OBJECTIVE: To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) combined with conventional ultrasound of axillary lymph nodes (ALNs) in predicting metastatic ALNs in patients with breast cancer. METHODS: This retrospective study included 259 patients with breast cancer who underwent conventional ultrasound and CEUS. The parameters and patterns evaluated on conventional ultrasound included short axis diameter (S), long axis/short axis (L/S) ratio, cortical thickness, resistive index (RI), lymph node (LN) morphology of greyscale ultrasound, hilum and vascular pattern. Meanwhile, enhancement pattern, wash-in time, time to peak (TP), maximum signal intensity, and duration of contrast enhancement were evaluated on CEUS. Univariate and multiple logistic regression analyses were performed to identify independent factors of ALN status. Three models (conventional ultrasound, CEUS, and combined parameters) were established. Receiver operating characteristic (ROC) curves were applied to evaluate the accuracy of the three predictive models. RESULTS: On conventional axillary ultrasound, LN morphology and vascular pattern were independent factors in predicting metastatic ALNs. On CEUS, maximum signal intensity, duration of contrast enhancement, and TP were independent factors in predicting metastatic ALNs. When combining conventional ultrasound and CEUS features, five independent factors obtained from the conventional ultrasound and CEUS were associated with ALN status. ROC curve analysis showed that the use of CEUS markers combined with conventional ultrasound features (AUC = 0.965) was superior to the use of CEUS markers (AUC = 0.936) and conventional ultrasound features alone (AUC = 0.851). CONCLUSION: Combining conventional ultrasound and CEUS features can enable discrimination of ALN status better than the use of CEUS and conventional ultrasound features alone. ADVANCES IN KNOWLEDGE: The axillary lymph node status in breast cancer patients impacts the treatment decision. Our ultrasonic data demonstrated that CEUS features of ALNs in breast cancer patients could be image markers for predicting ALN status. Combining conventional ultrasound and CEUS features of ALNs can improve specificity discrimination of ALN status better than the use of CEUS and the conventional ultrasound features alone, which will help the treatment planning optimization.
OBJECTIVE: To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) combined with conventional ultrasound of axillary lymph nodes (ALNs) in predicting metastatic ALNs in patients with breast cancer. METHODS: This retrospective study included 259 patients with breast cancer who underwent conventional ultrasound and CEUS. The parameters and patterns evaluated on conventional ultrasound included short axis diameter (S), long axis/short axis (L/S) ratio, cortical thickness, resistive index (RI), lymph node (LN) morphology of greyscale ultrasound, hilum and vascular pattern. Meanwhile, enhancement pattern, wash-in time, time to peak (TP), maximum signal intensity, and duration of contrast enhancement were evaluated on CEUS. Univariate and multiple logistic regression analyses were performed to identify independent factors of ALN status. Three models (conventional ultrasound, CEUS, and combined parameters) were established. Receiver operating characteristic (ROC) curves were applied to evaluate the accuracy of the three predictive models. RESULTS: On conventional axillary ultrasound, LN morphology and vascular pattern were independent factors in predicting metastatic ALNs. On CEUS, maximum signal intensity, duration of contrast enhancement, and TP were independent factors in predicting metastatic ALNs. When combining conventional ultrasound and CEUS features, five independent factors obtained from the conventional ultrasound and CEUS were associated with ALN status. ROC curve analysis showed that the use of CEUS markers combined with conventional ultrasound features (AUC = 0.965) was superior to the use of CEUS markers (AUC = 0.936) and conventional ultrasound features alone (AUC = 0.851). CONCLUSION: Combining conventional ultrasound and CEUS features can enable discrimination of ALN status better than the use of CEUS and conventional ultrasound features alone. ADVANCES IN KNOWLEDGE: The axillary lymph node status in breast cancer patients impacts the treatment decision. Our ultrasonic data demonstrated that CEUS features of ALNs in breast cancer patients could be image markers for predicting ALN status. Combining conventional ultrasound and CEUS features of ALNs can improve specificity discrimination of ALN status better than the use of CEUS and the conventional ultrasound features alone, which will help the treatment planning optimization.
Authors: Deepak G Bedi; Rajesh Krishnamurthy; Savitri Krishnamurthy; Beth S Edeiken; Huong Le-Petross; Bruno D Fornage; Roland L Bassett; Kelly K Hunt Journal: AJR Am J Roentgenol Date: 2008-09 Impact factor: 3.959
Authors: Judy C Boughey; Karla V Ballman; Kelly K Hunt; Linda M McCall; Elizabeth A Mittendorf; Gretchen M Ahrendt; Lee G Wilke; Huong T Le-Petross Journal: J Clin Oncol Date: 2015-02-02 Impact factor: 44.544
Authors: Carlos A Garcia-Etienne; Alberta Ferrari; Angelica Della Valle; Marco Lucioni; Elisa Ferraris; Giuseppe Di Giulio; Luigi Squillace; Elisabetta Bonzano; Angioletta Lasagna; Gianpiero Rizzo; Richard Tancredi; Andrea Scotti Foglieni; Francesca Dionigi; Maurizia Grasso; Eloisa Arbustini; Giorgio Cavenaghi; Paolo Pedrazzoli; Andrea R Filippi; Paolo Dionigi; Adele Sgarella Journal: Eur J Surg Oncol Date: 2019-08-13 Impact factor: 4.424
Authors: Mila Donker; Geertjan van Tienhoven; Marieke E Straver; Philip Meijnen; Cornelis J H van de Velde; Robert E Mansel; Luigi Cataliotti; A Helen Westenberg; Jean H G Klinkenbijl; Lorenzo Orzalesi; Willem H Bouma; Huub C J van der Mijle; Grard A P Nieuwenhuijzen; Sanne C Veltkamp; Leen Slaets; Nicole J Duez; Peter W de Graaf; Thijs van Dalen; Andreas Marinelli; Herman Rijna; Marko Snoj; Nigel J Bundred; Jos W S Merkus; Yazid Belkacemi; Patrick Petignat; Dominic A X Schinagl; Corneel Coens; Carlo G M Messina; Jan Bogaerts; Emiel J T Rutgers Journal: Lancet Oncol Date: 2014-10-15 Impact factor: 41.316
Authors: Igor Langer; Ulrich Guller; Gilles Berclaz; Ossi R Koechli; Gabriel Schaer; Mathias K Fehr; Thomas Hess; Daniel Oertli; Lucio Bronz; Beate Schnarwyler; Edward Wight; Urs Uehlinger; Eduard Infanger; Daniel Burger; Markus Zuber Journal: Ann Surg Date: 2007-03 Impact factor: 12.969
Authors: L Rubaltelli; V Beltrame; E Scagliori; E Bezzon; A C Frigo; M Rastrelli; R Stramare Journal: Ultraschall Med Date: 2013-07-16 Impact factor: 6.548
Authors: José Luiz B Bevilacqua; Michael W Kattan; Jane V Fey; Hiram S Cody; Patrick I Borgen; Kimberly J Van Zee Journal: J Clin Oncol Date: 2007-07-30 Impact factor: 44.544