Omniview of Three-Dimensional Ultrasound for Prospective Evaluation of Extrathyroidal Extension of Differentiated Thyroid Cancer

Omniview of Three-Dimensional Ultrasound for Prospective Evaluation of Extrathyroidal Extension of Differentiated Thyroid Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Omniview of Three-Dimensional Ultrasound for Prospective Evaluation of Extrathyroidal Extension of Differentiated Thyroid Cancer Ruyu Liu, Yuxin Jiang, Xingjian Lai, Ying Wang, Luying Gao, Shenling Zhu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4106269/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Feb, 2025 Read the published version in BMC Medical Imaging → Version 1 posted 10 You are reading this latest preprint version Abstract Background Differentiated thyroid cancer (DTC) accounts for the majority of thyroid cancers. The preoperative diagnosis of extrathyroidal extension (ETE) in DTC patients is highly important. However, two-dimensional ultrasound (2D-US) has several limitations in diagnosing ETE. This study aimed to evaluate the efficiency of OmniView of three-dimensional ultrasound (3D-OmniView) in assessing the ETE of DTC patients compared with that of 2D-US. Methods Patients who underwent thyroid surgery for nodules adjacent to the thyroid capsule between February 2016 and January 2018 were prospectively enrolled in this study. Both 2D-US and 3D-OmniView were used to evaluate ETE of thyroid nodules. The definition for ETE in ultrasound images was capsule disruption, or capsule disruption and surrounding tissue invasion. Intraoperative and pathological findings of ETE were considered positive. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the ROC curve (AUC) were calculated. Results A total of 176 DTC nodules from 137 patients were included in this study. ETE was identified in 67.0% of the nodules. The sensitivity, accuracy, NPV and AUC of 3D-OmniView for predicting ETE were significantly greater than those of 2D-US. The sensitivity and specificity of 2D-US and 3D-OmniView were 79.7% and 51.7%, respectively (P 1 cm than in evaluating ETE in nodules ≤ 1 cm. Conclusion 3D-OmniView was more precise in predicting ETE of DTC nodules than 2D-US. 3D-OmniView is recommended for further evaluation of suspicious ETE. ETE was easier to detect by ultrasound for nodules > 1 cm than for nodules ≤ 1 cm. extrathyroidal extension OmniView three-dimensional ultrasound differentiated thyroid cancer two-dimensional ultrasound thyroid nodule Figures Figure 1 Figure 2 Figure 3 Introduction Differentiated thyroid cancer (DTC) comprises more than 90% of all thyroid cancers[ 1 ]. The incidence of extrathyroidal extension (ETE) in thyroid cancer varies between 5–45% according to the current literature[ 2 ]. The presence of ETE is a crucial factor for thyroid nodules stratification, ultrasound-guided fine-needle aspiration biopsy recommendation, active surveillance or ablation options, surgery and radioactive iodine therapy regimen design, and the risk assessment of recurrence, metastasis and survival. Therefore, accurate preoperative diagnosis of ETE is important. As the most popular imaging method for detecting thyroid nodules, two-dimensional ultrasound (2D-US) is perfect for diagnosing malignant nodules. However, the efficiency of 2D-US in assessing ETE is limited. Relevant studies have shown that the sensitivity and specificity of 2D-US for diagnosing ETE are 6.8 ~ 94.1% and 18.6 ~ 100.0%, respectively [ 3 – 12 ]. Three-dimensional ultrasound (3D-US) targets organs by a single sweep of an ultrasound beam and can easily provide images in multiple slices and planes from stored data. This technology has already demonstrated substantial value in preoperative evaluations of the degree of invasion and adjacent tissue invasion in endometrial cancer, cervical cancer, bladder cancer, etc. [ 13 – 15 ]. 3D-OmniView is a new 3D-US imaging technology that enables manual drawing of a line, curve, polyline, or trace from any direction or angle and presents the curved surface plane[ 16 ]. This technology has been applied in fetal brain, pelvic, and uterine wall defects[ 17 – 19 ]. Some experts have suggested that 3D-US may be a potential tool for identifying ETE of thyroid cancer nodules[ 2 , 20 ], but no study has reported ETE of thyroid cancer nodules assessed by 3D-OmniView. Thus, we used 3D-OmniView to prospectively assess the ETE of DTC nodules and compared this method with 2D-US. Materials and Methods Patients From February 2016 to January 2018, 274 nodules adjacent to the thyroid capsule in 168 patients who underwent ultrasound examination at Peking Union Medical College Hospital were prospectively enrolled in this study, and institutional ethics board approval and written informed consent were obtained from all participants. The inclusion criteria were patients who 1) were preparing for thyroid surgery, 2) were willing to undergo 2D-US and 3D-US examinations, and 3) had nodules adjacent to the thyroid capsule. The exclusion criteria were as follows: 1) nodules that had not been resected (n = 19); 2) nodules whose US images could not be fully matched with gross pathology (n = 15); and 3) non-DTC nodules (62 benign nodules and 2 medullary carcinomas). Finally, 176 DTC nodules in 137 patients were included in this study. Image assessment The 2D-US examination was performed with a 5 to 12 MHz broad-spectrum linear probe (iU22; Philips Healthcare, Eindhoven, the Netherlands), and 3D-US volume data were acquired with a 5-17-MHz broad-spectrum real-time 4D linear probe (GE Voluson E10; General Electric Medical Systems, Tiefenbach, Austria). While collecting 3D-US volume data, the probe was stabilized, the sweep angle was adjusted from 15° to 30° according to nodule size, and then the initial volume data were automatically acquired. The real-time 2D-US (Fig. 1 ) and 3D-US data were reviewed by two experienced radiologists with more than two years of experience in thyroid ultrasound. The two radiologists were both blinded to the pathological results. In this study, we used a restrictive definition for ETE in ultrasound images, which means that the nodule abuts the thyroid capsule with signs of disruption or disrupts the capsule and invades surrounding tissues such as soft tissue and/or perithyroidal muscles[ 7 ]. When the results differed, the radiologists discussed the differences to reach an agreement. In the analysis of the 3D-US data, a polyline was drawn along the thyroid capsule near the suspicious ETE site in 3D-Render (the basic mode of 3D-US) (Fig. 2 ), and then a reconstructed warped plane of the capsule surface was built and defined as the 3D-OmniView plane (Fig. 3 ). Statistical analyses Descriptive data are reported as the mean and standard deviation (‾ x ± S ) or median and interquartile range (IQR), as appropriate. Chi-square tests, T tests, Z tests and Mann‒Whitney tests were used to evaluate the statistical significance of the associations between US and ETE of thyroid nodules. The parameters for evaluating the predictive performance of 2D-US and 3D-OmniView include the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the ROC curve (AUC). Intraoperative findings and pathological findings are criteria for diagnosing ETE. A P value less than 0.05 was considered to indicate statistical significance. The IBM SPSS Statistics package, version 26.0 (IBM Corp, Armonk, NY, USA) and MedCalc 11.4.2.0 software were used for the statistical analysis. Results Among the 137 patients, 33 were males and 104 were females. The average age was 42.89 ± 10.09 years. Among 176 DTC nodules, 173 papillary thyroid cancer and 3 follicular thyroid cancer were included. A total of 118 nodules presented pathologic ETE, and 58 did not. Table 1 shows no significant correlations between the ETE and non-ETE groups in age (P = 0.293), sex (P = 0.861) or nodule number (P = 0.892). On average, the nodules with ETE were larger than those without ETE (P = 0.003) and were mostly located in the middle third of the thyroid gland (P = 0.037). Table 1 Demographic characteristics and pathological ETE of 176 DTCs nodules in 137 patients ETE P YES(n = 118) NO(n = 58) Age-‾x ± S 42.32 ± 1.05 44.33 ± 1.48 0.293 Females-n (%) 74(75.5) 30(76.9) 0.861 Size, cm-median [IQR]) 1.23(0.80–1.43) 0.88(0.50–0.93) 0.003 Location of nodules-n(%) 0.037 Upper third 23(19.5) 13(22.4) Middle third 62(52.5) 20(34.5) Lower third 31(26.3) 20(34.5) Isthmus 2(1.7) 5(8.6) Number of nodules-n(%) 0.892 Single 29(29.6) 12(30.8) Multiple 69(70.4) 27(69.2) ETE: extrathyroidal extension; DTC: differentiated thyroid cancer Table 2 shows that the efficiency parameters of 3D-OmniView in diagnosing ETE of DTC nodules were almost all greater than those of 2D-US. For all the 176 DTC nodules, the sensitivity(51.7% vs 79.7%, P<0.001), NPV(45.2% vs. 66.7%, P = 0.005), accuracy(61.4% vs 80.7%, P<0.001) and AUC(0.66(0.59–0.73) vs. 0.66(0.59–0.73), P<0.001) of 3D-OmniView were significantly higher than 2D-US. The same diagnostic parameters were significantly different for 101 DTC nodules with a maximum diameter ≤ 1 cm. For 75 DTC nodules with a maximum diameter > 1 cm, the differences in sensitivity and accuracy were significant. As shown in Table 2 , both 2D-US and 3D-OmniView showed better efficacy in detecting ETE of nodules > 1 cm than in nodules ≤ 1 cm. Except for the NPV of nodules > 1 cm, which was less than that of nodules ≤ 1 cm, the sensitivity, specificity, PPV, accuracy, and AUC of 2D-US and 3D-OmniView for nodules > 1 cm were all greater than those for nodules ≤ 1 cm. Table 2 Efficiency of 2D-US and 3D-OmniView in predicting the ETE of DTCs Sensitivity, % Specificity, % NPV, % PPV, % Accuracy, % AUC (95%CI) All 176 DTC nodules 2D-US 51.7(61/118) 81.0(47/58) 45.2(47/104) 84.7(61/72) 61.4(108/176) 0.66(0.59–0.73) 3D-OmniView 79.7(94/118) 82.8(48/58) 66.7(48/72) 90.4(94/104) 80.7(142/176) 0.81(0.75–0.87) P value <0.001 0.809 0.005 0.255 <0.001 1 cm 2D-US 64.5(40/62) 84.6(11/13) 33.3(11/33) 95.2(40/42) 68.0(51/75) 0.75(0.63–0.84) 3D-OmniView 88.7(55/62) 84.6(11/13) 61.1(11/18) 96.5(55/57) 88.0(66/75) 0.87(0.77–0.93) P value 0.001 1.000 0.706 1.000 0.003 0.059* 101 DTC nodules with maximum diameter ≤ 1 cm 2D-US 37.5(21/56) 80.0(36/45) 50.7(36/71) 70.0(21/30) 56.4(56/101) 0.59(0.49–0.69) 3D-OmniView 69.6(39/56) 82.2(37/45) 68.5(37/54) 83.0(37/54) 75.2(76/101) 0.76(0.66–0.84) P value 0.001 0.788 0.045 0.181 0.005 <0.001* The P values were calculated by chi-square tests, except for the P value of the AUC (*), which was calculated by the Z test. ETE, extrathyroidal extension; DTC, differentiated thyroid cancer; 3D, three-dimensional; 2D-US, two-dimensional ultrasound; NPV, negative predictive value; PPV, positive predictive value; AUC, area under the ROC curve; CI, confidence interval. Discussion The present study explored the application of 3D-OmniView, a novel 3D-US technology, in evaluating the ETE of thyroid nodules. The results revealed that 3D-OmniView was more precise than 2D-US in predicting ETE of DTC nodules. The sensitivity, NPV, AUC and accuracy were improved by 3D-OmniView. ETE is easier to detect by ultrasound for nodules > 1 cm than for nodules ≤ 1 cm. 3D-OmniView could help more patients with nodules ≤ 1 cm. The precise preoperative diagnosis of ETE of thyroid nodules is highly important, especially for papillary thyroid microcarcinoma(PTMC). Nodules with ETE are classified as high risk by ultrasound according to the 2015 American Thyroid Association guidelines[ 21 ]. The thyroid imaging reporting and data system of the American Radiological Society assigns a score of 3 points to ETE[ 22 ]. ETE also affects the choice of active surveillance, ablation or surgery for thyroid cancer. The American Thyroid Association guidelines recommend total or near-total thyroidectomy for DTCs with ETE and postsurgical radioactive iodine therapy for thyroid nodules of any size with gross ETE [ 21 ]. Moreover, numerous studies have identified gross ETE risk factors for recurrence, metastasis and survival. Although the effect of minimal ETE on PTMC clinical outcomes is controversial[ 23 ], some new studies have shown that minimal ETE is an independent predictor of persistent/recurrent disease and is associated with lymph node metastasis and lower disease-free survival rate[ 24 , 25 ]. Ultrasound is the most popular imaging method for thyroid nodules. However, the accuracy of conventional 2D-US for the diagnosis of ETE is controversial[ 26 ]. First, the diagnostic criteria for ETE on ultrasound vary among different studies, from thyroid capsule contact, capsule contact > 25%, 25 ~ 50% or 50%, and disruption of the capsule to invasion of surrounding tissues. The sensitivity of 2D-US in predicting ETE decreases from 94.1–6.8%, and the specificity increases from 18.6–100%[ 3 – 12 ]. In this study, similar to the study of Ramundo (sensitivity, 43.2%; specificity, 81.9%)[ 7 ], we used a restrictive ultrasound definition of ETE (nodules abut the thyroid capsule with signs of disruption or disruption of the capsule and invade surrounding tissues). The sensitivity of 2D-US was 51.7%, and the specificity of 2D-US was 81.0%. We increased the sensitivity to 79.7% without decreasing the specificity of 3D-US. Second, 2D-US is a real-time dynamic imaging technique that is more dependent on the operator and more easily misses some information. Moreover, due to the lateral echo loss effect and acoustic shadow, exploration of the vascular and tracheal lateral boundaries of some nodules is limited. Therefore, we attempted to fill those gaps with 3D ultrasound. In our study, 3D-OminiView showed higher sensitivity and accuracy for identifying ETE. 3D-US imaging provides volume data, thus reducing operator dependence and decreasing observer differences. 3D-US revealed a coronal plane that could not be visualized by 2D-US, reduced the influence of acoustic shadows and lateral wall echo drop-out, and showed a significantly clearer relationship between the thyroid nodules and the thyroid capsule along the tracheal and vessel sides. In addition, the focus of the observation could be localized to one point, which was simultaneously shown in three planes (transverse, longitudinal and coronal). When the thyroid nodules were adjacent to the thyroid capsule, 3D-US focused on these areas and provided dynamic observations in three planes at the same time. Moreover, 3D-OmniView can turn the disrupted line of the thyroid capsule into a plane of the thyroid capsule with protruding nodules, enabling clearer visualization of the relationship between the thyroid nodules and the capsule. As a result, 3D-OmniView identified ETE more readily and precisely than 2D-US. Compared with other studies on the efficiency of 2D-US and 3D-US in diagnosing ETE, the present study maintained a relatively high specificity and improved the sensitivity (Table 3 ). This may be related to the use of 3D-OmniView technology and a restrictive US definition of ETE. In clinical practice, we found that 2D-US is sensitive enough to detect capsule contact of thyroid nodules, while the advantage of 3D-OmniView is reflected in the ability to distinguish capsule disruption and the relationship between nodules and the surrounding structure. Table 3 Comparison of the efficiency of 2D-US and 3D-US in diagnosing ETE between different studies Study Criteria for predicting ETE Sensitivity Specificity 2D-US 3D-US P 2D-US 3D-US P Yi et al .[ 12 ] contact capsule 94.1% 94.1% 1.000 41.5% 45.3% 0.754 Gweon et al .[ 10 ] contact capsule >25% 78.2% 86.5% 0.14 27.2% 27.2% > 0.99 Kim et al .[ 11 ] contact capsule >50% 46.4% 66.7% 0.03 74.8% 78.4% 1.00 This study capsule disruption or capsule disruption and invades surrounding tissues 51.7% 79.7% <0.001 81.0% 82.8% 0.776 There are several limitations in this study. First, to focus on the ETE diagnosis, the nodules we enrolled were all adjacent to the thyroid capsule. This may have resulted in selection bias. Second, this was a single-center study with a small number of patients. Because only 12 DTC nodules presented gross ETE, we did not compare the diagnostic value of gross and minimal ETE by 2D-US and 3D-Omniview. A large, multicenter, prospective and comprehensive study is needed in the future to confirm these results. Conclusions This study showed that 3D-OmniView was more precise in predicting ETE in DTC patients than was 2D-US, especially in terms of sensitivity. 3D-OmniView is recommended for further evaluation of suspicious ETE. However, 2D-US is sufficient for identifying nodules without suspicious signs of ETE. Moreover, ETE is easier to detect by ultrasound for nodules > 1 cm than for nodules ≤ 1 cm. Therefore, 3D-OmniView may aid in determining ETE for nodules ≤ 1 cm. Abbreviations DTC Differentiated thyroid cancer ETE Extrathyroidal extension 2D-US Two-dimensional ultrasound 3D-OmniView OmniView of three-dimensional ultrasound 3D-US Three-dimensional ultrasound PPV Positive predictive value NPV Negative predictive value AUC Area under the ROC curve CCA Common carotid artery IQR Interquartile range CI Confidence interval PTMC Papillary thyroid microcarcinoma Declarations Acknowledgements Not applicable. Author contributions Conception and design were contributed by B. Zhang and Y.-X Jiang. Data acquisition were contributed by all author. Data analysis and interpretation was contributed by X.-J Lai, Y.Wang and R.-Y. Liu. Drafting of the manuscript was contributed by R.-Y. Liu. Critical revision of the manuscript was contributed by X.-J Lai, R.-Y. Liu and B. Zhang. All authors reviewed the manuscript. Funding This study was funded by the China-Japan Friendship Hospital Talent Introduction Program (2019-RC-2). Availability of data and materials Aggregated and anonymized data used or analyzed during the current study are available from the corresponding author, Zhang Bo, upon reasonable request. Ethics approval and consent to participate This research gained consent to Ethics Review Committee in Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (number: S-K1238).Informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Sherman SI: Thyroid carcinoma . Lancet 2003, 361 (9356):501-511. Kwak JY, Kim EK, Youk JH, Kim MJ, Son EJ, Choi SH , et al : Extrathyroid extension of well-differentiated papillary thyroid microcarcinoma on US . Thyroid 2008, 18 (6):609-614. Lee CY, Kim SJ, Ko KR, Chung KW, Lee JH: Predictive factors for extrathyroidal extension of papillary thyroid carcinoma based on preoperative sonography . 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Cite Share Download PDF Status: Published Journal Publication published 10 Feb, 2025 Read the published version in BMC Medical Imaging → Version 1 posted Editorial decision: Revision requested 10 Oct, 2024 Reviews received at journal 18 Aug, 2024 Reviewers agreed at journal 31 Jul, 2024 Reviews received at journal 06 Jun, 2024 Reviewers agreed at journal 06 Jun, 2024 Reviewers invited by journal 22 May, 2024 Editor invited by journal 03 Apr, 2024 Submission checks completed at journal 03 Apr, 2024 Editor assigned by journal 03 Apr, 2024 First submitted to journal 15 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4106269","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":288270143,"identity":"8be452fd-77d9-4a97-91c7-4bd0ed6989e8","order_by":0,"name":"Ruyu Liu","email":"","orcid":"","institution":"China-Japan Friendship Hospital, Chinese Academy of Medical Sciences \u0026 Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Ruyu","middleName":"","lastName":"Liu","suffix":""},{"id":288270144,"identity":"bc3f5827-152e-4534-ab30-2b028d9e6820","order_by":1,"name":"Yuxin Jiang","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuxin","middleName":"","lastName":"Jiang","suffix":""},{"id":288270145,"identity":"c3dfb2df-0f5e-4b71-a5cd-6f21c13aca5a","order_by":2,"name":"Xingjian Lai","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xingjian","middleName":"","lastName":"Lai","suffix":""},{"id":288270147,"identity":"7d1cb815-cf86-4a16-b2f6-6e667536945b","order_by":3,"name":"Ying Wang","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Wang","suffix":""},{"id":288270148,"identity":"852fd3e7-60c4-437f-b647-92d015171984","order_by":4,"name":"Luying Gao","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Luying","middleName":"","lastName":"Gao","suffix":""},{"id":288270151,"identity":"765f6b87-510a-4c78-9da9-0bdfdd871cdd","order_by":5,"name":"Shenling Zhu","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shenling","middleName":"","lastName":"Zhu","suffix":""},{"id":288270152,"identity":"5891b01d-0d16-4515-b4a6-5128cb6bc879","order_by":6,"name":"Xiao Yang","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Yang","suffix":""},{"id":288270154,"identity":"bb44cb46-4810-48d9-bbfb-75ef5c7d2aea","order_by":7,"name":"Ruina Zhao","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ruina","middleName":"","lastName":"Zhao","suffix":""},{"id":288270155,"identity":"d500ca14-ea7d-4eba-9315-b7674d286b0a","order_by":8,"name":"Xiaoyan Zhang","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyan","middleName":"","lastName":"Zhang","suffix":""},{"id":288270156,"identity":"f423b396-6977-4198-80f7-d750011dec79","order_by":9,"name":"Xuehua Xi","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuehua","middleName":"","lastName":"Xi","suffix":""},{"id":288270157,"identity":"93854737-12f4-4867-bc35-35a28f77b8e1","order_by":10,"name":"Bo Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIie3RsWrDMBCAYZkDeTmaIcuVQPIKKgY3g0lfRSJwk4ZOJaNDQF7SPY+RRzAVdRfTOYUOCYXOHj0U2jxAsJ2tg775fo6ThAiC/0qvfnEE0frYqGwxLDnWML0tNv5u98jLQUV0cpCouuIxNi9R3jc+K55PjXHS5AebQqZKELF/3Xdu2L4lpN/RrHc2/bLq80Yg86ErAWJB+onMhux9YtU3CMK0M5HE0GqpjCObTubKR3lfgsSStNMJYsUTMSQhrORc1+WU4vMjbxUvZd8ts8LBR7sq8cGfv7L9yRaj2FedyYXrrhsPgiAILvkDH4hKBeOdNiQAAAAASUVORK5CYII=","orcid":"","institution":"National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; China-Japan Friendship Hospital","correspondingAuthor":true,"prefix":"","firstName":"Bo","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-03-15 08:44:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4106269/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4106269/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12880-025-01572-w","type":"published","date":"2025-02-10T15:57:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54322701,"identity":"221da6f7-f7af-4d7c-a1b7-7d37badf6358","added_by":"auto","created_at":"2024-04-08 19:51:47","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":661119,"visible":true,"origin":"","legend":"\u003cp\u003eThe longitudinal (A) and transverse (B) planes of 2D-US showed a 0.5 cm×0.5 cm×0.6 cm solid thyroid nodule in the right lobe of the thyroid, which was closely adjacent to the common carotid artery (CCA).\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4106269/v1/2d555a8f90bc1cbe6c88ee1c.jpg"},{"id":54322699,"identity":"0f0be99a-ea4f-482c-a6ab-15c0d763d0c2","added_by":"auto","created_at":"2024-04-08 19:51:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":197043,"visible":true,"origin":"","legend":"\u003cp\u003e3D-Render showing the transverse (A), longitudinal (B), and coronal planes (C) and a reconstructed 3D coronal image (3D) of the above thyroid nodule in Figure 1. In the C plane and reconstructed 3D coronal image, the thyroid capsule near the CCA was interrupted.\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4106269/v1/ce8f21ccab87d659c57e8fc3.jpg"},{"id":54322700,"identity":"7260c5fd-05ca-4741-9a95-1970f5c09b5a","added_by":"auto","created_at":"2024-04-08 19:51:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112100,"visible":true,"origin":"","legend":"\u003cp\u003eA polyline was drawn along the thyroid capsule with suspicious interruption in the coronal plane. The reconstructed 3D-OmniView plane showed a hypoechoic thyroid nodule extending into the hyperechoic thyroid capsule.\u003c/p\u003e","description":"","filename":"floatimage3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4106269/v1/890a25fb311b4ec25b444e85.jpg"},{"id":76487516,"identity":"eb3ef1a2-1632-41e4-87de-77e4a209f007","added_by":"auto","created_at":"2025-02-17 16:08:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3095890,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4106269/v1/8800b803-384c-4426-bfdb-4acb0e9404e5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Omniview of Three-Dimensional Ultrasound for Prospective Evaluation of Extrathyroidal Extension of Differentiated Thyroid Cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDifferentiated thyroid cancer (DTC) comprises more than 90% of all thyroid cancers[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The incidence of extrathyroidal extension (ETE) in thyroid cancer varies between 5\u0026ndash;45% according to the current literature[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The presence of ETE is a crucial factor for thyroid nodules stratification, ultrasound-guided fine-needle aspiration biopsy recommendation, active surveillance or ablation options, surgery and radioactive iodine therapy regimen design, and the risk assessment of recurrence, metastasis and survival. Therefore, accurate preoperative diagnosis of ETE is important.\u003c/p\u003e \u003cp\u003eAs the most popular imaging method for detecting thyroid nodules, two-dimensional ultrasound (2D-US) is perfect for diagnosing malignant nodules. However, the efficiency of 2D-US in assessing ETE is limited. Relevant studies have shown that the sensitivity and specificity of 2D-US for diagnosing ETE are 6.8\u0026thinsp;~\u0026thinsp;94.1% and 18.6\u0026thinsp;~\u0026thinsp;100.0%, respectively [\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThree-dimensional ultrasound (3D-US) targets organs by a single sweep of an ultrasound beam and can easily provide images in multiple slices and planes from stored data. This technology has already demonstrated substantial value in preoperative evaluations of the degree of invasion and adjacent tissue invasion in endometrial cancer, cervical cancer, bladder cancer, etc. [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. 3D-OmniView is a new 3D-US imaging technology that enables manual drawing of a line, curve, polyline, or trace from any direction or angle and presents the curved surface plane[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This technology has been applied in fetal brain, pelvic, and uterine wall defects[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Some experts have suggested that 3D-US may be a potential tool for identifying ETE of thyroid cancer nodules[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], but no study has reported ETE of thyroid cancer nodules assessed by 3D-OmniView. Thus, we used 3D-OmniView to prospectively assess the ETE of DTC nodules and compared this method with 2D-US.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003e From February 2016 to January 2018, 274 nodules adjacent to the thyroid capsule in 168 patients who underwent ultrasound examination at Peking Union Medical College Hospital were prospectively enrolled in this study, and institutional ethics board approval and written informed consent were obtained from all participants. The inclusion criteria were patients who 1) were preparing for thyroid surgery, 2) were willing to undergo 2D-US and 3D-US examinations, and 3) had nodules adjacent to the thyroid capsule. The exclusion criteria were as follows: 1) nodules that had not been resected (n\u0026thinsp;=\u0026thinsp;19); 2) nodules whose US images could not be fully matched with gross pathology (n\u0026thinsp;=\u0026thinsp;15); and 3) non-DTC nodules (62 benign nodules and 2 medullary carcinomas). Finally, 176 DTC nodules in 137 patients were included in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eImage assessment\u003c/h2\u003e \u003cp\u003eThe 2D-US examination was performed with a 5 to 12 MHz broad-spectrum linear probe (iU22; Philips Healthcare, Eindhoven, the Netherlands), and 3D-US volume data were acquired with a 5-17-MHz broad-spectrum real-time 4D linear probe (GE Voluson E10; General Electric Medical Systems, Tiefenbach, Austria). While collecting 3D-US volume data, the probe was stabilized, the sweep angle was adjusted from 15\u0026deg; to 30\u0026deg; according to nodule size, and then the initial volume data were automatically acquired. The real-time 2D-US (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and 3D-US data were reviewed by two experienced radiologists with more than two years of experience in thyroid ultrasound. The two radiologists were both blinded to the pathological results. In this study, we used a restrictive definition for ETE in ultrasound images, which means that the nodule abuts the thyroid capsule with signs of disruption or disrupts the capsule and invades surrounding tissues such as soft tissue and/or perithyroidal muscles[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. When the results differed, the radiologists discussed the differences to reach an agreement.\u003c/p\u003e \u003cp\u003eIn the analysis of the 3D-US data, a polyline was drawn along the thyroid capsule near the suspicious ETE site in 3D-Render (the basic mode of 3D-US) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and then a reconstructed warped plane of the capsule surface was built and defined as the 3D-OmniView plane (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eDescriptive data are reported as the mean and standard deviation (\u0026oline;\u003cb\u003ex\u0026thinsp;\u0026plusmn;\u0026thinsp;S\u003c/b\u003e) or median and interquartile range (IQR), as appropriate. Chi-square tests, T tests, Z tests and Mann‒Whitney tests were used to evaluate the statistical significance of the associations between US and ETE of thyroid nodules. The parameters for evaluating the predictive performance of 2D-US and 3D-OmniView include the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the ROC curve (AUC). Intraoperative findings and pathological findings are criteria for diagnosing ETE. A P value less than 0.05 was considered to indicate statistical significance. The IBM SPSS Statistics package, version 26.0 (IBM Corp, Armonk, NY, USA) and MedCalc 11.4.2.0 software were used for the statistical analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAmong the 137 patients, 33 were males and 104 were females. The average age was 42.89\u0026thinsp;\u0026plusmn;\u0026thinsp;10.09 years. Among 176 DTC nodules, 173 papillary thyroid cancer and 3 follicular thyroid cancer were included. A total of 118 nodules presented pathologic ETE, and 58 did not. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows no significant correlations between the ETE and non-ETE groups in age (P\u0026thinsp;=\u0026thinsp;0.293), sex (P\u0026thinsp;=\u0026thinsp;0.861) or nodule number (P\u0026thinsp;=\u0026thinsp;0.892). On average, the nodules with ETE were larger than those without ETE (P\u0026thinsp;=\u0026thinsp;0.003) and were mostly located in the middle third of the thyroid gland (P\u0026thinsp;=\u0026thinsp;0.037).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics and pathological ETE of 176 DTCs nodules in 137 patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eETE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES(n\u0026thinsp;=\u0026thinsp;118)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO(n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge-\u0026oline;x\u0026thinsp;\u0026plusmn;\u0026thinsp;S\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemales-n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74(75.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.861\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSize, cm-median [IQR])\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23(0.80\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88(0.50\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocation of nodules-n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUpper third\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23(19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMiddle third\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62(52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLower third\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIsthmus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of nodules-n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSingle\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29(29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMultiple\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69(70.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eETE: extrathyroidal extension; DTC: differentiated thyroid cancer\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that the efficiency parameters of 3D-OmniView in diagnosing ETE of DTC nodules were almost all greater than those of 2D-US. For all the 176 DTC nodules, the sensitivity(51.7% vs 79.7%, P\u0026lt;0.001), NPV(45.2% vs. 66.7%, P\u0026thinsp;=\u0026thinsp;0.005), accuracy(61.4% vs 80.7%, P\u0026lt;0.001) and AUC(0.66(0.59\u0026ndash;0.73) vs. 0.66(0.59\u0026ndash;0.73), P\u0026lt;0.001) of 3D-OmniView were significantly higher than 2D-US. The same diagnostic parameters were significantly different for 101 DTC nodules with a maximum diameter\u0026thinsp;\u0026le;\u0026thinsp;1 cm. For 75 DTC nodules with a maximum diameter\u0026thinsp;\u0026gt;\u0026thinsp;1 cm, the differences in sensitivity and accuracy were significant.\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, both 2D-US and 3D-OmniView showed better efficacy in detecting ETE of nodules\u0026thinsp;\u0026gt;\u0026thinsp;1 cm than in nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm. Except for the NPV of nodules\u0026thinsp;\u0026gt;\u0026thinsp;1 cm, which was less than that of nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm, the sensitivity, specificity, PPV, accuracy, and AUC of 2D-US and 3D-OmniView for nodules\u0026thinsp;\u0026gt;\u0026thinsp;1 cm were all greater than those for nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEfficiency of 2D-US and 3D-OmniView in predicting the ETE of DTCs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNPV, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePPV, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAccuracy, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAUC (95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAll 176 DTC nodules\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D-US\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.7(61/118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.0(47/58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.2(47/104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.7(61/72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.4(108/176)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.66(0.59\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3D-OmniView\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.7(94/118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.8(48/58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.7(48/72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.4(94/104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80.7(142/176)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.81(0.75\u0026ndash;0.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e75 DTC nodules with maximum diameter \u0026gt;1 cm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D-US\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.5(40/62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.6(11/13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.3(11/33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.2(40/42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.0(51/75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.75(0.63\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3D-OmniView\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.7(55/62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.6(11/13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.1(11/18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.5(55/57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.0(66/75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.87(0.77\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.059*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e101 DTC nodules with maximum diameter\u0026thinsp;\u0026le;\u0026thinsp;1 cm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D-US\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.5(21/56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.0(36/45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.7(36/71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.0(21/30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.4(56/101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.59(0.49\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3D-OmniView\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.6(39/56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.2(37/45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.5(37/54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.0(37/54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.2(76/101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.76(0.66\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe P values were calculated by chi-square tests, except for the P value of the AUC (*), which was calculated by the Z test.\u003c/p\u003e \u003cp\u003eETE, extrathyroidal extension; DTC, differentiated thyroid cancer; 3D, three-dimensional; 2D-US, two-dimensional ultrasound; NPV, negative predictive value; PPV, positive predictive value; AUC, area under the ROC curve; CI, confidence interval.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study explored the application of 3D-OmniView, a novel 3D-US technology, in evaluating the ETE of thyroid nodules. The results revealed that 3D-OmniView was more precise than 2D-US in predicting ETE of DTC nodules. The sensitivity, NPV, AUC and accuracy were improved by 3D-OmniView. ETE is easier to detect by ultrasound for nodules\u0026thinsp;\u0026gt;\u0026thinsp;1 cm than for nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm. 3D-OmniView could help more patients with nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm.\u003c/p\u003e \u003cp\u003eThe precise preoperative diagnosis of ETE of thyroid nodules is highly important, especially for papillary thyroid microcarcinoma(PTMC). Nodules with ETE are classified as high risk by ultrasound according to the 2015 American Thyroid Association guidelines[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The thyroid imaging reporting and data system of the American Radiological Society assigns a score of 3 points to ETE[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. ETE also affects the choice of active surveillance, ablation or surgery for thyroid cancer. The American Thyroid Association guidelines recommend total or near-total thyroidectomy for DTCs with ETE and postsurgical radioactive iodine therapy for thyroid nodules of any size with gross ETE [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Moreover, numerous studies have identified gross ETE risk factors for recurrence, metastasis and survival. Although the effect of minimal ETE on PTMC clinical outcomes is controversial[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], some new studies have shown that minimal ETE is an independent predictor of persistent/recurrent disease and is associated with lymph node metastasis and lower disease-free survival rate[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUltrasound is the most popular imaging method for thyroid nodules. However, the accuracy of conventional 2D-US for the diagnosis of ETE is controversial[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. First, the diagnostic criteria for ETE on ultrasound vary among different studies, from thyroid capsule contact, capsule contact\u0026thinsp;\u0026gt;\u0026thinsp;25%, 25\u0026thinsp;~\u0026thinsp;50% or 50%, and disruption of the capsule to invasion of surrounding tissues. The sensitivity of 2D-US in predicting ETE decreases from 94.1\u0026ndash;6.8%, and the specificity increases from 18.6\u0026ndash;100%[\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In this study, similar to the study of Ramundo (sensitivity, 43.2%; specificity, 81.9%)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], we used a restrictive ultrasound definition of ETE (nodules abut the thyroid capsule with signs of disruption or disruption of the capsule and invade surrounding tissues). The sensitivity of 2D-US was 51.7%, and the specificity of 2D-US was 81.0%. We increased the sensitivity to 79.7% without decreasing the specificity of 3D-US. Second, 2D-US is a real-time dynamic imaging technique that is more dependent on the operator and more easily misses some information. Moreover, due to the lateral echo loss effect and acoustic shadow, exploration of the vascular and tracheal lateral boundaries of some nodules is limited. Therefore, we attempted to fill those gaps with 3D ultrasound.\u003c/p\u003e \u003cp\u003eIn our study, 3D-OminiView showed higher sensitivity and accuracy for identifying ETE. 3D-US imaging provides volume data, thus reducing operator dependence and decreasing observer differences. 3D-US revealed a coronal plane that could not be visualized by 2D-US, reduced the influence of acoustic shadows and lateral wall echo drop-out, and showed a significantly clearer relationship between the thyroid nodules and the thyroid capsule along the tracheal and vessel sides. In addition, the focus of the observation could be localized to one point, which was simultaneously shown in three planes (transverse, longitudinal and coronal). When the thyroid nodules were adjacent to the thyroid capsule, 3D-US focused on these areas and provided dynamic observations in three planes at the same time. Moreover, 3D-OmniView can turn the disrupted line of the thyroid capsule into a plane of the thyroid capsule with protruding nodules, enabling clearer visualization of the relationship between the thyroid nodules and the capsule. As a result, 3D-OmniView identified ETE more readily and precisely than 2D-US.\u003c/p\u003e \u003cp\u003eCompared with other studies on the efficiency of 2D-US and 3D-US in diagnosing ETE, the present study maintained a relatively high specificity and improved the sensitivity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This may be related to the use of 3D-OmniView technology and a restrictive US definition of ETE. In clinical practice, we found that 2D-US is sensitive enough to detect capsule contact of thyroid nodules, while the advantage of 3D-OmniView is reflected in the ability to distinguish capsule disruption and the relationship between nodules and the surrounding structure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the efficiency of 2D-US and 3D-US in diagnosing ETE between different studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCriteria for predicting ETE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2D-US\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3D-US\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2D-US\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e3D-US\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYi \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003econtact capsule\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e45.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGweon \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003econtact capsule \u0026gt;25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e27.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKim \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003econtact capsule \u0026gt;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecapsule disruption or capsule disruption and invades surrounding tissues\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e82.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere are several limitations in this study. First, to focus on the ETE diagnosis, the nodules we enrolled were all adjacent to the thyroid capsule. This may have resulted in selection bias. Second, this was a single-center study with a small number of patients. Because only 12 DTC nodules presented gross ETE, we did not compare the diagnostic value of gross and minimal ETE by 2D-US and 3D-Omniview. A large, multicenter, prospective and comprehensive study is needed in the future to confirm these results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study showed that 3D-OmniView was more precise in predicting ETE in DTC patients than was 2D-US, especially in terms of sensitivity. 3D-OmniView is recommended for further evaluation of suspicious ETE. However, 2D-US is sufficient for identifying nodules without suspicious signs of ETE. Moreover, ETE is easier to detect by ultrasound for nodules\u0026thinsp;\u0026gt;\u0026thinsp;1 cm than for nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm. Therefore, 3D-OmniView may aid in determining ETE for nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDTC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Differentiated thyroid cancer\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eETE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Extrathyroidal extension\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2D-US \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Two-dimensional ultrasound\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3D-OmniView \u0026nbsp; \u0026nbsp;OmniView of three-dimensional ultrasound\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3D-US \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Three-dimensional ultrasound\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePPV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Positive predictive value\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNPV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Negative predictive value\u003c/p\u003e\n\u003cp\u003eAUC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Area under the ROC curve\u003c/p\u003e\n\u003cp\u003eCCA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Common carotid artery\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIQR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Interquartile range\u003c/p\u003e\n\u003cp\u003eCI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Confidence interval\u003c/p\u003e\n\u003cp\u003ePTMC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Papillary thyroid microcarcinoma\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConception and design were contributed by B. Zhang and\u0026nbsp;Y.-X Jiang. Data acquisition were contributed by all author. Data analysis and interpretation was contributed by\u0026nbsp;X.-J Lai, Y.Wang and R.-Y. Liu. Drafting of the manuscript was contributed by\u0026nbsp;R.-Y. Liu. Critical revision of the manuscript was contributed by\u0026nbsp;X.-J Lai,\u0026nbsp;R.-Y. Liu and B. Zhang. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by\u0026nbsp;the\u0026nbsp;China-Japan\u0026nbsp;Friendship Hospital Talent Introduction Program\u0026nbsp;(2019-RC-2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAggregated and anonymized data used or analyzed during the current study\u003c/p\u003e\n\u003cp\u003eare available from the corresponding author, Zhang Bo, upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research gained consent to Ethics Review Committee in Peking Union Medical College Hospital, Chinese Academy of Medical Sciences (number: S-K1238).Informed consent was obtained from all\u0026nbsp;individual\u0026nbsp;participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSherman SI: \u003cstrong\u003eThyroid carcinoma\u003c/strong\u003e. \u003cem\u003eLancet \u003c/em\u003e2003, \u003cstrong\u003e361\u003c/strong\u003e(9356):501-511.\u003c/li\u003e\n\u003cli\u003eKwak JY, Kim EK, Youk JH, Kim MJ, Son EJ, Choi SH\u003cem\u003e, et al\u003c/em\u003e: \u003cstrong\u003eExtrathyroid extension of well-differentiated papillary thyroid microcarcinoma on US\u003c/strong\u003e. \u003cem\u003eThyroid \u003c/em\u003e2008, \u003cstrong\u003e18\u003c/strong\u003e(6):609-614.\u003c/li\u003e\n\u003cli\u003eLee CY, Kim SJ, Ko KR, Chung KW, Lee JH: \u003cstrong\u003ePredictive factors for 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\u003cstrong\u003e185\u003c/strong\u003e(1):13-22.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"extrathyroidal extension, OmniView, three-dimensional ultrasound, differentiated thyroid cancer, two-dimensional ultrasound, thyroid nodule","lastPublishedDoi":"10.21203/rs.3.rs-4106269/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4106269/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDifferentiated thyroid cancer (DTC) accounts for the majority of thyroid cancers. The preoperative diagnosis of extrathyroidal extension (ETE) in DTC patients is highly important. However, two-dimensional ultrasound (2D-US) has several limitations in diagnosing ETE. This study aimed to evaluate the efficiency of OmniView of three-dimensional ultrasound (3D-OmniView) in assessing the ETE of DTC patients compared with that of 2D-US.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients who underwent thyroid surgery for nodules adjacent to the thyroid capsule between February 2016 and January 2018 were prospectively enrolled in this study. Both 2D-US and 3D-OmniView were used to evaluate ETE of thyroid nodules. The definition for ETE in ultrasound images was capsule disruption, or capsule disruption and surrounding tissue invasion. Intraoperative and pathological findings of ETE were considered positive. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the ROC curve (AUC) were calculated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 176 DTC nodules from 137 patients were included in this study. ETE was identified in 67.0% of the nodules. The sensitivity, accuracy, NPV and AUC of 3D-OmniView for predicting ETE were significantly greater than those of 2D-US. The sensitivity and specificity of 2D-US and 3D-OmniView were 79.7% and 51.7%, respectively (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and 81.0% and 82.8%, respectively (P\u0026thinsp;=\u0026thinsp;0.776). Both 2D-US and 3D-OmniView showed better efficacy in evaluating ETE in nodules\u0026thinsp;\u0026gt;\u0026thinsp;1 cm than in evaluating ETE in nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003e3D-OmniView was more precise in predicting ETE of DTC nodules than 2D-US. 3D-OmniView is recommended for further evaluation of suspicious ETE. ETE was easier to detect by ultrasound for nodules\u0026thinsp;\u0026gt;\u0026thinsp;1 cm than for nodules\u0026thinsp;\u0026le;\u0026thinsp;1 cm.\u003c/p\u003e","manuscriptTitle":"Omniview of Three-Dimensional Ultrasound for Prospective Evaluation of Extrathyroidal Extension of Differentiated Thyroid Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 19:51:42","doi":"10.21203/rs.3.rs-4106269/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-10T11:27:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-18T10:26:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197133945979535258334686101467398072016","date":"2024-07-31T22:29:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-06T09:21:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55940902235364567898834457040495518297","date":"2024-06-06T07:57:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-22T11:33:39+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-03T16:21:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-03T16:17:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-03T16:17:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2024-03-15T08:35:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"692306b7-5e59-43fb-b92b-72bc7f738218","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-17T16:02:02+00:00","versionOfRecord":{"articleIdentity":"rs-4106269","link":"https://doi.org/10.1186/s12880-025-01572-w","journal":{"identity":"bmc-medical-imaging","isVorOnly":false,"title":"BMC Medical Imaging"},"publishedOn":"2025-02-10 15:57:34","publishedOnDateReadable":"February 10th, 2025"},"versionCreatedAt":"2024-04-08 19:51:42","video":"","vorDoi":"10.1186/s12880-025-01572-w","vorDoiUrl":"https://doi.org/10.1186/s12880-025-01572-w","workflowStages":[]},"version":"v1","identity":"rs-4106269","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4106269","identity":"rs-4106269","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}