1
|
Ma Y, Li S, Huang G, Huang X, Zhou Q, Wang W, Wang J, Zhao F, Li Z, Chen X, Zhu B, Zhou J. Role of iodine density value on dual-energy CT for detection of high tumor cell proportion region in lung cancer during CT-guided transthoracic biopsy. Eur J Radiol 2023; 160:110689. [PMID: 36669332 DOI: 10.1016/j.ejrad.2023.110689] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 01/01/2023] [Accepted: 01/03/2023] [Indexed: 01/09/2023]
Abstract
OBJECTIVE This study aimed to identify regions with at least 20% tumor cell content in lung cancer tumors by using spectral parameters from dual-layer spectral detector computed tomography (SDCT) to design the puncture path for transthoracic lung biopsy (TTLB). MATERIALS AND METHODS This prospective study recruited patients with suspected lung cancer. Forty-one patients were enrolled to identify the high tumor cell proportion region (HTPR) and then another 15 patients to validate the accuracy of the HTPR. In each of the 41 patients, the suspected regions with high or low tumor cell proportions were punctured according to local iodine density (IoD) values for separate biopsies. The tumor cell proportions of 82 specimens were assessed and classified into high and low tumor cell proportions based on the threshold value of 20 %. The performance of spectral parameters was analyzed to distinguish the HTPR (tumor cell proportion ≥ 20 %) from the low tumor cell proportion region (LTPR). The cutoff value of optimal spectral parameter was used to prospectively guide the biopsy of the HTPR in 15 cases for further validation, and then the accuracy was calculated. RESULTS The AUC values of spectral parameters were all higher than those of CTconventional in identifying the HTPR (all P < 0.05). The IoD with a cutoff value of 0.59 mg/mL in arterial phase (AP) yielded good performance (specificity: 97.10 %) in identifying the HTPR. It was applied to 15 cases for validation, and the accuracy rate was 100 %. CONCLUSION Spectral CT parameters can be used to identify regions with at least 20% tumor cell content in lung cancer for biopsies.
Collapse
Affiliation(s)
- Yaqiong Ma
- Second Clinical School, Lanzhou University, 730030 Lanzhou, China; Department of Radiology, Gansu Provincial Hospital, 730030 Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, 730030 Lanzhou, China
| | - Shenglin Li
- Second Clinical School, Lanzhou University, 730030 Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, 730030 Lanzhou, China
| | - Gang Huang
- Department of Radiology, Gansu Provincial Hospital, 730030 Lanzhou, China
| | - Xiaoyu Huang
- Second Clinical School, Lanzhou University, 730030 Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, 730030 Lanzhou, China
| | - Qing Zhou
- Second Clinical School, Lanzhou University, 730030 Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, 730030 Lanzhou, China
| | - Wenna Wang
- Department of Radiology, Gansu Provincial Hospital, 730030 Lanzhou, China
| | - Jinsui Wang
- Department of Pathology, Gansu Provincial Hospital, 730030 Lanzhou, China
| | - Fenghui Zhao
- Department of Pathology, Gansu Provincial Hospital, 730030 Lanzhou, China
| | - Zhenjun Li
- Department of Pathology, Gansu Provincial Hospital, 730030 Lanzhou, China
| | - Xingbiao Chen
- Clinical Science, Philips Healthcare, Shanghai, 200070, Shanghai, China
| | - Bingyin Zhu
- Department of Radiology, Gansu Provincial Hospital, 730030 Lanzhou, China
| | - Junlin Zhou
- Second Clinical School, Lanzhou University, 730030 Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, 730030 Lanzhou, China; Department of Radiology, Lanzhou University Second Hospital, 730030 Lanzhou, China.
| |
Collapse
|