Evidence map›Paper›PMID 42701536›Full record

ArticleQuantitative imaging in medicine and surgery2026

Spectral computed tomography multi-parameter images for differentiating between tumor tissue and inflammatory tissue in pneumonic-type lung carcinoma lesions.

Ya-Qiong Ma, Yong-Kun Zheng, Qian-Xiao Han, Xiao-Yue Zhang, Gang Huang, Li-Li Wang, Zhi-Mei Jiao

Abstract read
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Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ya-Qiong Ma *Department of Radiology, Gansu Provincial Hospital, Lanzhou, China.
Yong-Kun Zheng *First Clinical Medical College, Gansu University of Chinese Medicine, Lanzhou, China.
Qian-Xiao HanFirst Clinical Medical College, Gansu University of Chinese Medicine, Lanzhou, China.
Xiao-Yue ZhangDepartment of Clinical Science, Philips Healthcare China, Xi'an, China.
Gang HuangDepartment of Radiology, Gansu Provincial Hospital, Lanzhou, China.
Li-Li WangDepartment of Radiology, Gansu Provincial Hospital, Lanzhou, China.
Zhi-Mei JiaoDepartment of Medical Imaging, Zhangye People's Hospital Affiliated to Hexi University, Zhangye, China.ORCID https://orcid.org/0009-0007-0854-903X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pneumonic-type lung carcinoma (PTLC) is a special type of lung cancer with imaging manifestations similar to pneumonia. Due to the intralesional heterogeneity of PTLC, it is difficult to accurately select the optimal target for needle biopsy. Differentiating between tumor tissue and inflammatory tissue within the lesion before puncture could significantly increase the biopsy rate and facilitate early diagnosis. This study aimed to investigate the utility of spectral computed tomography (CT) parameters in differentiating between tumor tissue and inflammatory tissue in PTLC lesions, providing a novel method for target selection before needle biopsy. Methods: A total of 102 patients with PTLC and 96 patients with pneumonia were retrospectively enrolled in the study between September 2020 and April 2024 to evaluate the differentiation of tumor and inflammatory tissue components in PTLC lesions. An additional 30 patients with high suspicion of PTLC were prospectively enrolled to validate the diagnostic accuracy of tumor tissue localization. All patients underwent contrast-enhanced spectral CT examinations, and final diagnoses were confirmed based on pathological findings and follow-up CT evaluations. The ability to visually distinguish tumor tissue from inflammatory tissue in PTLC lesions using conventional CT imaging and spectral CT imaging was evaluated. Conventional CT (CT Results: Among the 102 patients with PTLC, the numbers of cases in which tumor tissue and inflammatory tissue could be differentiated on AP/venous phase (VP) images were 34/27 for conventional CT images, 90/81 for ID images, 87/71 on 40-keV monoenergetic images, and 95/84 for Zeff images, respectively. Spectral CT images exhibited significantly higher discriminatory efficiency than conventional CT images (Q =157.48 for AP and Q =138.87 for VP; both P<0.001). In both the AP and VP, the SIAs presented with significantly higher CT Conclusions: Spectral CT parametric imaging can effectively differentiate tumor tissue from inflammatory tissue in PTLC lesions and may facilitate accurate target selection for biopsy.

Indexed as

biopsydual-layer spectral detector computed tomography (dual-layer SDCT)lung neoplasmsPneumonic-type

Identifiers

PMID42701536
PMCPMC13545578

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.