To evaluate the clinical usefulness of dual-energy computed tomography (CT) with weighted-average (WA) images and iodine overlay (IO) images in the evaluation of laryngeal cartilage invasion in patients with laryngeal and hypopharyngeal squamous cell carcinoma (SCC). The institutional review board approved this retrospective study, and written comprehensive consent was obtained from all patients. Seventy-two consecutive patients underwent 128-section dual-source dual-energy CT to stage laryngeal (n=27) or hypopharyngeal (n=45) cancer. Three observers who were blinded to the patients' clinical histories and histopathologic findings evaluated cartilage invasion on WA images alone or in combination with IO images (nonossified cartilages were selectively evaluated on IO images) by using a five-point scale. Thirty of the 72 patients (42%) underwent surgery, and findings from histopathologic examination in those patients were used as the standard of reference for the evaluation of diagnostic performance with receiver operating characteristic (ROC) curve analysis and in terms of sensitivity and specificity. Interobserver reproducibility was calculated with κ statistics. For thyroid cartilage, the area under the ROC curve (AUC) of the WA plus IO images was marginally larger than that for WA images alone (AUC=0.957 vs 0.870, respectively; P=.075). The specificity of WA plus IO images was significantly superior to that of WA images alone (96% vs 70%, respectively; P=.031), with no compromise to the sensitivity (86% for both). For thyroid and cricoid cartilages, the interobserver reproducibility was higher for diagnoses made with WA plus IO images (κ=0.68-0.72 and 0.64-0.79, respectively) than for those made with WA images alone (κ=0.29-0.56 and 0.20-0.64, respectively). Combined analysis of WA and IO images obtained with dual-energy CT improves the diagnostic performance and interobserver reproducibility of evaluations of laryngeal cartilage invasion by SCC.

BACKGROUND AND PURPOSE: The accurate prediction of prognosis and failure is crucial for optimizing treatment strategies for patients with cancer. The purpose of this study was to assess the performance of pretreatment CT texture analysis for the prediction of treatment failure in primary head and neck squamous cell carcinoma treated with chemoradiotherapy. MATERIALS AND METHODS: This retrospective study included 62 patients diagnosed with primary head and neck squamous cell carcinoma who underwent contrast-enhanced CT examinations for staging, followed by chemoradiotherapy. CT texture features of the whole primary tumor were measured using an in-house developed Matlab-based texture analysis program. Histogram, gray-level co-occurrence matrix, gray-level run-length, gray-level gradient matrix, and Laws features were used for texture feature extraction. Receiver operating characteristic analysis was used to identify the optimal threshold of any significant texture parameter. We used multivariate Cox proportional hazards models to examine the association between the CT texture parameter and local failure, adjusting for age, sex, smoking, primary tumor stage, primary tumor volume, and human papillomavirus status. RESULTS: Twenty-two patients (35.5%) developed local failure, and the remaining 40 (64.5%) showed local control. Multivariate analysis revealed that 3 histogram features (geometric mean [hazard ratio = 4.68, P = .026], harmonic mean [hazard ratio = 8.61, P = .004], and fourth moment [hazard ratio = 4.56, P = .048]) and 4 gray-level run-length features (short-run emphasis [hazard ratio = 3.75, P = .044], gray-level nonuniformity [hazard ratio = 5.72, P = .004], run-length nonuniformity [hazard ratio = 4.15, P = .043], and short-run low gray-level emphasis [hazard ratio = 5.94, P = .035]) were significant predictors of outcome after adjusting for clinical variables. CONCLUSIONS: Independent primary tumor CT texture analysis parameters are associated with local failure in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy.

BACKGROUND AND PURPOSE: Dual-energy CT can distinguish iodine-enhanced tumors from nonossified cartilage and has been investigated for evaluating cartilage invasion in patients with laryngeal and hypopharyngeal squamous cell carcinomas. In this study, we compared the diagnostic accuracy of MR imaging and of a combination of weighted-average and iodine overlay dual-energy CT images in detecting cartilage invasion by laryngeal and hypopharyngeal squamous cell carcinomas, in particular thyroid cartilage invasion. MATERIALS AND METHODS: Fifty-five consecutive patients who underwent 3T MR imaging and 128-slice dual-energy CT for preoperative initial staging of laryngeal or hypopharyngeal squamous cell carcinomas were included. Two blinded observers evaluated laryngeal cartilage invasion on MR imaging and dual-energy CT using a combination of weighted-average and iodine-overlay images. Pathologic findings of surgically resected specimens were used as the reference standard for evaluating sensitivity, specificity, and the areas under the receiver operating characteristic curve of both modalities for cartilage invasion by each type of cartilage and for all cartilages together. Sensitivity and specificity were compared using the McNemar test and generalized linear mixed models. RESULTS: Dual-energy CT showed higher specificity than MR imaging for diagnosing all cartilage together (84% for MR imaging versus 98% for dual-energy CT, P < .004) and for thyroid cartilage (64% versus 100%, P < .001), with a similar average area under the curve (0.94 versus 0.95, P = .70). The sensitivity did not differ significantly for all cartilages together (97% versus 81%, P = .16) and for thyroid cartilage (100% versus 89%, P = .50), though there was a trend toward increased sensitivity with MR imaging. CONCLUSIONS: Dual-energy CT showed higher specificity and acceptable sensitivity in diagnosing laryngeal cartilage invasion compared with MR imaging.

SUMMARY: Our aim was to evaluate changes in texture features based on variations in CT parameters on a phantom. Scans were performed with varying milliampere, kilovolt, section thickness, pitch, and acquisition mode. Forty-two texture features were extracted by using an in-house-developed Matlab program. Two-tailed t tests and false-detection analyses were performed with significant differences in texture features based on detector array configurations (Q values = 0.001–0.006), section thickness (Q values = 0.0002–0.001), and acquisition mode (Q values = 0.003–0.006). Variations in milliampere and kilovolt had no significant effect.

The 2021 World Health Organization (WHO) classification system for thoracic tumors (including lung cancer) contains several updates to the 2015 edition. Revisions for lung cancer include a new grading system for invasive nonmucinous adenocarcinoma that better reflects prognosis, reorganization of squamous cell carcinomas and neuroendocrine neoplasms, and description of some new entities. Moreover, remarkable advancements in our knowledge of genetic mutations and targeted therapies have led to a much greater emphasis on genetic testing than that in 2015. In 2015, guidelines recommended evaluation of only two driver mutations, ie, epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) fusions, in patients with nonsquamous non-small cell lung cancer. The 2021 guidelines recommend testing for numerous additional gene mutations for which targeted therapies are now available including ROS1, RET, NTRK1-3, KRAS, BRAF, and MET. The correlation of imaging features and genetic mutations is being studied. Testing for the immune biomarker programmed death ligand 1 is now recommended before starting first-line therapy in patients with metastatic non-small cell lung cancer. Because 70% of lung cancers are unresectable at patient presentation, diagnosis of lung cancer is usually based on small diagnostic samples (ie, biopsy specimens) rather than surgical resection specimens. The 2021 version emphasizes differences in the histopathologic interpretation of small diagnostic samples and resection specimens. Radiologists play a key role not only in evaluation of tumor and metastatic disease but also in identification of optimal biopsy targets. ^©RSNA, 2024 Test Your Knowledge questions in the supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.