Software-Based Analysis of the Taller-Than-Wide Feature of High-Risk Thyroid Nodules.

BACKGROUND: Shape is one of the most important features in the diagnosis of malignant thyroid nodules. This characteristic has been described qualitatively, but only shapes that appear markedly different can be easily differentiated at first interpretation. This study sought to clarify whether software-based shape indexes are useful for the detection of thyroid cancers. METHODS: In the final analysis, 200 participants with 231 pathologically proven nodules participated in the study. Ultrasound features were assessed by clinicians. The tumor contour was auto-defined, and shape indexes were calculated using commercial software. RESULTS: Of the 231 nodules, 134 were benign and 97 were malignant. The presence of taller-than-wide (TTW) dimensions differed significantly between the benign and malignant thyroid tumors. Designation of TTW assessed by the software had a higher kappa value and proportional agreement than TTW assessed by clinicians. Disagreement between the clinician and software in designating nodules as TTW occurred for 28 nodules. The presence of other ultrasonic characteristics and small differences in the height and width measurements were causes for the incorrect interpretation of the TTW feature. CONCLUSION: The proposed software-based quantitative analysis of tumor shape seems to be promising as an important advance compared with conventional TTW features evaluated by operators because it allows for a more reliable and consistent distinction and is less influenced by other ultrasonic features.

Differences in the ultrasonographic appearance of thyroid nodules after radiofrequency ablation.

CONTEXT: Radiofrequency ablation (RFA) is a well-tolerated approach to treating benign thyroid nodules (TNs), but no index can predict its success. Other than size decrease, little is known about TN appearance on ultrasonography (US) after RFA. OBJECTIVE: This study aimed to (a) assess the effectiveness of single-session RFA treatment, (b) determine whether pre-ablation US characteristics correlate with its effectiveness, and (c) demonstrate TN characteristics on baseline and follow-up US. DESIGN: Retrospective cohort study among the patients who underwent single-session RFA for the treatment of benign TNs at a referral medical center between January 2018 and April 2019. PATIENTS: A total of 116 patients (137 nodules) were included in the study. MEASUREMENTS: Characteristics were quantified using commercial software. TNs were classified into 2015 American Thyroid Association (ATA) sonographic patterns and American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TI-RADS) categories. RESULTS: The average volume reduction ratio (VRR) was 74.51% in 1 year (95% confidence interval, 70.63%-78.39%). The only pre-ablation US feature significantly different between nodules with VRR <50% and VRR >50% was the cyst composition (0.05 vs. 0.02, p-value = .02). The VRR and margin change in the first 3 months after ablation were found to be leading indicators significantly correlated to the VRR in 6 months with correlation coefficients (r) = .72 and -.28 (p-value < .0001 and = .0008) and VRR in 1 year with r = .65 and -.17 (p-value < .0001 and = .046), respectively. After RFA, more TNs became ATA high suspicion (2.9% vs. 19.7%, p < .0001) and more appeared to be the non-ATA patterns (12.4% vs. 23.4%, p < .0001). Also, a greater number of post-RFA TNs were classified as ACR-TI-RADS categories 4 and 5 (40.1% vs. 70.1%, p < .0001). CONCLUSIONS: Radiofrequency ablation therapy is effective for treating TNs. Pre-ablation cyst components, 3-month post-ablation volume reduction and margin change of TNs were related to the 6-month and 1-year response. Clinicians should consider that TNs would appear peculiar on US after RFA, mistakenly suggesting malignant potential.

A 2-Phase Merge Filter Approach to Computer-Aided Detection of Breast Tumors on 3-Dimensional Ultrasound Imaging.

OBJECTIVES: The role of image analysis in 3-dimensional (3D) automated breast ultrasound (ABUS) images is increasingly important because of its widespread use as a screening tool in whole-breast examinations. However, reviewing a large number of images acquired from ABUS is time-consuming and sometimes error prone. The aim of this study, therefore, was to develop an efficient computer-aided detection (CADe) algorithm to assist the review process. METHODS: The proposed CADe algorithm consisted of 4 major steps. First, initial tumor candidates were formed by extracting and merging hypoechoic square cells on 2-dimensional (2D) transverse images. Second, a feature-based classifier was then constructed using 2D features to filter out nontumor candidates. Third, the remaining 2D candidates were merged longitudinally into 3D masses. Finally, a 3D feature-based classifier was used to further filter out nontumor masses to obtain the final detected masses. The proposed method was validated with 176 passes of breast images acquired by an Acuson S2000 automated breast volume scanner (Siemens Medical Solutions USA, Inc., Malvern, PA), including 44 normal passes and 132 abnormal passes containing 162 proven lesions (79 benign and 83 malignant). RESULTS: The proposed CADe system could achieve overall sensitivity of 100% and 90% with 6.71 and 5.14 false-positives (FPs) per pass, respectively. Our results also showed that the average number of FPs per normal pass (7.16) was more than the number of FPs per abnormal pass (6.56) at 100% sensitivity. CONCLUSIONS: The proposed CADe system has a great potential for becoming a good companion tool with ABUS imaging by ensuring high sensitivity with a relatively small number of FPs.

A Variance-reduction Approach to Detection of the Thyroid-nodule Boundary on Ultrasound Images.

To perform computer-aided diagnosis of the thyroid nodules on ultrasound images, the location and boundary of nodules should be clearly defined. However, the identification of thyroid nodule boundary is a difficult issue due to the biological characteristics of the nodules, the physics and quality of ultrasound imaging, and the subjective factors and operating conditions of the operator. In this study, we propose a novel and semiautomatic method for detecting the boundary of thyroid nodule based on the Variance-Reduction (V-R) statistics without image preprocessing. The region of interest (ROI) is first automatically generated according to the initial inputs of the nodule's major and minor axes. The boundary candidate pixel points are then extracted by using the V-R statistics from the grayscale values of all pixel points in the ROI. Three filtering methods are further applied to eliminate the outlier pixel points to ensure that the remaining candidate pixel points are located on the nodule boundary. Finally, the remaining pixel points are smoothened and linked together to form the final boundary. The proposed method is validated with ultrasound images of 538 thyroid nodules, with manual delineation by experienced radiologist as gold standard. The effectiveness is evaluated and compared with previous publications using boundary error metrics and overlapping area metrics with the same data set. The results show that the normalized average mean boundary error is 1.02%, the true positive overlapping area ratio achieves 93.66% and false positive overlapping area ratio is limited to 7.68%. In conclusion, our proposed method is reliable and effective in detecting thyroid nodule boundary on ultrasound images.

Using standardized ultrasound imaging to correlate OSA severity with tongue morphology.

BACKGROUND: Ultrasound imaging has been explored as a potential diagnostic tool for obstructive sleep apnea (OSA); we reported backscatter ultrasound imaging (BUI) of the tongue correlates with OSA severity in adults. We focus on anatomical features of the tongue using standardized ultrasonography and hypothesize that differences in morphology correlate with OSA severity. METHODS: This prospective study was IRB approved (53,172) and conducted at Stanford University Sleep Surgery Clinic. Patients ≥18 years with polysomnography (PSG) underwent a standardized submental ultrasound scan using a laser alignment tool to observe the upper airway in supine position during tidal respiration. Images acquired from this scan were divided into 4 equiangular regions (A-D). RESULTS: A total of 144 patients (30 women) July 2020-December 2022 were included with mean age 41.6 years (±12.9 SD), BMI 27.2 kg/m2(±4.7 SD), and AHI 19.7 (±20.0 SD). Moderate-to-severe OSA patients had significantly narrower airspace at regions A, B and C with p-values ranging from <0.0001 to 0.0003. These patients had a significantly wider (p = 0.0021-0.0045 for regions A, B and C) tongue and thicker (p = 0.0403 for region B) deep tissue. The predictive model to assess the risk of moderate-to-severe OSA achieved an area under the receiver operating characteristic curve of 0.839 (95 % CI: 0.769 to 0.895). CONCLUSIONS: With standardized, computerized ultrasound imaging of the shape and configuration of the tongue, we identified regions that correlated well with OSA severity. Further research is needed to determine the clinical implications of such pathophysiological findings.

Clinical performance of ultrasonic backscatter parametric and nonparametric statistics in detecting early hepatic steatosis.

Diagnosis of early hepatic steatosis would allow timely intervention. B-mode ultrasound imaging was in question for detecting early steatosis, especially with a variety of concomitant parenchymal disease. This study aimed to use the surgical specimen as a reference standard to elucidate the clinical performance of ultrasonic echogenicity and backscatter parametric and nonparametric statistics in real-world scenarios. Ultrasound radio-frequency (RF) signals of right liver lobe and patient data were collected preoperatively. Surgical specimen was then used to histologically determine staging of steatosis. A backscatter nonparametric statistic (h), a known backscatter parametric statistic, i.e., the Nakagami parameter (m), and a quantitative echo intensity (env) were calculated. Among the 236 patients included in the study, 93 were grade 0 (<5% fat) and 143 were with steatosis. All the env, m and h statistics had shown significant discriminatory power of steatosis grades (AUC = 0.643-0.907 with p-value < 0.001). Mann-Whitney U tests, however, revealed that only the backscatter statistics m and h were significantly different between the groups of grades 0 and 1 steatosis. The two-way ANOVA showed a significant confounding effect of the elevated ALT on env (p-value = 0.028), but no effect on m or h. Additionally, the severe fibrosis was found to be a significant covariate for m and h. Ultrasonic signals acquired from different scanners were found linearly comparable.

Association of Backscattered Ultrasonographic Imaging of the Tongue With Severity of Obstructive Sleep Apnea in Adults.

Importance: Determining interventions to manage obstructive sleep apnea (OSA) depends on clinical examination, polysomnography (PSG) results, and imaging analysis. There remains the need of a noninvasive and cost-effective way to correlate relevant upper airway anatomy with severity of OSA to direct treatment and optimize outcome. Objective: To determine whether backscattered ultrasonographic imaging (BUI) analysis of the tongue is associated with severity of OSA in adults. Design, Setting, and Participants: In this prospective, single-center, diagnostic study of a consecutive series of patients (aged ≥18 years) at a sleep surgery clinic, the 89 included patients had a PSG within 3 years at the time of ultrasonography and BUI analysis between July 2020 and March 2022. Patients were excluded if body mass index had changed more than 10% since time of PSG. A standardized submental ultrasonographic scan with laser alignment was used with B-mode and BUI analysis applied to the tongue. The B-mode and BUI intensity were associated with the apnea-hypopnea index (AHI), a measure of severity of apnea from normal (no OSA) to severe OSA. Exposures: Ultrasonography and PSG. Main Outcomes and Measures: The main outcomes were BUI parameters and their association with AHI value. Results: Eighty-nine patients were included between July 2020 and March 2022. A total of 70 (78.7%) male patients were included; and distribution by race and ethnicity was 46 (52%) White participants, 22 (25%) Asian participants, and 2 (2%) African American participants, and 19 (21%) others. Median (IQR) age was 37.0 (29.0-48.3) years; median (IQR) BMI was 25.3 (23.2-29.8); and median (IQR) AHI was 11.1 (5.6-23.1) events per hour. At the middle to posterior tongue region, the 4 OSA severity levels explained a significant portion of the BUI variance (η2 = 0.153-0.236), and a significant difference in BUI values was found between the subgroups with AHI values of less than 15 (no OSA and mild OSA) and greater than or equal to 15 (moderate OSA and severe OSA) events per hour. The echo intensity showed no significant differences. The BUI values showed a positive association with AHI, with a Spearman correlation coefficient of up to 0.43. Higher BUI values remained associated with higher AHI after correction for the covariates of BMI and age. Conclusions and Relevance: In this prospective diagnostic study, standardized BUI analysis of the tongue was associated with OSA severity. With the practicality of ultrasonography, this analysis is pivotal in connecting anatomy with physiology in treatment planning for patients with OSA.

Assessing Detection Accuracy of Computerized Sonographic Features and Computer-Assisted Reading Performance in Differentiating Thyroid Cancers.

For ultrasound imaging of thyroid nodules, medical guidelines are all based on findings of sonographic features to provide clinicians management recommendations. Due to the recent development of artificial intelligence and machine learning (AI/ML) technologies, there have been computer-assisted detection (CAD) software devices available for clinical use to detect and quantify the sonographic features of thyroid nodules. This study is to validate the accuracy of the computerized sonographic features (CSF) by a CAD software device, namely, AmCAD-UT, and then to assess how the reading performance of clinicians (readers) can be improved providing the computerized features. The feature detection accuracy is tested against the ground truth established by a panel of thyroid specialists and a multiple-reader multiple-case (MRMC) study is performed to assess the sequential reading performance with the assistance of the CSF. Five computerized features, including anechoic area, hyperechoic foci, hypoechoic pattern, heterogeneous texture, and indistinct margin, were tested, with AUCs ranging from 0.888~0.946, 0.825~0.913, 0.812~0.847, 0.627~0.77, and 0.676~0.766, respectively. With the five CSFs, the sequential reading performance of 18 clinicians is found significantly improved, with the AUC increasing from 0.720 without CSF to 0.776 with CSF. Our studies show that the computerized features are consistent with the clinicians' findings and provide additional value in assisting sonographic diagnosis.

Risk Stratification in Patients With Follicular Neoplasm on Cytology: Use of Quantitative Characteristics and Sonographic Patterns.

Objectives: Differentiating thyroid nodules with a cytological diagnosis of follicular neoplasm remains an issue. The goal of this study was to determine whether ultrasonographic (US) findings obtained preoperatively from the computer-aided detection (CAD) system are sufficient to further stratify the risk of malignancy for this diagnostic cytological category. Methods: From September 2016 to September 2018 in our hospital, patients diagnosed with Bethesda category IV (follicular neoplasm or suspicion of follicular neoplasm) thyroid nodules and underwent surgical excisions were include in the study. Quantification and analysis of tumor features were performed using CAD software. The US findings of the region of interest, including index of composition, margin, echogenicity, texture, echogenic dots indicative of calcifications, tall and wide orientation, and margin were calculated into computerized values. The nodules were further classified into American Thyroid Association (ATA) and American College of Radiology Thyroid Imaging Reporting & Data System (TI-RADS) categories. Results: 92 (10.1%) of 913 patients were diagnosed with Bethesda category IV thyroid nodules. In 65 patients, the histological type of the nodule was identified. The quantitative features between patients with benign and malignant conditions differed significantly. The presence of heterogeneous echotexture, blurred margins, or irregular margins was shown to have the highest diagnostic value. The risks of malignancy for nodules classified as having very low to intermediate suspicion ATA, non-ATA, and high suspicion ATA patterns were 9%, 35.7%, and 51.7%, respectively. Meanwhile, the risks of malignancy were 12.5%, 26.1%, and 53.8% for nodules classified as TIRADS 3, 4, and 5, respectively. When compared to human observers, among whom poor agreement was noticeable, the CAD software has shown a higher average accuracy. Conclusions: For patients with nodules diagnosed as Bethesda category IV, the software-based characterizations of US features, along with the associated ATA patterns and TIRADS system, were shown helpful in the risk stratification of malignancy.

Ultrasonographic features for differentiating follicular thyroid carcinoma and follicular adenoma.

BACKGROUND: Preoperative differentiation of follicular thyroid carcinoma (FTC) from follicular adenoma (FA) remains an unsolved puzzle. Patients sometimes undergo unnecessary lobectomy for histology confirmation inevitably. OBJECTIVE: In this retrospective study, we propose new gray-scale ultrasonographic (US) features that may help to differentiate FTC from FA. METHOD: Medical charts and US images of follicular thyroid neoplasms were collected prospectively. Gray-scale US features including conventional parameters adding tubercle-in-nodule and trabecular formation were recorded. RESULTS: The histopathologic diagnosis was FA in 139 and FTC in 49 patients. In patients with FTC, minimally invasive follicular carcinoma (MIFC) was seen in 36 patients and widely invasive follicular carcinoma (WIFC) in 13. The incidences of calcifications (p < 0.0001), tubercle-in-nodule signs (p < 0.0001), spiculated margins (p = 0.014), and trabecular formations (p = 0.03) were significantly higher in FTC. Tubercle-in-nodule (p < 0.01) and calcification (p < 0.001) were independent factors in the differentiation of FTC in multivariate analysis (area under the curve = 0.689). CONCLUSIONS: US characteristics of tubercle-in-nodule in combination with calcification help to differentiate FTC from FA.

Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection.

Physicians use sonographic characteristics as a reference for the possible diagnosis of thyroid cancers. The purpose of this study was to investigate whether physicians were more effective in their tentative diagnosis based on the information provided by a computer-aided detection (CAD) system. A computer compared software-defined and physician-adjusted tumor loci. A multicenter, multireader, and multicase (MRMC) study was designed to compare clinician performance without and with the use of CAD. Interobserver variability was also analyzed. Excellent, satisfactory, and poor segmentations were observed in 25.3%, 58.9%, and 15.8% of nodules, respectively. There were 200 patients with 265 nodules in the study set. Nineteen physicians scored the malignancy potential of the nodules. The average area under the curve (AUC) of all readers was 0.728 without CAD and significantly increased to 0.792 with CAD. The average standard deviation of the malignant potential score significantly decreased from 18.97 to 16.29. The mean malignant potential score significantly decreased from 35.01 to 31.24 for benign cases. With the CAD system, an additional 7.6% of malignant nodules would be suggested for further evaluation, and biopsy would not be recommended for an additional 10.8% of benign nodules. The results demonstrated that applying a CAD system would improve clinicians' interpretations and lessen the variability in diagnosis. However, more studies are needed to explore the use of the CAD system in an actual ultrasound diagnostic situation where much more benign thyroid nodules would be seen.

Computerized Cytological Features for Papillary Thyroid Cancer Diagnosis-Preliminary Report.

Fine needle aspiration cytology (FNAC) is the final diagnosis of thyroid nodules before surgery. It is important to further improve the indeterminate FNAC diagnosis results using computerized cytological features. This retrospective cross-sectional study included 240 cases, of whom 110 had histologic diagnosis of papillary thyroid cancers (PTC), 100 had nodular/adenomatous goiters/hyperplasia (benign goiters), 10 had follicular/Hurthle cell carcinomas, and 20 had follicular adenomas. Morphological and chromatic features of FNAC were quantified and analyzed. The result showed that six quantified cytological features were found significantly different between patients with a histologic diagnosis of PTC and patients with histologic diagnosis of benign goiters in multivariate analysis. These cytological features were used to estimate the malignancy risk in nodules with indeterminate FNAC results. The Area Under the Receiver Operating Characteristics (AUROC) of the diagnostic accuracy with a benign or malignant nature was 81.3% (p < 0.001), 78.7% (p = 0.014), and 56.8% (p = 0.52) for nodules with FNAC results of atypia, which is suspicious for malignancy and follicular neoplasm, respectively. In conclusion, quantification of cytological features could be used to develop a computer-aided tool for diagnosing PTC in thyroid nodules with indeterminate FNAC results.

Quantitative analysis of echogenicity for patients with thyroid nodules.

Hypoechogenicity has been described qualitatively and is potentially subject to intra- and inter-observer variability. The aim of this study was to clarify whether quantitative echoic indexes (EIs) are useful for the detection of malignant thyroid nodules. Overall, 333 participants with 411 nodules were included in the final analysis. Quantification of echogenicity was performed using commercial software (AmCAD-UT; AmCad BioMed, Taiwan). The coordinates of three defined regions, the nodule, thyroid parenchyma, and strap muscle regions, were recorded in the database separately for subsequent analysis. And the results showed that ultrasound echogenicity (US-E), as assessed by clinicians, defined hypoechogenicity as an independent factor for malignancy. The EI, adjusted EI (EIN-T; EIN-M) and automatic EI(N-R)/R values between benign and malignant nodules were all significantly different, with lower values for malignant nodules. All of the EIs showed similar percentages of sensitivity and specificity and had better accuracies than US-E. In conclusion, the proposed quantitative EI seems more promising to constitute an important advancement than the conventional qualitative US-E in allowing for a more reliable distinction between benign and malignant thyroid nodules.

Computerized quantification of ultrasonic heterogeneity in thyroid nodules.

To test whether computerized quantification of ultrasonic heterogeneity can be of help in the diagnosis of thyroid malignancy, we evaluated ultrasonic heterogeneity with an objective and quantitative computerized method in a prospective setting. A total of 400 nodules including 271 benign thyroid nodules and 129 malignant thyroid nodules were evaluated. Patient clinical data were collected, and the grading of heterogeneity on conventional gray-scale ultrasound images was retrospectively reviewed by a thyroid specialist. Quantification of ultrasonic heterogeneity (heterogeneity index, HI) was performed by a proprietary program implemented with methods proposed in this article. HI values differed significantly between benign and malignant nodules, diagnosed by a combination of fine-needle aspiration and surgical pathology results (p < 0.001, area under the curve = 0.714). The ultrasonic heterogeneity of these samples, as assessed by an experienced clinician, could not significantly differentiate between benign and malignant thyroid nodules. However, nodules with marked ultrasonic heterogeneity had higher HI values than nodules with homogeneous nodules. These results indicate that the new computer-aided diagnosis method for evaluation of the ultrasonic heterogeneity of thyroid nodules is an objective and quantitative method that is correlated with conventional ultrasonic heterogeneity assessment, but can better aid in the diagnosis of thyroid malignancy.

Quantitative analysis of dynamic power Doppler sonograms for patients with thyroid nodules.

To clarify and determine whether power Doppler sonograms are useful for the detection of malignant thyroid nodules, a computerized quantification method was used to evaluate the vascular density of a thyroid nodule in a prospective setting. Sonographic power Doppler images were collected in consecutive frames (45 frames of images), and a proprietary program (AmCAD-UV) was implemented using methods proposed in this article automatically calculated a quantified power Doppler vascular index (PDVI). The minimum PDVI value (PDVImin) was suggested as a measure of the vascular density of the nodule. The vascular densities of the peripheral and central areas of the nodule, referred to as central PDVImin and Ring PDVImin, respectively, were also evaluated. For 238 tumors (79 malignant and 159 benign) from 208 patients, all of the proposed indices of benign lesions were significantly higher than those of the malignant lesions. The area under the receiver operating characteristic curve (AUC) reaches 71% with the PDVImin. When the vascular patterns were further classified into intra-nodular and peripheral vascularity types, no vascularity type was observed significantly more frequently in malignant nodules than in benign nodules. These proposed computerized vascular indices provide a quantification method to objectively evaluate thyroid nodules and have potential as predictors of thyroid malignancy. The conventional vascular characterizations of malign nodules, that is, more vessels are observed in malignant nodules than in benign nodules, are shown to be unreliable in our study. Instead, a higher value of the quantified power Doppler vascular density was observed in benign nodules.

Computerized detection and quantification of microcalcifications in thyroid nodules.

To improve the ultrasonographic detection rates of thyroid cancers with microcalcifications, we propose to enhance the sensitivity of sonographic calcifications detection and to avoid interobserver variation by a computerized quantification method in a prospective setting. A total of 227 participants with 258 nodules were evaluated. Among them, two nodules were excluded for suspicious aspiration cytology results without pathologic proof. Among the remaining 256 nodules, the diagnosis of 181 nodules was verified by surgical pathology and the diagnosis of 75 was based on fine needle aspiration (FNA) biopsy results. There were 173 benign thyroid nodules and 83 malignant thyroid nodules, which included 74 papillary carcinomas. Patient clinical data were collected and the presence of calcifications on conventional gray-scale ultrasound images was retrospectively reviewed by a thyroid specialist. Quantification of cystic components and calcifications was automatically performed by a proprietary program (AmCAD-UT) implemented with methods proposed in this article. The calcification index (CI) was calculated after the cystic component was excluded. The CI between benign and malignant nodules diagnosed by combined FNA biopsy and surgical pathology results (total number, 256) showed a significant difference (p < 0.0001, AUC = 0.746). Furthermore, we excluded patients without surgical pathology results for further validation and the CI between benign and malignant nodules confirmed by pathology results (total number, 181) showed a significant difference (p < 0.0001, AUC = 0.763). To learn whether our computer program increased our diagnostic capabilities, we analyzed human investigators and their abilities to detect and evaluate. In this study, calcifications were noted in 48.19% (40 of 83) of malignant thyroid nodules and in 10.98% (19 of 173) of benign nodules. This new computer-aided diagnosis method to evaluate the sonographic calcifications of thyroid nodules is a more sensitive and more objective method. It can provide better sensitivity than conventional methods in the diagnosis of thyroid malignancies containing microcalcifications.