Thirty-five radiomic features were found to be prognostic (CI > 0.60, FDR < 5%) for DM and twelve for survival. It is noteworthy that tumor volume was only moderately prognostic for DM (CI=0.55, p-value=2.77 × 10−5) in the discovery cohort. A radiomic-signature had strong power for predicting DM in the independent validation dataset (CI=0.61, p-value=1.79 ×10−17). Adding this radiomic-signature to a clinical model resulted in a significant improvement of predicting DM in the validation dataset (p-value=1.56 × 10−11). Conclusions Although only basic metrics are routinely quantified, this study shows that radiomic features capturing detailed information of the tumor phenotype can be used as a prognostic biomarker for clinically-relevant factors such as DM. Moreover, the radiomic-signature provided additional information to clinical data.

show abstract

“…Not only does accurate tumor delineation have implications for the adequacy of radiotherapy, it also has a bearing on the accuracy of predicted life expectancy [3]. The delineation of a tumor is a very timeconsuming task for the specialist, and this is leading to an increase in the use of automatic or semiautomatic delineation tools.…”

Section: Discussionmentioning

confidence: 99%

“…8. In this plot, volume estimates are represented in mm 3 . As can be seen in the figure, the 95 % limits of agreement (−6170, 9270) contain 96 % of the difference scores.…”

Section: Volume Evaluationmentioning

confidence: 99%

Three-dimensional segmentation of retroperitoneal masses using continuous convex relaxation and accumulated gradient distance for radiotherapy planning

Suárez-Mejías

Pérez-Carrasco

Serrano

et al. 2016

Med Biol Eng Comput

View full text Add to dashboard Cite

An innovative algorithm has been developed for the segmentation of retroperitoneal tumors in 3D radiological images. This algorithm makes it possible for radiation oncologists and surgeons semiautomatically to select tumors for possible future radiation treatment and surgery. It is based on continuous convex relaxation methodology, the main novelty being the introduction of accumulated gradient distance, with intensity and gradient information being incorporated into the segmentation process. The algorithm was used to segment 26 CT image volumes. The results were compared with manual contouring of the same tumors. The proposed algorithm achieved 90 % sensitivity, 100 % specificity and 84 % positive predictive value, obtaining a mean distance to the closest point of 3.20 pixels. The algorithm's dependence on the initial manual contour was also analyzed, with results showing that the algorithm substantially reduced the variability of the manual segmentation carried out by different specialists. The algorithm was also compared with four benchmark algorithms (thresholding, edge-based level-set, region-based level-set and continuous max-flow with two labels). To the best of our knowledge, this is the first time the segmentation of retroperitoneal tumors for radiotherapy planning has been addressed.

show abstract

The complex relationship between lung tumor volume and survival in patients with non-small cell lung cancer treated by definitive radiotherapy: A prospective, observational prognostic factor study of the Trans-Tasman Radiation Oncology Group (TROG 99.05)

Cited by 67 publications

References 14 publications

The relationship between tumor volume changes and serial plasma osteopontin detection during radical radiotherapy of non-small-cell lung cancer

The relationship between tumor volume changes and serial plasma osteopontin detection during radical radiotherapy of non-small-cell lung cancer

CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

Three-dimensional segmentation of retroperitoneal masses using continuous convex relaxation and accumulated gradient distance for radiotherapy planning

Contact Info

Product

Resources

About