CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy

Kuno, Hirofumi; Qureshi, Muhammad M.; Chapman, Margaret N.; Li, B.; Arasa, Vanessa Carlota Andreu; Onoue, Keita; Truong, M.T.; Sakai, Osamu

doi:10.3174/ajnr.a5407

Cited by 68 publications

(56 citation statements)

References 47 publications

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“…This postprocessing tool can be applied retrospectively to all images acquired in clinical routine. 26,27 However, lack of standardized software, evolving research, and variable numeric algorithms currently limit the use of these new promising tools in clinical routine.…”

Section: Discussionmentioning

confidence: 99%

MRI with DWI for the Detection of Posttreatment Head and Neck Squamous Cell Carcinoma: Why Morphologic MRI Criteria Matter

Ailianou¹,

Mundada²,

Perrot³

et al. 2018

AJNR Am J Neuroradiol

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Section: Discussionmentioning

confidence: 99%

MRI with DWI for the Detection of Posttreatment Head and Neck Squamous Cell Carcinoma: Why Morphologic MRI Criteria Matter

Ailianou¹,

Mundada²,

Perrot³

et al. 2018

AJNR Am J Neuroradiol

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“…The high homogeneity of PET-CT images also was revealed as predictors of progression-free survival in pharynx cancer [33]. In terms of third order metrics, significant differences of GLRLM features were found between regional control group and local recurrence group in HNSCC patients treated with chemoradiotherapy [16].…”

Section: Discussionmentioning

confidence: 91%

“…Although the individual CT texture parameters have showed significant predictive role of survival and treatment failure in head and neck squamous cell carcinoma (HNSCC) [15,16]. The application of radiomics signature combined with multiple CT texture markers in LSCC patients has not been well discussed.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of CT-based radiomics signature and nomogram as prognostic markers in patients with laryngeal squamous cell carcinoma

et al. 2020

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Background: The aim of this study was to evaluate the prognostic value of radiomics signature and nomogram based on contrast-enhanced computed tomography (CT) in patients after surgical resection of laryngeal squamous cell carcinoma (LSCC). Methods: All patients (n = 136) were divided into the training cohort (n = 96) and validation cohort (n = 40). The LASSO regression method was performed to construct radiomics signature from CT texture features. Then a radiomics nomogram incorporating the radiomics signature and clinicopathologic factors was established to predict overall survival (OS). The validation of nomogram was evaluated by calibration curve, concordance index (C-index) and decision curve. Results: Based on three selected texture features, the radiomics signature showed high C-indexes of 0.782 (95%CI: 0.656-0.909) and 0.752 (95%CI, 0.614-0.891) in the two cohorts. The radiomics nomogram had significantly better discrimination capability than cancer staging in the training cohort (C-index, 0.817 vs. 0.682; P = 0.009) and validation cohort (C-index, 0.913 vs. 0.699; P = 0.019), as well as a good agreement between predicted and actual survival in calibration curves. Decision curve analysis also suggested improved clinical utility of radiomics nomogram. Conclusions: Radiomics signature and nomogram showed favorable prediction accuracy for OS, which might facilitate the individualized risk stratification and clinical decision-making in LSCC patients.

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“…Measures of texture analysis such as smoothness and regularity in pixels represent both distributions and relationships in gray-level patterns [27]. Texture analysis has been applied to the field of oncology to analyze predictors, treatment responses, and histologic classification [28][29][30][31][32]. Heterogeneity in the malignant tissues is recognized to reflect cellularity, necrosis, and angiogenesis, which are associated with disorders of attenuation [33].…”

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confidence: 99%

Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions

Tomita

Kuno

Koike

et al. 2020

International Journal of Endocrinology

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Background and Objectives. Thyroid nodules are increasingly being detected during cross-sectional imaging of the neck and chest. The purpose of this study is to investigate the efficacy of dual-energy computed tomography (DECT) using iodine concentration measurement and multiparametric texture analysis of monochromatic images for differentiating between benign and malignant thyroid nodules. Materials and Methods. This retrospective study included 34 consecutive patients who presented with thyroid nodules and underwent noncontrast DECT between 2015 and 2016. Manual segmentation of each thyroid nodule by monochromatic imaging (40, 60, and 80 keV) was performed, and an in-house developed MATLAB-based texture analysis program was used to extract 41 textures. Iodine material decomposition and CT attenuation slopes were also measured. Histopathologic findings of ultrasound-guided biopsies over a follow-up period of at least one year were used as reference standards. Basic descriptive statistics and areas under receiver operating characteristic curves (AUCs) were evaluated. Results. The 34 nodules comprised 14 benign nodules and 20 malignant nodules. Iodine content and Hounsfield unit curve slopes did not differ significantly between benign and malignant thyroid nodules (P=0.480–0.670). However, significant differences in the texture features of monochromatic images were observed between benign and malignant nodules: histogram mean and median, co-occurrence matrix contrast, gray-level gradient matrix (GLGM) skewness, and mean gradients and variance of gradients for GLGM at 80 keV (P=0.014–0.044). The highest AUC was 0.77, for the histogram mean and median of images acquired at 80 keV. Conclusions. Texture features extracted from monochromatic images using DECT, specifically acquired at high keV, may be a promising diagnostic approach for thyroid nodules. A further large study for incidental thyroid nodules using DECT texture analysis is required to validate our results.

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CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy

Abstract: Independent primary tumor CT texture analysis parameters are associated with local failure in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy.

Cited by 68 publications

References 47 publications

MRI with DWI for the Detection of Posttreatment Head and Neck Squamous Cell Carcinoma: Why Morphologic MRI Criteria Matter

MRI with DWI for the Detection of Posttreatment Head and Neck Squamous Cell Carcinoma: Why Morphologic MRI Criteria Matter

Evaluation of CT-based radiomics signature and nomogram as prognostic markers in patients with laryngeal squamous cell carcinoma

Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions

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