Texture Analysis as Imaging Biomarker of Tumoral Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients Studied with 3-T Magnetic Resonance

Cecco, Carlo N. De; Ganeshan, Balaji; Ciolina, Maria; Rengo, Marco; Meinel, Felix G.; Musio, Daniela; Felice, Francesca De; Raffetto, Nicola; Tombolini, Vincenzo; Laghi, Andréa

doi:10.1097/rli.0000000000000116

Cited by 173 publications

(140 citation statements)

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“…macroscopic heterogeneity). In cancer, changes in image texture are associated with hypoxia, angiogenesis, cellular proliferation, tumour grade, genetic mutation status [12, 13], and with prognosis and treatment response [14, 15]. …”

Section: Introductionmentioning

confidence: 99%

MRI texture analysis (MRTA) of T2-weighted images in Crohn’s disease may provide information on histological and MRI disease activity in patients undergoing ileal resection

et al. 2016

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ObjectivesTo associate MRI textural analysis (MRTA) with MRI and histological Crohn’s disease (CD) activity.MethodsSixteen patients (mean age 39.5 years, 9 male) undergoing MR enterography before ileal resection were retrospectively analysed. Thirty-six small (≤3 mm) ROIs were placed on T2-weighted images and location-matched histological acute inflammatory scores (AIS) measured. MRI activity (mural thickness, T2 signal, T1 enhancement) (CDA) was scored in large ROIs. MRTA features (mean, standard deviation, mean of positive pixels (MPP), entropy, kurtosis, skewness) were extracted using a filtration histogram technique. Spatial scale filtration (SSF) ranged from 2 to 5 mm. Regression (linear/logistic) tested associations between MRTA and AIS (small ROIs), and CDA/constituent parameters (large ROIs).ResultsSkewness (SSF = 2 mm) was associated with AIS [regression coefficient (rc) 4.27, p = 0.02]. Of 120 large ROI analyses (for each MRI, MRTA feature and SSF), 15 were significant. Entropy (SSF = 2, 3 mm) and kurtosis (SSF = 3 mm) were associated with CDA (rc 0.9, 1.0, −0.45, p = 0.006–0.01). Entropy and mean (SSF = 2–4 mm) were associated with T2 signal [odds ratio (OR) 2.32–3.16, p = 0.02–0.004], [OR 1.22–1.28, p = 0.03–0.04]. MPP (SSF = 2 mm) was associated with mural thickness (OR 0.91, p = 0.04). Kurtosis (SSF = 3 mm), standard deviation (SSF = 5 mm) were associated with decreased T1 enhancement (OR 0.59, 0.42, p = 0.004, 0.007).ConclusionsMRTA features may be associated with CD activity.Key Points• MR texture analysis features may be associated with Crohn’s disease histological activity.• Texture analysis features may correlate with MR-dependent Crohn’s disease activity scores.• The utility of MR texture analysis in Crohn’s disease merits further investigation.Electronic supplementary materialThe online version of this article (doi:10.1007/s00330-016-4324-4) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

MRI texture analysis (MRTA) of T2-weighted images in Crohn’s disease may provide information on histological and MRI disease activity in patients undergoing ileal resection

et al. 2016

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“…It was reported that tumour heterogeneity assessed by the coefficient of variation was superior to the conventional parameters and was an important predictive factor of the pathologic response. 95 Two more recent studies evaluated the performance of texture analysis on MR images; in particular, De Cecco et al 96 considered textural features estimated on T2w-MRI acquired before and at midtreatment, whereas Nie et al 97 evaluated multiparametric MRI (T 1 weighted-MRI, T2w-MRI, DW-MRI and DCE-MRI) acquired before CRT. They both concluded that radiomic analysis performed on MRI images may improve the prediction of the pathologic response of rectal cancer to treatment.…”

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

120

106

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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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“…This reduction in T2 signal (together with a decrease in tumor size) may arise because of fibrotic response (replacement of neoplasm by fibrosis) to chemoradiation treatment (21). With the availability of spatially mapped annotations of these pathologies onto MRI, the results of our study may thus have further implications in the development of computerized imaging features to quantitatively capture subtle tissue characteristics on in vivo MRI (22–25). …”

Section: Discussionmentioning

confidence: 98%

Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging

Antunes¹,

Viswanath²,

Brady³

et al. 2018

Academic Radiology

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Rationale and Objectives: The objective of this study was to develop and quantitatively evaluate a radiology-pathology fusion method for spatially mapping tissue regions corresponding to different chemoradiation therapy-related effects from surgically excised whole-mount rectal cancer histopathology onto preoperative magnetic resonance imaging (MRI). Materials and Methods: This study included six subjects with rectal cancer treated with chemoradiation therapy who were then imaged with a 3-T T2-weighted MRI sequence, before undergoing mesorectal excision surgery. Excised rectal specimens were sectioned, stained, and digitized as two-dimensional (2D) whole-mount slides. Annotations of residual disease, ulceration, fibrosis, muscularis propria, mucosa, fat, inflammation, and pools of mucin were made by an expert pathologist on digitized slide images. An expert radiologist and pathologist jointly established corresponding 2D sections between MRI and pathology images, as well as identified a total of 10 corresponding landmarks per case (based on visually similar structures) on both modalities (five for driving registration and five for evaluating alignment). We spatially fused the in vivo MRI and ex vivo pathology images using landmark-based registration. This allowed us to spatially map detailed annotations from 2D pathology slides onto corresponding 2D MRI sections. Results: Quantitative assessment of coregistered pathology and MRI sections revealed excellent structural alignment, with an overall deviation of 1.50 ± 0.63 mm across five expert-selected anatomic landmarks (in-plane misalignment of two to three pixels at 0.67- to 1.00-mm spatial resolution). Moreover, the T2-weighted intensity distributions were distinctly different when comparing fibrotic tissue to perirectal fat (as expected), but showed a marked overlap when comparing fibrotic tissue and residual rectal cancer. Conclusions: Our fusion methodology enabled successful and accurate localization of post-treatment effects on in vivo MRI.

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Texture Analysis as Imaging Biomarker of Tumoral Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients Studied with 3-T Magnetic Resonance

Abstract: Texture parameters derived from T2w images of rectal cancer have the potential to act as imaging biomarkers of tumoral response to neoadjuvant CRT.

Cited by 173 publications

References 31 publications

MRI texture analysis (MRTA) of T2-weighted images in Crohn’s disease may provide information on histological and MRI disease activity in patients undergoing ileal resection

MRI texture analysis (MRTA) of T2-weighted images in Crohn’s disease may provide information on histological and MRI disease activity in patients undergoing ileal resection

Texture analysis of medical images for radiotherapy applications

Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging

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