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Spectral computed tomography iodine concentration spatial distribution and multi-parameter quantitative analysis in
Jiawei He1,2, Sheng Mao2, Hu Yuan2
1Department of Radiology, Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Background:
Central small cell lung cancer (SCLC) and squamous cell carcinoma (SCC) are distinct types of lung cancer that require different treatment approaches and have varying prognoses. Accurate differentiation is crucial for clinical decision-making. However, traditional computed tomography (CT) may face challenges when their imaging features overlap. Spectral CT provides additional spectral images, offering more objective information for differentiation. This study investigated the application values of iodine concentration spatial distribution and multi-parameter quantitative analysis using a novel double-layer detector energy spectrum CT in the differential diagnosis of SCLC and SCC.
Methods:
Sixty-six patients with central lung cancer (including 31 patients with SCLC and 35 patients with SCC) were examined with CT spectral imaging during arterial phase (AP) and venous phase (VP). The mean iodine concentration (IC), mean effective atomic number (Eff-Z), normalized iodine concentration (NIC), normalized iodine concentration in the proximal region (NICpro), normalized iodine concentration in the distal region (NICdis), and the differences in NIC between the proximal and distal regions in the AP and VP were calculated. The differences in parameters between central SCLC and SCC were compared, and receiver operating characteristic (ROC) curves were generated to explore the value of these parameters in distinguishing between central SCLC and SCC.
Results:
The Eff-Z, IC, and NIC of SCLC were higher than SCC in the AP and VP. In terms of the spatial distribution differences in iodine concentration, both NICpro and NICdis during AP and VP were higher in SCLC compared to SCC. Moreover, ROC analysis showed that the NICdis in the VP had highest diagnostic performance in differentiating SCLC from SCC with an area under the receiver operating characteristic curve of 0.897, sensitivity of 96.80%, and a critical threshold of 0.175.
Conclusions:
CT spectral imaging proves beneficial in diagnosing and differentiating between central SCLC and SCC, demonstrating significant clinical application value. Particularly, the spatial distribution of iodine concentration emerges as a valuable factor capable of enhancing diagnostic efficiency, showcasing undeniable potential.
