Evidence map›Paper›PMID 36033815›Full record

ArticleFrontiers in public health2022

Dynamic change of COVID-19 lung infection evaluated using co-registration of serial chest CT images.

Xiao Chen, Yang Zhang, Guoquan Cao, Jiahuan Zhou, Ya Lin, Boyang Chen, Ke Nie, Gangze Fu, Min-Ying Su, Meihao Wang

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Article in Frontiers in public health, 2022. 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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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Xiao ChenDepartment of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Yang ZhangDepartment of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, United States.
Guoquan CaoDepartment of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Jiahuan ZhouDepartment of Radiology, Yuyao Hospital of Traditional Chinese Medicine, Ningbo, China.
Ya LinThe People's Hospital of Cangnan, Wenzhou, China.
Boyang ChenNingbo No. 6 Hospital, Ningbo, China.
Ke NieDepartment of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, United States.
Gangze FuDepartment of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Min-Ying SuDepartment of Radiological Sciences, University of California, Irvine, CA, United States.
Meihao WangDepartment of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To evaluate the volumetric change of COVID-19 lesions in the lung of patients receiving serial CT imaging for monitoring the evolution of the disease and the response to treatment. Materials and methods: A total of 48 patients, 28 males and 20 females, who were confirmed to have COVID-19 infection and received chest CT examination, were identified. The age range was 21-93 years old, with a mean of 54 ± 18 years. Of them, 33 patients received the first follow-up (F/U) scan, 29 patients received the second F/U scan, and 11 patients received the third F/U scan. The lesion region of interest (ROI) was manually outlined. A two-step registration method, first using the Affine alignment, followed by the non-rigid Demons algorithm, was developed to match the lung areas on the baseline and F/U images. The baseline lesion ROI was mapped to the F/U images using the obtained geometric transformation matrix, and the radiologist outlined the lesion ROI on F/U CT again. Results: The median (interquartile range) lesion volume (cm Conclusion: The results suggest that the registration method can be applied to assist in the evaluation of longitudinal changes of COVID-19 lesions on chest CT.

Indexed as

COVID-19AdultAgedAged, 80 and overAlgorithmsFemaleHumansLungMaleMiddle AgedTomography, X-Ray ComputedYoung Adultcomputed tomographyCOVID-19dynamic changespneumoniaregistration

Identifiers

PMID36033815
PMCPMC9412202

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