Locoregional Control of Non-Small Cell Lung Cancer in Relation to Automated Early Assessment of Tumor Regression on Cone Beam Computed Tomography

Brink, Carsten; Bernchou, U.; Bertelsen, Anders; Hansen, Olfred; Schytte, Tine; Bentzen, Søren M.

doi:10.1016/j.ijrobp.2014.03.038

Cited by 61 publications

(78 citation statements)

References 15 publications

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“…In addition, only 9% of cases were manually delineated; therefore, most of the analyses relied on a nonvalidated automated model. Furthermore, this study did not correlate final TV at follow-up with tumor regression during RT as a final confirmation of tumor response after therapy (16). By contrast, Bral et al (17) evaluated MVCT-based assessment of NSCLC treated with 2 different radiation schemas, including a hypofractionated regimen, and in which about half of the patients received RT alone.…”

Section: Discussionmentioning

confidence: 62%

“…Standard CT scans during and after RT using a deformable registration model revealed progressive tumor shrinkage after RT (15), similar to our findings. Brink et al (16) used an automated model to assess TV regression using kV CBCT and showed that pronounced TV regression correlated with worse survival. However, about 30% of patients did not receive concurrent chemotherapy.…”

Section: Discussionmentioning

confidence: 99%

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Reduction in Tumor Volume by Cone Beam Computed Tomography Predicts Overall Survival in Non-Small Cell Lung Cancer Treated With Chemoradiation Therapy

Jabbour

Kim

Haider

et al. 2015

International Journal of Radiation Oncology*Biology*Physics

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Purpose We sought to evaluate whether tumor response using cone beam computed tomography (CBCT) performed as part of the routine care during chemoradiation therapy (CRT) could forecast the outcome of unresectable, locally advanced, non-small cell lung cancer (NSCLC). Methods and Materials We manually delineated primary tumor volumes (TV) of patients with NSCLC who were treated with radical CRT on days 1, 8, 15, 22, 29, 36, and 43 on CBCTs obtained as part of the standard radiation treatment course. Percentage reductions in TV were calculated and then correlated to survival and pattern of recurrence using Cox proportional hazard models. Clinical information including histologic subtype was also considered in the study of such associations. Results We evaluated 38 patients with a median follow-up time of 23.4 months. The median TV reduction was 39.3% (range, 7.3%-69.3%) from day 1 (D1) to day 43 (D43) CBCTs. Overall survival was associated with TV reduction from D1 to D43 (hazard ratio [HR] 0.557, 95% CI 0.39–0.79, P=.0009). For every 10% decrease in TV from D1 to D43, the risk of death decreased by 44.3%. For patients whose TV decreased ≤39.3 or <39.3%, log-rank test demonstrated a separation in survival (P=.02), with median survivals of 31 months versus 10 months, respectively. Neither local recurrence (HR 0.791, 95% CI 0.51–1.23, P=.29), nor distant recurrence (HR 0.78, 95% CI 0.57–1.08, P=.137) correlated with TV decrease from D1 to D43. Histologic subtype showed no impact on our findings. Conclusions TV reduction as determined by CBCT during CRT as part of routine care predicts post-CRT survival. Such knowledge may justify intensification of RT or application of additional therapies. Assessment of genomic characteristics of these tumors may permit a better understanding of behavior or prediction of therapeutic outcomes.

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Section: Discussionmentioning

confidence: 62%

Section: Discussionmentioning

confidence: 99%

Reduction in Tumor Volume by Cone Beam Computed Tomography Predicts Overall Survival in Non-Small Cell Lung Cancer Treated With Chemoradiation Therapy

Jabbour

Kim

Haider

et al. 2015

International Journal of Radiation Oncology*Biology*Physics

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show abstract

“…17 Unfortunately, no measured CBCT cut-off tumour response was determined for a better understanding of the behaviour or prediction of therapeutic outcomes. Conversely, Brink et al 32 showed a rather controversial result that greater tumour reduction during RT is unfavourable in terms of locoregional control and OS for nonadenocarcinoma histologies, supposing that the rapid tumour shrinkage during RT could be an indicator of tumour aggressiveness (in terms of high kinetic proliferative).…”

Section: Discussionmentioning

confidence: 99%

Cone-beam computed tomography in lung stereotactic ablative radiation therapy: predictive parameters of early response

Mazzola

Fiorentino

Ricchetti

et al. 2016

BJR

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“…The main steps in assessing density changes in healthy lung tissue from CBCT and follow-up CT image data and relating this to the locally delivered dose have been described in detail elsewhere [3,6,9]. Briefly, deformable image registrations were performed using the elastix freeware toolbox [10].…”

Section: Image Registrationmentioning

confidence: 99%

Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients

Bernchou¹,

Hansen²,

Schytte³

et al. 2015

Radiotherapy and Oncology

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Locoregional Control of Non-Small Cell Lung Cancer in Relation to Automated Early Assessment of Tumor Regression on Cone Beam Computed Tomography

Cited by 61 publications

References 15 publications

Reduction in Tumor Volume by Cone Beam Computed Tomography Predicts Overall Survival in Non-Small Cell Lung Cancer Treated With Chemoradiation Therapy

Reduction in Tumor Volume by Cone Beam Computed Tomography Predicts Overall Survival in Non-Small Cell Lung Cancer Treated With Chemoradiation Therapy

Cone-beam computed tomography in lung stereotactic ablative radiation therapy: predictive parameters of early response

Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients

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