Standardisierte Akquisition und Dokumentation von Videosequenzen bei der konventionellen Schilddrüsensonografie

Zusammenfassung

Ultraschall ist die bildgebende Basisdiagnostik zur Beurteilung der Schilddrüse. Aufgrund der hohen Prävalenz struktureller Parenchymveränderungen kommt das Untersuchungsverfahren in Deutschland sehr häufig zum Einsatz, in vielen Fällen im Rahmen von Verlaufskontrollen. Die Beurteilung thyreoidaler Pathologien und deren Dynamik unterliegt einer relevanten Inter- und Intraobservervariabilität. Befunde die während des Live-Ultraschalls nicht identifiziert und aufgezeichnet wurden, können retrospektiv nicht mehr beurteilt werden. Durch die Akquisition und Dokumentation von standardisierten Videosequenzen der Ultraschallbilder (sogenannte Cine Loops), wird eine sekundäre Nachbetrachtung unter Berücksichtigung von Voraufnahmen analog anderer Schnittbildverfahren wie der CT oder MRT möglich. Die Durchführung könnte dabei auch von nichtärztlichem Personal übernommen werden. Das gewonnene Bildmaterial kann im lokalen PACS gespeichert und für die Lehre und Forschung verwendet werden.

Abstract

Ultrasound is the basic imaging method for the assessment of the thyroid gland. Due to the high prevalence of structural disease, the examination procedure is used very frequently in Germany, in many cases in the context of follow-up. The assessment of thyroid pathologies and their dynamics is subjected to relevant inter- and intraobserver variability. Findings that were not identified during live ultrasound cannot be assessed retrospectively. Applying an SOP for the acquisition and documentation of standardized video sequences of ultrasound images (so-called cine loops), allows for a secondary retrospective evaluation of the thyroid gland, taking into account previously acquired images analogous to other cross-sectional imaging methods such as CT or MRI. The cine loops can be acquired by non-physician personnel, stored to the local PACS and used for educational and research purposes.

Schlüsselwörter

Ultraschall - Schilddrüse - Standardisierung - Videosequenzen - Dokumentation

Keywords

ultrasound - thyroid - SOP - cine loops - documentation

Publication History

Article published online:
26 May 2023

• Literatur

• 1 Kangelaris GT, Kim TB, Orlof LA. Role of ultrasound in thyroid disorders. Otolaryngol Clin North Am 2010; 43: 1209-1227 DOI: 10.1016/j.otc.2010.08.006.
• 2 Lantz M, Almquist M, Koutouridou E. et al. Thyroid ultrasound and its role in the investigation of thyroid disease. Lakartidningen. 2022 119: 22046
• 3 Haugen BR, Alexander EK, Bible KC. et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid 2016; 26: 1-133 DOI: 10.1089/thy.2015.0020.
• 4 Perros P, Boelaert K, Colley S. et al. Guidelines for the management of thyroid cancer. Clin Endocrinol (Oxf) 2014; 81 (Suppl. 01) 1-122 DOI: 10.1111/cen.12515. (PMID: 24989897)
• 5 Dobruch-Sobczak K, Adamczewski Z, Dedecjus M. et al. Summary of Meta-analyses of Studies Involving TIRADS Classifications (EU-TIRADS, ACR-TIRADS, and K-TIRADS) in Evaluating the Malignant Potential of Focal Lesions of The Thyroid Gland. J Ultrason 2022; 22: 121-129 DOI: 10.15557/JoU.2022.0020. (PMID: 35811588)
• 6 Negro R, Greco G. Patients undergoing endocrine consultation and first diagnosis of nodular disease: Indications of thyroid ultrasound and completeness of ultrasound reports. Endocrine 2023; DOI: 10.1007/s12020-023-03301-1. (PMID: 36622626)
• 7 Lim JY, Kuo JH. Thyroid Nodule Radiofrequency Ablation: Complications and Clinical Follow Up. Tech Vasc Interv Radiol 2022; 25: 100824 DOI: 10.1016/j.tvir.2022.100824. (PMID: 35551808)
• 8 Andermann P, Schlogl S, Mader U. et al. Intra- and interobserver variability of thyroid volume measurements in healthy adults by 2D versus 3D ultrasound. Nuklearmedizin 2007; 46: 1-7 (PMID: 17299648)
• 9 Grani G, Lamartina L, Cantisani V. et al. Interobserver agreement of various thyroid imaging reporting and data systems. Endocr Connect 2018; 7: 1-7 DOI: 10.1530/EC-17-0336.
• 10 Seifert P, Gorges R, Zimny M. et al. Interobserver agreement and efficacy of consensus reading in Kwak-, EU-, and ACR-thyroid imaging recording and data systems and ATA guidelines for the ultrasound risk stratification of thyroid nodules. Endocrine 2020; 67: 143-154 DOI: 10.1007/s12020-019-02134-1. (PMID: 31741167)
• 11 Lee MK, Na DG, Joo L. et al. Standardized Imaging and Reporting for Thyroid Ultrasound: Korean Society of Thyroid Radiology Consensus Statement and Recommendation. Korean J Radiol 2023; 24: 22-30 DOI: 10.3348/kjr.2022.0894. (PMID: 36606617)
• 12 Attenhofer CH, Pellikka PA, Oh JK. et al. Is review of videotape necessary after review of digitized cine-loop images in stress echocardiography? A prospective study in 306 patients. J Am Soc Echocardiogr 1997; 10: 179-184 DOI: 10.1016/s0894-7317(97)70091-9. (PMID: 9083974)
• 13 Scott TE, Jones J, Rosenberg H. et al. Increasing the detection rate of congenital heart disease during routine obstetric screening using cine loop sweeps. J Ultrasound Med 2013; 32: 973-979 DOI: 10.7863/ultra.32.6.973.
• 14 Gaarder M, Seierstad T, Soreng R. et al. Standardized cine-loop documentation in renal ultrasound facilitates skill-mix between radiographer and radiologist. Acta Radiol 2015; 56: 368-373 DOI: 10.1177/0284185114527868.
• 15 Dormagen JB, Gaarder M, Drolsum A. Standardized cine-loop documentation in abdominal ultrasound facilitates offline image interpretation. Acta Radiol 2015; 56: 3-9 DOI: 10.1177/0284185113517228. (PMID: 24345769)
• 16 Alyami J, Almutairi FF, Aldoassary S. et al. Interobserver variability in ultrasound assessment of thyroid nodules. Medicine (Baltimore) 2022; 101: e31106 DOI: 10.1097/MD.0000000000031106. (PMID: 36254067)
• 17 Chiu LC, Leonardi M, Lu C. et al. Predicting Pouch of Douglas Obliteration Using Ultrasound and Laparoscopic Video Sets: An Interobserver and Diagnostic Accuracy Study. J Ultrasound Med 2019; 38: 3155-3161 DOI: 10.1002/jum.15015. (PMID: 31037752)
• 18 Youk JH, Jung I, Yoon JH. et al. Comparison of Inter-Observer Variability and Diagnostic Performance of the Fifth Edition of BI-RADS for Breast Ultrasound of Static versus Video Images. Ultrasound Med Biol 2016; 42: 2083-2088 DOI: 10.1016/j.ultrasmedbio.2016.05.006. (PMID: 27324292)
• 19 Stolz LA, Muruganandan KM, Bisanzo MC. et al. Point-of-care ultrasound education for non-physician clinicians in a resource-limited emergency department. Trop Med Int Health 2015; 20: 1067-1072 DOI: 10.1111/tmi.12511. (PMID: 25808431)
• 20 O’Dochartaigh D, Douma M, MacKenzie M. Five-year Retrospective Review of Physician and Non-physician Performed Ultrasound in a Canadian Critical Care Helicopter Emergency Medical Service. Prehosp Emerg Care 2017; 21: 24-31 DOI: 10.1080/10903127.2016.1204036. (PMID: 27436374)
• 21 Barnett M, Pillow MT, Carnell J. et al. Informing the Revolution: A Needs Assessment of Ultrasound Knowledge and Skills Among Graduating Physician Assistant Students. J Physician Assist Educ 2018; 29: 173-176 DOI: 10.1097/JPA.0000000000000210.
• 22 Rizzolo D, Krackov RE. Integration of Ultrasound Into the Physician Assistant Curriculum. J Physician Assist Educ 2019; 30: 103-110 DOI: 10.1097/JPA.0000000000000251. (PMID: 31124808)
• 23 Seifert P, Maikowski I, Winkens T. et al. Ultrasound Cine Loop Standard Operating Procedure for Benign Thyroid Diseases-Evaluation of Non-Physician Application. Diagnostics (Basel) 2021; 11 DOI: 10.3390/diagnostics11010067. (PMID: 33406645)
• 24 Kwak JY, Han KH, Yoon JH. et al. Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk. Radiology 2011; 260: 892-899 DOI: 10.1148/radiol.11110206. (PMID: 21771959)
• 25 Tessler FN, Middleton WD, Grant EG. et al. ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee. J Am Coll Radiol 2017; 14: 587-595 DOI: 10.1016/j.jacr.2017.01.046. (PMID: 28372962)
• 26 Nell S, Kist JW, Debray TP. et al. Qualitative elastography can replace thyroid nodule fine-needle aspiration in patients with soft thyroid nodules. A systematic review and meta-analysis. Eur J Radiol 2015; 84: 652-661 DOI: 10.1016/j.ejrad.2015.01.003.
• 27 Winkens T, Seifert P, Hollenbach C. et al. The FUSION iENA Study: Comparison of I-124-PET/US Fusion Imaging with Conventional Diagnostics for the Functional Assessment of Thyroid Nodules by Multiple Observers. Nuklearmedizin 2019; 58: 434-442 DOI: 10.1055/a-1031-9832.
• 28 Seifert P, Winkens T, Kuhnel C. et al. I-124-PET/US Fusion Imaging in Comparison to Conventional Diagnostics and Tc-99m Pertechnetate SPECT/US Fusion Imaging for the Function Assessment of Thyroid Nodules. Ultrasound Med Biol 2019; 45: 2298-2308 DOI: 10.1016/j.ultrasmedbio.2019.05.008. (PMID: 31196748)
• 29 O’Connor SD, Kulkarni NM, Griffin Jr MO. et al. Structured Reporting in Ultrasound. Ultrasound Q 2020; 36: 1-5 DOI: 10.1097/RUQ.0000000000000447. (PMID: 31107426)
• 30 Wildman-Tobriner B, Ngo L, Jaffe TA. et al. Automated Structured Reporting for Thyroid Ultrasound: Effect on Reporting Errors and Efficiency. J Am Coll Radiol 2021; 18: 265-273 DOI: 10.1016/j.jacr.2020.07.024. (PMID: 32818484)
• 31 Webb JM, Meixner DD, Adusei SA. et al. Automatic Deep Learning Semantic Segmentation of Ultrasound Thyroid Cineclips Using Recurrent Fully Convolutional Networks. IEEE Access 2021; 9: 5119-5127 DOI: 10.1109/access.2020.3045906. (PMID: 33747681)
• 32 Kumar V, Webb J, Gregory A. et al. Automated Segmentation of Thyroid Nodule, Gland, and Cystic Components From Ultrasound Images Using Deep Learning. IEEE Access 2020; 8: 63482-63496 DOI: 10.1109/access.2020.2982390.
• 33 Chambara N, Liu SYW, Lo X. et al. Diagnostic performance evaluation of different TI-RADS using ultrasound computer-aided diagnosis of thyroid nodules: An experience with adjusted settings. PLoS One 2021; 16: e0245617 DOI: 10.1371/journal.pone.0245617.
• 34 Lu WW, Zhang D, Ni XJ. A Review of the Role of Ultrasound Radiomics and Its Application and Limitations in the Investigation of Thyroid Disease. Med Sci Monit 2022; 28: e937738 DOI: 10.12659/MSM.937738. (PMID: 36258648)
• 35 Kronke M, Eilers C, Dimova D. et al. Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry. PLoS One 2022; 17: e0268550 DOI: 10.1371/journal.pone.0268550. (PMID: 35905038)