Prediction of cervical lymph node metastasis in patients with papillary thyroid cancer using combined conventional ultrasound, strain elastography, and acoustic radiation force impulse (ARFI) elastography
Objectives To investigate the value of combined conventional ultrasound (US), strain elastography (SE) and acoustic radiation force impulse (ARFI) elastography for prediction of cervical lymph node metastasis (CLNM) in papillary thyroid cancer (PTC). Methods A consecutive series of 203 patients with...
Gespeichert in:
| Veröffentlicht in: | European radiology 2016-08, Vol.26 (8), p.2611-2622 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2622 |
|---|---|
| container_issue | 8 |
| container_start_page | 2611 |
| container_title | European radiology |
| container_volume | 26 |
| creator | Xu, Jun-Mei Xu, Xiao-Hong Xu, Hui-Xiong Zhang, Yi-Feng Guo, Le-Hang Liu, Lin-Na Liu, Chang Bo, Xiao-Wan Qu, Shen Xing, Mingzhao Li, Xiao-Long |
| description | Objectives
To investigate the value of combined conventional ultrasound (US), strain elastography (SE) and acoustic radiation force impulse (ARFI) elastography for prediction of cervical lymph node metastasis (CLNM) in papillary thyroid cancer (PTC).
Methods
A consecutive series of 203 patients with 222 PTCs were preoperatively evaluated by US, SE, and ARFI including virtual touch tissue imaging (VTI) and virtual touch tissue quantification (VTQ). A multivariate analysis was performed to predict CLNM by 22 independent variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance.
Results
Multivariate analysis demonstrated that VTI area ratio (VAR) > 1 was the best predictor for CLNM, followed by abnormal cervical lymph node (ACLN), capsule contact, microcalcification, capsule involvement, and multiple nodules (all
P
1. As combination of US characteristics with and without VAR, the Az, sensitivity, and specificity were 0.803 and 0.556, 83.0 % and 100.0 %, and 77.6 % and 11.2 %, respectively (
P
|
| doi_str_mv | 10.1007/s00330-015-4088-2 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1846411860</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1801426246</sourcerecordid><originalsourceid>FETCH-LOGICAL-c405t-90be998249eab2f7245564e66cf28ad7e5e909013b120bb98f0b7444b01710113</originalsourceid><addsrcrecordid>eNqNUtGK1TAQLaK46-oH-CIBX1bY6iRN2-RxWVxdWFBEn0uaTu_N0iY1SVfuP_pRzt27igqCEEgmc86ZYeYUxXMOrzlA-yYBVBWUwOtSglKleFAcc1mJkoOSD4tj0JUqW63lUfEkpRsA0Fy2j4sj0dQNtLw-Lr5_jDg4m13wLIzMYrx11kxs2s3LlvkwIJsxm0THJeY8W0x26HNi31zeUrS4aTJxx_J2F4MbmDWeRNianN8wG-beeaTf4G-JRVVIe51yNCmsfjhjiZ6kihOVCJtolu3ujBk_MGPDmrKzLJrBmbv-xhAtMjcv65SQnZ5_urx69QfzafFoNJR7dn-fFF8u336-eF9ef3h3dXF-XVoJdS419Ki1ElKj6cXYClnXjcSmsaNQZmixRg0aeNVzAX2v1Qh9K6XsgbccOK9OitOD7hLD1xVT7maXLNIgPFLXHVeykZyrBv4DClyKRsiGoC__gt6ENdLA7lC0aSXUXpAfUDaGlCKO3RLdTBvoOHR7V3QHV3Tkim7vik4Q58W98trPOPxi_LQBAcQBkCjlNxh_K_1P1R_RVcXF</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1800338280</pqid></control><display><type>article</type><title>Prediction of cervical lymph node metastasis in patients with papillary thyroid cancer using combined conventional ultrasound, strain elastography, and acoustic radiation force impulse (ARFI) elastography</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>Xu, Jun-Mei ; Xu, Xiao-Hong ; Xu, Hui-Xiong ; Zhang, Yi-Feng ; Guo, Le-Hang ; Liu, Lin-Na ; Liu, Chang ; Bo, Xiao-Wan ; Qu, Shen ; Xing, Mingzhao ; Li, Xiao-Long</creator><creatorcontrib>Xu, Jun-Mei ; Xu, Xiao-Hong ; Xu, Hui-Xiong ; Zhang, Yi-Feng ; Guo, Le-Hang ; Liu, Lin-Na ; Liu, Chang ; Bo, Xiao-Wan ; Qu, Shen ; Xing, Mingzhao ; Li, Xiao-Long</creatorcontrib><description>Objectives
To investigate the value of combined conventional ultrasound (US), strain elastography (SE) and acoustic radiation force impulse (ARFI) elastography for prediction of cervical lymph node metastasis (CLNM) in papillary thyroid cancer (PTC).
Methods
A consecutive series of 203 patients with 222 PTCs were preoperatively evaluated by US, SE, and ARFI including virtual touch tissue imaging (VTI) and virtual touch tissue quantification (VTQ). A multivariate analysis was performed to predict CLNM by 22 independent variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance.
Results
Multivariate analysis demonstrated that VTI area ratio (VAR) > 1 was the best predictor for CLNM, followed by abnormal cervical lymph node (ACLN), capsule contact, microcalcification, capsule involvement, and multiple nodules (all
P
< 0.05). ROC analyses of these characteristics showed the areas under the curve (Az), sensitivity, and specificity were 0.600–0.630, 47.7 %–93.2 %, and 26.9 %–78.4 % for US, respectively; and they were 0.784, 83.0 %, and 73.9 %, respectively, for VAR > 1. As combination of US characteristics with and without VAR, the Az, sensitivity, and specificity were 0.803 and 0.556, 83.0 % and 100.0 %, and 77.6 % and 11.2 %, respectively (
P
< 0.001).
Conclusions
ARFI elastography shows superior performance over conventional US, particularly when combined with US, in predicting CLNM in PTC patients.
Key Points
• Conventional ultrasound is useful in predicting cervical lymph node metastasis preoperatively.
• Virtual touch tissue imaging area ratio is the strongest predicting factor.
• Predictive performance is markedly improved by combining ultrasound characteristics with VAR.
• Acoustic radiation force impulse elastography may be a promising complementary tool.</description><identifier>ISSN: 0938-7994</identifier><identifier>EISSN: 1432-1084</identifier><identifier>DOI: 10.1007/s00330-015-4088-2</identifier><identifier>PMID: 26560715</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Acoustics ; Adolescent ; Adult ; Aged ; Calcinosis - diagnostic imaging ; Calcinosis - pathology ; Carcinoma - diagnostic imaging ; Carcinoma - pathology ; Carcinoma, Papillary ; Diagnostic Radiology ; Elasticity Imaging Techniques - methods ; Endocrinology ; Female ; Head and Neck ; Hospitals ; Humans ; Imaging ; Internal Medicine ; Interventional Radiology ; Lymph Nodes - diagnostic imaging ; Lymph Nodes - pathology ; Lymphatic Metastasis ; Lymphatic system ; Male ; Medical prognosis ; Medicine ; Medicine & Public Health ; Metabolism ; Metastasis ; Middle Aged ; Multivariate Analysis ; Neck ; Neoplasms, Multiple Primary - diagnostic imaging ; Neoplasms, Multiple Primary - pathology ; Neuroradiology ; Radiation ; Radiology ; Reproducibility of Results ; ROC Curve ; Thyroid cancer ; Thyroid Cancer, Papillary ; Thyroid Neoplasms - diagnostic imaging ; Thyroid Neoplasms - pathology ; Thyroid Nodule - diagnostic imaging ; Thyroid Nodule - pathology ; Thyroidectomy ; Ultrasonic imaging ; Ultrasonography ; Ultrasound ; Young Adult</subject><ispartof>European radiology, 2016-08, Vol.26 (8), p.2611-2622</ispartof><rights>European Society of Radiology 2015</rights><rights>European Society of Radiology 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c405t-90be998249eab2f7245564e66cf28ad7e5e909013b120bb98f0b7444b01710113</citedby><cites>FETCH-LOGICAL-c405t-90be998249eab2f7245564e66cf28ad7e5e909013b120bb98f0b7444b01710113</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00330-015-4088-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00330-015-4088-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26560715$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xu, Jun-Mei</creatorcontrib><creatorcontrib>Xu, Xiao-Hong</creatorcontrib><creatorcontrib>Xu, Hui-Xiong</creatorcontrib><creatorcontrib>Zhang, Yi-Feng</creatorcontrib><creatorcontrib>Guo, Le-Hang</creatorcontrib><creatorcontrib>Liu, Lin-Na</creatorcontrib><creatorcontrib>Liu, Chang</creatorcontrib><creatorcontrib>Bo, Xiao-Wan</creatorcontrib><creatorcontrib>Qu, Shen</creatorcontrib><creatorcontrib>Xing, Mingzhao</creatorcontrib><creatorcontrib>Li, Xiao-Long</creatorcontrib><title>Prediction of cervical lymph node metastasis in patients with papillary thyroid cancer using combined conventional ultrasound, strain elastography, and acoustic radiation force impulse (ARFI) elastography</title><title>European radiology</title><addtitle>Eur Radiol</addtitle><addtitle>Eur Radiol</addtitle><description>Objectives
To investigate the value of combined conventional ultrasound (US), strain elastography (SE) and acoustic radiation force impulse (ARFI) elastography for prediction of cervical lymph node metastasis (CLNM) in papillary thyroid cancer (PTC).
Methods
A consecutive series of 203 patients with 222 PTCs were preoperatively evaluated by US, SE, and ARFI including virtual touch tissue imaging (VTI) and virtual touch tissue quantification (VTQ). A multivariate analysis was performed to predict CLNM by 22 independent variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance.
Results
Multivariate analysis demonstrated that VTI area ratio (VAR) > 1 was the best predictor for CLNM, followed by abnormal cervical lymph node (ACLN), capsule contact, microcalcification, capsule involvement, and multiple nodules (all
P
< 0.05). ROC analyses of these characteristics showed the areas under the curve (Az), sensitivity, and specificity were 0.600–0.630, 47.7 %–93.2 %, and 26.9 %–78.4 % for US, respectively; and they were 0.784, 83.0 %, and 73.9 %, respectively, for VAR > 1. As combination of US characteristics with and without VAR, the Az, sensitivity, and specificity were 0.803 and 0.556, 83.0 % and 100.0 %, and 77.6 % and 11.2 %, respectively (
P
< 0.001).
Conclusions
ARFI elastography shows superior performance over conventional US, particularly when combined with US, in predicting CLNM in PTC patients.
Key Points
• Conventional ultrasound is useful in predicting cervical lymph node metastasis preoperatively.
• Virtual touch tissue imaging area ratio is the strongest predicting factor.
• Predictive performance is markedly improved by combining ultrasound characteristics with VAR.
• Acoustic radiation force impulse elastography may be a promising complementary tool.</description><subject>Acoustics</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Calcinosis - diagnostic imaging</subject><subject>Calcinosis - pathology</subject><subject>Carcinoma - diagnostic imaging</subject><subject>Carcinoma - pathology</subject><subject>Carcinoma, Papillary</subject><subject>Diagnostic Radiology</subject><subject>Elasticity Imaging Techniques - methods</subject><subject>Endocrinology</subject><subject>Female</subject><subject>Head and Neck</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Imaging</subject><subject>Internal Medicine</subject><subject>Interventional Radiology</subject><subject>Lymph Nodes - diagnostic imaging</subject><subject>Lymph Nodes - pathology</subject><subject>Lymphatic Metastasis</subject><subject>Lymphatic system</subject><subject>Male</subject><subject>Medical prognosis</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolism</subject><subject>Metastasis</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>Neck</subject><subject>Neoplasms, Multiple Primary - diagnostic imaging</subject><subject>Neoplasms, Multiple Primary - pathology</subject><subject>Neuroradiology</subject><subject>Radiation</subject><subject>Radiology</subject><subject>Reproducibility of Results</subject><subject>ROC Curve</subject><subject>Thyroid cancer</subject><subject>Thyroid Cancer, Papillary</subject><subject>Thyroid Neoplasms - diagnostic imaging</subject><subject>Thyroid Neoplasms - pathology</subject><subject>Thyroid Nodule - diagnostic imaging</subject><subject>Thyroid Nodule - pathology</subject><subject>Thyroidectomy</subject><subject>Ultrasonic imaging</subject><subject>Ultrasonography</subject><subject>Ultrasound</subject><subject>Young Adult</subject><issn>0938-7994</issn><issn>1432-1084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNUtGK1TAQLaK46-oH-CIBX1bY6iRN2-RxWVxdWFBEn0uaTu_N0iY1SVfuP_pRzt27igqCEEgmc86ZYeYUxXMOrzlA-yYBVBWUwOtSglKleFAcc1mJkoOSD4tj0JUqW63lUfEkpRsA0Fy2j4sj0dQNtLw-Lr5_jDg4m13wLIzMYrx11kxs2s3LlvkwIJsxm0THJeY8W0x26HNi31zeUrS4aTJxx_J2F4MbmDWeRNianN8wG-beeaTf4G-JRVVIe51yNCmsfjhjiZ6kihOVCJtolu3ujBk_MGPDmrKzLJrBmbv-xhAtMjcv65SQnZ5_urx69QfzafFoNJR7dn-fFF8u336-eF9ef3h3dXF-XVoJdS419Ki1ElKj6cXYClnXjcSmsaNQZmixRg0aeNVzAX2v1Qh9K6XsgbccOK9OitOD7hLD1xVT7maXLNIgPFLXHVeykZyrBv4DClyKRsiGoC__gt6ENdLA7lC0aSXUXpAfUDaGlCKO3RLdTBvoOHR7V3QHV3Tkim7vik4Q58W98trPOPxi_LQBAcQBkCjlNxh_K_1P1R_RVcXF</recordid><startdate>20160801</startdate><enddate>20160801</enddate><creator>Xu, Jun-Mei</creator><creator>Xu, Xiao-Hong</creator><creator>Xu, Hui-Xiong</creator><creator>Zhang, Yi-Feng</creator><creator>Guo, Le-Hang</creator><creator>Liu, Lin-Na</creator><creator>Liu, Chang</creator><creator>Bo, Xiao-Wan</creator><creator>Qu, Shen</creator><creator>Xing, Mingzhao</creator><creator>Li, Xiao-Long</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope></search><sort><creationdate>20160801</creationdate><title>Prediction of cervical lymph node metastasis in patients with papillary thyroid cancer using combined conventional ultrasound, strain elastography, and acoustic radiation force impulse (ARFI) elastography</title><author>Xu, Jun-Mei ; Xu, Xiao-Hong ; Xu, Hui-Xiong ; Zhang, Yi-Feng ; Guo, Le-Hang ; Liu, Lin-Na ; Liu, Chang ; Bo, Xiao-Wan ; Qu, Shen ; Xing, Mingzhao ; Li, Xiao-Long</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c405t-90be998249eab2f7245564e66cf28ad7e5e909013b120bb98f0b7444b01710113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Acoustics</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Calcinosis - diagnostic imaging</topic><topic>Calcinosis - pathology</topic><topic>Carcinoma - diagnostic imaging</topic><topic>Carcinoma - pathology</topic><topic>Carcinoma, Papillary</topic><topic>Diagnostic Radiology</topic><topic>Elasticity Imaging Techniques - methods</topic><topic>Endocrinology</topic><topic>Female</topic><topic>Head and Neck</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Imaging</topic><topic>Internal Medicine</topic><topic>Interventional Radiology</topic><topic>Lymph Nodes - diagnostic imaging</topic><topic>Lymph Nodes - pathology</topic><topic>Lymphatic Metastasis</topic><topic>Lymphatic system</topic><topic>Male</topic><topic>Medical prognosis</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolism</topic><topic>Metastasis</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>Neck</topic><topic>Neoplasms, Multiple Primary - diagnostic imaging</topic><topic>Neoplasms, Multiple Primary - pathology</topic><topic>Neuroradiology</topic><topic>Radiation</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>ROC Curve</topic><topic>Thyroid cancer</topic><topic>Thyroid Cancer, Papillary</topic><topic>Thyroid Neoplasms - diagnostic imaging</topic><topic>Thyroid Neoplasms - pathology</topic><topic>Thyroid Nodule - diagnostic imaging</topic><topic>Thyroid Nodule - pathology</topic><topic>Thyroidectomy</topic><topic>Ultrasonic imaging</topic><topic>Ultrasonography</topic><topic>Ultrasound</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Jun-Mei</creatorcontrib><creatorcontrib>Xu, Xiao-Hong</creatorcontrib><creatorcontrib>Xu, Hui-Xiong</creatorcontrib><creatorcontrib>Zhang, Yi-Feng</creatorcontrib><creatorcontrib>Guo, Le-Hang</creatorcontrib><creatorcontrib>Liu, Lin-Na</creatorcontrib><creatorcontrib>Liu, Chang</creatorcontrib><creatorcontrib>Bo, Xiao-Wan</creatorcontrib><creatorcontrib>Qu, Shen</creatorcontrib><creatorcontrib>Xing, Mingzhao</creatorcontrib><creatorcontrib>Li, Xiao-Long</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>European radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Jun-Mei</au><au>Xu, Xiao-Hong</au><au>Xu, Hui-Xiong</au><au>Zhang, Yi-Feng</au><au>Guo, Le-Hang</au><au>Liu, Lin-Na</au><au>Liu, Chang</au><au>Bo, Xiao-Wan</au><au>Qu, Shen</au><au>Xing, Mingzhao</au><au>Li, Xiao-Long</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of cervical lymph node metastasis in patients with papillary thyroid cancer using combined conventional ultrasound, strain elastography, and acoustic radiation force impulse (ARFI) elastography</atitle><jtitle>European radiology</jtitle><stitle>Eur Radiol</stitle><addtitle>Eur Radiol</addtitle><date>2016-08-01</date><risdate>2016</risdate><volume>26</volume><issue>8</issue><spage>2611</spage><epage>2622</epage><pages>2611-2622</pages><issn>0938-7994</issn><eissn>1432-1084</eissn><abstract>Objectives
To investigate the value of combined conventional ultrasound (US), strain elastography (SE) and acoustic radiation force impulse (ARFI) elastography for prediction of cervical lymph node metastasis (CLNM) in papillary thyroid cancer (PTC).
Methods
A consecutive series of 203 patients with 222 PTCs were preoperatively evaluated by US, SE, and ARFI including virtual touch tissue imaging (VTI) and virtual touch tissue quantification (VTQ). A multivariate analysis was performed to predict CLNM by 22 independent variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance.
Results
Multivariate analysis demonstrated that VTI area ratio (VAR) > 1 was the best predictor for CLNM, followed by abnormal cervical lymph node (ACLN), capsule contact, microcalcification, capsule involvement, and multiple nodules (all
P
< 0.05). ROC analyses of these characteristics showed the areas under the curve (Az), sensitivity, and specificity were 0.600–0.630, 47.7 %–93.2 %, and 26.9 %–78.4 % for US, respectively; and they were 0.784, 83.0 %, and 73.9 %, respectively, for VAR > 1. As combination of US characteristics with and without VAR, the Az, sensitivity, and specificity were 0.803 and 0.556, 83.0 % and 100.0 %, and 77.6 % and 11.2 %, respectively (
P
< 0.001).
Conclusions
ARFI elastography shows superior performance over conventional US, particularly when combined with US, in predicting CLNM in PTC patients.
Key Points
• Conventional ultrasound is useful in predicting cervical lymph node metastasis preoperatively.
• Virtual touch tissue imaging area ratio is the strongest predicting factor.
• Predictive performance is markedly improved by combining ultrasound characteristics with VAR.
• Acoustic radiation force impulse elastography may be a promising complementary tool.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>26560715</pmid><doi>10.1007/s00330-015-4088-2</doi><tpages>12</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0938-7994 |
| ispartof | European radiology, 2016-08, Vol.26 (8), p.2611-2622 |
| issn | 0938-7994 1432-1084 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1846411860 |
| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Acoustics Adolescent Adult Aged Calcinosis - diagnostic imaging Calcinosis - pathology Carcinoma - diagnostic imaging Carcinoma - pathology Carcinoma, Papillary Diagnostic Radiology Elasticity Imaging Techniques - methods Endocrinology Female Head and Neck Hospitals Humans Imaging Internal Medicine Interventional Radiology Lymph Nodes - diagnostic imaging Lymph Nodes - pathology Lymphatic Metastasis Lymphatic system Male Medical prognosis Medicine Medicine & Public Health Metabolism Metastasis Middle Aged Multivariate Analysis Neck Neoplasms, Multiple Primary - diagnostic imaging Neoplasms, Multiple Primary - pathology Neuroradiology Radiation Radiology Reproducibility of Results ROC Curve Thyroid cancer Thyroid Cancer, Papillary Thyroid Neoplasms - diagnostic imaging Thyroid Neoplasms - pathology Thyroid Nodule - diagnostic imaging Thyroid Nodule - pathology Thyroidectomy Ultrasonic imaging Ultrasonography Ultrasound Young Adult |
| title | Prediction of cervical lymph node metastasis in patients with papillary thyroid cancer using combined conventional ultrasound, strain elastography, and acoustic radiation force impulse (ARFI) elastography |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-13T01%3A48%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prediction%20of%20cervical%20lymph%20node%20metastasis%20in%20patients%20with%20papillary%20thyroid%20cancer%20using%20combined%20conventional%20ultrasound,%20strain%20elastography,%20and%20acoustic%20radiation%20force%20impulse%20(ARFI)%20elastography&rft.jtitle=European%20radiology&rft.au=Xu,%20Jun-Mei&rft.date=2016-08-01&rft.volume=26&rft.issue=8&rft.spage=2611&rft.epage=2622&rft.pages=2611-2622&rft.issn=0938-7994&rft.eissn=1432-1084&rft_id=info:doi/10.1007/s00330-015-4088-2&rft_dat=%3Cproquest_cross%3E1801426246%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1800338280&rft_id=info:pmid/26560715&rfr_iscdi=true |