A Paradigm Shift in Oncology Imaging: a Prospective Cross-sectional Study to Assess Low-dose Deep Learning Image Reconstruction Versus Standard-dose Iterative Reconstruction for Comprehensive Lesion Detection in Dual-energy Computed Tomography

Overview

Journal Quant Imaging Med Surg

Specialty Radiology

Date 2024 Sep 16

PMID 39281146

Authors

Ping Hou

Nana Liu

Xiangnan Feng

Yan Chen

Huixia Wang

Xiaopeng Wang

Jie Liu

Pengchao Zhan

Xing Liu

Bo Shang

Zhimeng Shen

Luotong Wang

Jianbo Gao

Peijie Lyu

Affiliations

Soon will be listed here.

Abstract

Background: Low-kiloelectron volt (keV) virtual monochromatic images (VMIs) from low-dose (LD) dual-energy computed tomography (DECT) can enhance lesion contrast but suffer from high image noise. Recently, a deep learning image reconstruction (DLIR) algorithm has been developed and shown significant potential in suppressing image noise and improving image quality. To date, the capacity of LD low-keV thoracic-abdominal-pelvic DECT with DLIR to detect various types of tumor lesions have not been assessed. Hence, this study aimed to evaluate the image quality and lesion detection capabilities of LD VMIs using DLIR with thoracic-abdominal-pelvic DECT versus standard-dose (SD) iterative reconstruction (IR) in oncology patients.

Methods: This prospective intraindividual study included 56 oncology patients who received a SD (13.86 mGy) and a consecutive LD (7.15 mGy) thoracic-abdominal-pelvic DECT from April 2022 to July 2023 at The First Affiliated hospital of Zhengzhou University. SD VMIs were reconstructed using IR at 50 keV (SD-IR), while LD VMIs were processed using DLIR at 50 keV (LD-DL) and 40 keV (LD-DL), respectively. Quantitative image parameters [computed tomography (CT) values, image noise, and contrast-to-noise ratios (CNRs)], qualitative metrics (image noise, vessel conspicuity, image contrast, artificial sensation, and overall image quality), and lesion CNRs and conspicuity were compared. The lesion detection rates in the SD-IR, LD-DL, and LD-DL VMIs were assessed according to lesion location (lung, liver, and lymph), type, and size. Repeated measures analysis of variance and the Friedman test were applied for comparing quantitative and qualitative measures, respectively. The Cochran Q test was used for comparing lesion detection rates.

Results: Compared to SD-IR VMIs, LD-DL VMIs showed similar CT values and image noise (P>0.05), similar (P>0.05) or higher(P<0.05) CNRs, similar (P>0.05) or superior (P<0.05) perceptual image quality, and similar (P>0.05) or higher (P<0.001) lesion CNR and conspicuity. LD-DL VMIs exhibited higher CT values (by 40.4-47.1%) and CNRs (by 21.8-39.8%) (P<0.001), equivalent image noise, similar (P>0.05) or superior (P<0.05) perceptual image quality except for artificial sensation, and similar (P>0.05) or higher (P<0.001) lesion CNRs (by 16.5-46.3%) and conspicuity. The VMIs of LD-DL and LD-DL were consistent with those of SD-IR in terms of lesion detection capability in pulmonary nodules [SD-IR LD-DL LD-DL: 88/88 (100.0%) 88/88 (100.0%) 88/88 (100.0%); P>0.99], for lymph nodes [125/126 (99.2%) 123/126 (97.6%) 124/126 (98.4%); P>0.05], and high-contrast liver lesions [12/12 (100.0%) 12/12 (100.0%) 12/12 (100.0%); P>0.05], but not for small liver lesions (≤0.5 cm) [63/65 (96.9%) 43/65 (66.2%) 51/65 (78.5%); P<0.05] or low-contrast liver lesions [198/200 (99.0%) 174/200 (87.0%) 183/200 (91.5%); P<0.05].

Conclusions: VMIs at 40 keV with DLIR enables a 50% decrease in the radiation dose while largely maintaining diagnostic capabilities for multidetection of pulmonary nodules, lymph nodes, and liver lesions in oncology patients.

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