Dataset Information

Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in ¹⁸F-FDG total-body PET/CT examination: a preliminary study.

ABSTRACT:

Purpose

To investigate the feasibility of ultra-low-dose CT (ULDCT) reconstructed with the artificial intelligence iterative reconstruction (AIIR) algorithm in total-body PET/CT imaging.

Methods

The study included both the phantom and clinical parts. An anthropomorphic phantom underwent CT imaging with ULDCT (10mAs) and standard-dose CT (SDCT) (120mAs), respectively. ULDCT was reconstructed with AIIR and hybrid iterative reconstruction (HIR) (expressed as ULDCT-AIIR_phantom and ULDCT-HIR_phantom), respectively, and SDCT was reconstructed with HIR (SDCT-HIR_phantom) as control. In the clinical part, 52 patients with malignant tumors underwent the total-body PET/CT scan. ULDCT with AIIR (ULDCT-AIIR) and HIR (ULDCT-HIR), respectively, was reconstructed for PET attenuation correction, followed by the SDCT reconstructed with HIR (SDCT-HIR) for anatomical location. PET/CT images' quality was qualitatively assessed by two readers. The CT_mean, as well as the CT standard deviation (CT_sd), SUV_max, SUV_mean, and the SUV standard deviation (SUV_sd), was recorded. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated and compared.

Results

The image quality of ULDCT-HIR_phantom was inferior to the SDCT-HIR_phantom, but no significant difference was found between the ULDCT-AIIR_phantom and SDCT-HIR_phantom. The subjective score of ULDCT-AIIR in the neck, chest and lower limb was equivalent to that of SDCT-HIR. Besides the brain and lower limb, the change rates of CT_mean in thyroid, neck muscle, lung, mediastinum, back muscle, liver, lumbar muscle, first lumbar spine and sigmoid colon were -2.15, -1.52, 0.66, 2.97, 0.23, 8.91, 0.06, -4.29 and 8.78%, respectively, while all CT_sd of ULDCT-AIIR was lower than that of SDCT-HIR. Except for the brain, the CNR of ULDCT-AIIR was the same as the SDCT-HIR, but the SNR was higher. The change rates of SUV_max, SUV_mean and SUV_sd were within [Formula: see text] 3% in all ROIs. For the lesions, the SUV_max, SUV_sd and TBR showed no significant difference between PET-AIIR and PET-HIR.

Conclusion

The SDCT-HIR could not be replaced by the ULDCT-AIIR at date, but the AIIR algorithm decreased the image noise and increased the SNR, which can be implemented under special circumstances in PET/CT examination.

SUBMITTER: Hu Y

PROVIDER: S-EPMC9807709 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in <sup>18</sup>F-FDG total-body PET/CT examination: a preliminary study.

Hu Yan Y Zheng Zhe Z Yu Haojun H Wang Jingyi J Yang Xinlan X Shi Hongcheng H

EJNMMI physics 20230102 1

<h4>Purpose</h4>To investigate the feasibility of ultra-low-dose CT (ULDCT) reconstructed with the artificial intelligence iterative reconstruction (AIIR) algorithm in total-body PET/CT imaging.<h4>Methods</h4>The study included both the phantom and clinical parts. An anthropomorphic phantom underwent CT imaging with ULDCT (10mAs) and standard-dose CT (SDCT) (120mAs), respectively. ULDCT was reconstructed with AIIR and hybrid iterative reconstruction (HIR) (expressed as ULDCT-AIIR<sub>phantom</s ...[more]

PMID: 36592256

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Project description:BackgroundMagnetic resonance imaging (MRI) plays an important role in the diagnosis of leptomeningeal metastases (LM); however, some sub-centimeter lesions may be missed. Positron emission tomography/computed tomography (PET/CT) has a high sensitivity and may play a synergistic role with MRI in diagnosing spinal LM (SLM). We aimed to retrospectively evaluate the detection of SLM with 18F-fluorodeoxyglucose PET/CT (18F-FDG PET/CT) compared to that of whole spinal cord MRI in a single center.MethodsPatients with SLM who had undergone 18F-FDG PET/CT and MRI were enrolled. 18F-FDG PET/CT imaging findings were independently reviewed by 2 nuclear medicine physicians. 18F-FDG PET/CT findings of SLMs were described. A consistency test was conducted to assess the patient-based diagnostic results obtained by the 2 physicians. Patient-based sensitivity, accuracy, and specificity in diagnosing SLM between 18F-FDG PET/CT and MRI of the whole spinal cord were compared using the chi-square or Fisher's exact test. A P value of <0.05 was considered statistically significant. The receiver operating characteristic (ROC) curve was obtained to assess the diagnostic performance of maximum standardized uptake value (SUVmax) to diagnose SLM.ResultsA total of 16 patients with SLM were included in this study from October 2010 to April 2022. The primary tumor involved the lungs, liver, ovaries, prostate, esophagus, and unknown primary site. The mean age of patients, including 13 males and 3 females, was 57.8±11.2 (range, 34-73) years. Of 16 patients with SLM, 10 had nodular diseases, 2 had linear diseases, and 4 had mixed diseases. The kappa value of the consistency test of the 2 radiologists' diagnostic results was 0.765. The patient-based sensitivity, specificity, and accuracy of 18F-FDG PET/CT in diagnosing SLM were 87.5%, 89.2%, and 88.7%, respectively and those of whole spinal cord MRI were 75.0%, 100.0%, and 92.5%, respectively. There were no significant differences in sensitivity, specificity, and accuracy between the 2 methods, with P values of 0.654, 0.115, and 0.506, respectively. However, more nodular diseases were observed on PET/CT. The area under the ROC curve (AUC) for the prediction of SLM by SUVmax was 0.907 [95% confidence interval (CI): 0.831-0.983]. When SUVmax ≥2.45, the Youden index was the largest, and the sensitivity and specificity were 89.3% and 75.7%, respectively.Conclusions18F-FDG PET/CT is a good choice of imaging modality for assessing SLM. In the diagnosis of SLMs, PET/CT and enhanced MRI can play a better synergistic role.

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Dataset Information

Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in ¹⁸F-FDG total-body PET/CT examination: a preliminary study.

Purpose

Methods

Results

Conclusion

Publications

Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in <sup>18</sup>F-FDG total-body PET/CT examination: a preliminary study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in 18F-FDG total-body PET/CT examination: a preliminary study.

Purpose

Methods

Results

Conclusion

Publications

Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in <sup>18</sup>F-FDG total-body PET/CT examination: a preliminary study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in ¹⁸F-FDG total-body PET/CT examination: a preliminary study.