CT characteristics allow identification of patient-specific susceptibility for radiation-induced lung damage

Defraene, Gilles; Elmpt, Wouter van; Crijns, Wouter; Slagmolen, Pieter; Ruysscher, Dirk De

doi:10.1016/j.radonc.2015.07.033

Cited by 48 publications

(49 citation statements)

References 35 publications

(79 reference statements)

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“…CT-based quantitative imaging applied for lung cancer SBRT patients has focussed primarily on patient radiosensitivity and radiation toxicity [28][29][30][31][32]. Recently, a study by Mattonen et al used CT texture analysis to identify a predictor of tumor recurrence in 22 NSCLC patients treated with SBRT [31].…”

Section: Discussionmentioning

confidence: 99%

“…While quantitative CT imaging has been well reported for lung cancer diagnosis and management [27], there are a limited number of studies on predicting outcomes in lung cancer patients undergoing SBRT [28][29][30][31][32]. Analysis of baseline Hounsfield Units (HU) and changes in HU or textural features after SBRT have been investigated as prognostic indicators for radiation-induced lung damage [28][29][30]32] and recurrence [31]. These studies have been limited in their reproducibility and prognostic power prior to SBRT, which would be important for optimizing individualized treatment plans to improve prognosis and/or prevent recurrent disease.…”

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confidence: 99%

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CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer

Huynh

Coroller

Narayan

et al. 2016

Radiotherapy and Oncology

173

126

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer

Huynh

Coroller

Narayan

et al. 2016

Radiotherapy and Oncology

173

126

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“…6 Although most parts of the works in this context faced the detection of RILI by the evaluation of simple CT ; Pota et al, 2015 103 CRT, chemoradiotherapy; DCE-MRI, dynamic contrast-enhanced MRI; EBRT, external beam radiotherapy; IMRT, intensity-modulated radiotherapy; mp-MRI, multiparametric MRI; PET, positron emission tomography; RT, radiotherapy; SABR, stereotactic ablative radiation therapy; SRT, stereotactic radiotherapy; T2w, T 2 weighted. density, [76][77][78] Mattonen et al [79][80][81] proposed texture analysis for an automatic classification of tumour recurrence and lung injuries. They found a radiomic signature consisting of five textural features (minimum grey level, grey-level uniformity, GLCM homogeneity, GLCM correlation and GLCM energy) after stereotactic ablative radiation therapy (SABR) in consolidative and periconsolidative regions.…”

Section: Application Of Texture Analysis In Radiotherapymentioning

confidence: 99%

Texture analysis of medical images for radiotherapy applications

Scalco¹,

Rizzo²

2017

The British Journal of Radiology

127

108

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The high-throughput extraction of quantitative information from medical images, known as radiomics, has grown in interest due to the current necessity to quantitatively characterize tumour heterogeneity. In this context, texture analysis, consisting of a variety of mathematical techniques that can describe the grey-level patterns of an image, plays an important role in assessing the spatial organization of different tissues and organs. For these reasons, the potentiality of texture analysis in the context of radiotherapy has been widely investigated in several studies, especially for the prediction of the treatment response of tumour and normal tissues. Nonetheless, many different factors can affect the robustness, reproducibility and reliability of textural features, thus limiting the impact of this technique. In this review, an overview of the most recent works that have applied texture analysis in the context of radiotherapy is presented, with particular focus on the assessment of tumour and tissue response to radiations. Preliminary, the main factors that have an influence on features estimation are discussed, highlighting the need of more standardized image acquisition and reconstruction protocols and more accurate methods for region of interest identification. Despite all these limitations, texture analysis is increasingly demonstrating its ability to improve the characterization of intratumour heterogeneity and the prediction of clinical outcome, although prospective studies and clinical trials are required to draw a more complete picture of the full potential of this technique.

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“…Quantification of lung density changes has been investigated for patient-specific susceptibility of radiation-induced lung damage following SABR [64]. A recent study by Ghobadi et al [65] showed that the combination of mean density changes with the standard deviation of the density was a more sensitive and specific method to assess radiationinduced lung damage than measuring differences in mean density.…”

Section: Sensitivity (%) Specificity (%)mentioning

confidence: 99%

Pulmonary imaging after stereotactic radiotherapy—does RECIST still apply?

Mattonen¹,

Ward²,

Palma³

2016

BJR

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The use of stereotactic ablative radiotherapy (SABR) for the treatment of primary lung cancer and metastatic disease is rapidly increasing. However, the presence of benign fibrotic changes on CT imaging makes response assessment following SABR a challenge, as these changes develop with an appearance similar to tumour recurrence. Misclassification of benign fibrosis as local recurrence has resulted in unnecessary interventions, including biopsy and surgical resection. Response evaluation criteria in solid tumours (RECIST) are widely used as a universal set of guidelines to assess tumour response following treatment. However, in the context of non-spherical and irregular post-SABR fibrotic changes, the RECIST criteria can have several limitations. Positron emission tomography can also play a role in response assessment following SABR; however, false-positive results in regions of inflammatory lung post-SABR can be a major clinical issue and optimal standardized uptake values to distinguish fibrosis and recurrence have not been determined. Although validated CT high-risk features show a high sensitivity and specificity for predicting recurrence, most recurrences are not detected until more than 1-year post-treatment. Advanced quantitative radiomic analysis on CT imaging has demonstrated promise in distinguishing benign fibrotic changes from local recurrence at earlier time points, and more accurately, than physician assessment. Overall, the use of RECIST alone may prove inferior to novel metrics of assessing response.

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CT characteristics allow identification of patient-specific susceptibility for radiation-induced lung damage

Cited by 48 publications

References 35 publications

CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer

CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer

Texture analysis of medical images for radiotherapy applications

Pulmonary imaging after stereotactic radiotherapy—does RECIST still apply?

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