Dual-energy x-ray approach for object/energy-specific attenuation coefficient correction in single-photon emission computed tomography: effects of contrast agent

Can spectral computed tomography (CT) replace perfusion CT to assess the histological classification of non-small cell lung cancer?

Background

Non-small cell lung cancer (NSCLC) accounts for 80% of total lung cancer cases, it is necessary to distinguish the histological types of NSCLC. This study set out to investigate the correlation between spectral computed tomography (CT) and CT perfusion parameters in patients with NSCLC and to compare the differential diagnostic efficacy of these two imaging modalities for the histological classification of NSCLC.

Methods

A total of 62 eligible consecutive patients, including 32 with lung adenocarcinoma (LUAD) and 30 with lung squamous cell carcinoma (LUSC), who underwent "one-stop" spectral combined perfusion scan and pathologically confirmed NSCLC at Lanzhou University Second Hospital between September 2020 and December 2021 were prospectively enrolled. The spectral parameters of lesions in the arterial phase (AP) and venous phase (VP) [including iodine concentration (IC), effective atomic number (Zeff), CT40keV, and slope of the spectral curve (K70keV)] and perfusion parameters [blood flow (BF), blood volume (BV), surface permeability (PS), and mean transit time (MTT)] were assessed. Pearson or Spearman correlation analysis was performed to evaluate the correlation between the two imaging parameters, and the DeLong test was used to compare the diagnostic performance of the two imaging modalities.

Results

BV and BF were strongly correlated with spectral parameters CT40keV, IC, Zeff, and K70keV in the AP and VP (0.6

Conclusions

Spectral parameters are significantly correlated with perfusion parameters in NSCLC, and spectral CT has a better diagnostic efficacy than perfusion CT in differentiating the histological classification of NSCLC.

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Key Words

• Non-small cell lung cancer (NSCLC)
• perfusion CT
• spectral CT

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Affiliation(s)

Liangna Deng Second Clinical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Jingjing Yang Second Clinical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Tiezhu Ren Second Clinical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Mengyuan Jing Second Clinical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Tao Han Second Clinical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Bin Zhang Second Clinical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Junlin Zhou Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China

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Special Section Guest Editorial: Computed tomography (CT) at 50 years

Guest editors Patrick La Riviere, Rebecca Fahrig, and Norbert Pelc introduce the JMI Special Section Celebrating X-Ray Computed Tomography at 50.