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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

This study aims to explore the feasibility of fine-needle aspiration biopsy (FNAB) under dual modal photoacoustic tomography(PAT)/ultrasound (US) imaging. A total of 25 patients who have thyroid nodules with thyroid imaging reporting and data system (TIRADS) 3 and 4 (malignant risk <85%) were recruited. The specimens obtained from the PAT/US-guided FNAB were collected for cytology analysis. Cytological diagnoses for the 25 patients were classified in perspective of the Bethesda system for reporting thyroid cytopathology diagnostic category (DC) I: 4%(1/25); DC II: 12% (3/25); DC III: 20% (5/25); DC IV: 8% (2/25); DC V: 32% (8/25); and DC VI: 24% (6/25). The DC I nodule exhibited inadequate cytology and had structural characteristic of predominant calcifications in PAT/US mapping. The DC V-VI nodules showed lower photoacoustic (PA) signals compared to the DC I-IV nodules. Regions with a high PA signal demonstrated a significant number of erythrocytes in FNAB cytology. Moreover, nodules with microcalcifications did not show a significant difference compared to their surroundings in the PA signal, while nodules with macrocalcifications gave higher PA signals compared to their surroundings. The conclusions are as follows: combining US with PAT can evaluate the structure and function of thyroid nodules in vivo. This study demonstrates that dual modal PAT/US imaging has the potential to be an effective clinical tool to guide FNAB of thyroid nodules.

Details

Title
Photoacoustic Tomography Combined with Ultrasound Mapping for Guiding Fine-Needle Aspiration of Thyroid Nodules: A Pilot Study
Author
Wen, Yanting 1 ; Wu, Dan 2 ; Liu, Xiaotian 3 ; Xie, Yonghua 2 ; Zhang, Jing 1 ; Yang, Ying 1 ; Wu, Yun 4 ; Jiang, Shixie 5 ; Jiang, Huabei 6 

 School of Computer Science and Technology/School of Artificial Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; [email protected] (Y.W.); [email protected] (D.W.); [email protected] (Y.X.); [email protected] (J.Z.); [email protected] (Y.Y.); Department of Ultrasound, Chengdu Fifth People’s Hospital/The Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China; [email protected] 
 School of Computer Science and Technology/School of Artificial Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; [email protected] (Y.W.); [email protected] (D.W.); [email protected] (Y.X.); [email protected] (J.Z.); [email protected] (Y.Y.) 
 Department of Ultrasound, Chengdu Fifth People’s Hospital/The Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China; [email protected] 
 Health Management Department, Chengdu Women’s and Children’s Central Hospital/The Affiliated Hospital, School of Medicine, UESTC, Chengdu 610031, China; [email protected] 
 Department of Psychiatry, University of Florida College of Medicine, Gainesville, FL 32610, USA; [email protected] 
 Department of Medical Engineering, University of South Florida, Tampa, FL 33620, USA 
First page
1190
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
23046732
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2893091764
Copyright
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.