Model-Based Iterative Reconstruction Technique for Ultralow-Dose Computed Tomography of the Lung

Yamada, Yoshitake; Jinzaki, Masahiro; Tanami, Yutaka; Shiomi, Eisuke; Sugiura, Hiroaki; Abe, Takayuki; Kuribayashi, Sachio

doi:10.1097/rli.0b013e3182562a89

Cited by 132 publications

(82 citation statements)

References 37 publications

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“…The strength of this study compared to other studies evaluating the use of ASIR and MBIR in conjunction with reduced dose is that it represents a more thorough qualitative and quantitative analysis (including the use of two phantoms) for the specific application of lung cancer screening with a focus on GGO definition 13 , 14 , 15 . Despite the study strengths, there were several limitations.…”

Section: Discussionmentioning

confidence: 99%

Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study

Mathieu

Fox

et al. 2014

J Applied Clin Med Phys

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The purpose of this study was to reduce the radiation dosage associated with computed tomography (CT) lung cancer screening while maintaining overall diagnostic image quality and definition of ground‐glass opacities (GGOs). A lung screening phantom and a multipurpose chest phantom were used to quantitatively assess the performance of two iterative image reconstruction algorithms (adaptive statistical iterative reconstruction (ASIR) and model‐based iterative reconstruction (MBIR)) used in conjunction with reduced tube currents relative to a standard clinical lung cancer screening protocol (51 effective mAs (3.9 mGy) and filtered back‐projection (FBP) reconstruction). To further assess the algorithms' performances, qualitative image analysis was conducted (in the form of a reader study) using the multipurpose chest phantom, which was implanted with GGOs of two densities. Our quantitative image analysis indicated that tube current, and thus radiation dose, could be reduced by 40% or 80% from ASIR or MBIR, respectively, compared with conventional FBP, while maintaining similar image noise magnitude and contrast‐to‐noise ratio. The qualitative portion of our study, which assessed reader preference, yielded similar results, indicating that dose could be reduced by 60% (to 20 effective mAs (1.6 mGy)) with either ASIR or MBIR, while maintaining GGO definition. Additionally, the readers' preferences (as indicated by their ratings) regarding overall image quality were equal or better (for a given dose) when using ASIR or MBIR, compared with FBP. In conclusion, combining ASIR or MBIR with reduced tube current may allow for lower doses while maintaining overall diagnostic image quality, as well as GGO definition, during CT lung cancer screening.PACS numbers: 87.57.Q‐, 87.57.nf

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Section: Discussionmentioning

confidence: 99%

Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study

Mathieu

Fox

et al. 2014

J Applied Clin Med Phys

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“…Ultra-low-dose CT protocols combined with iterative reconstruction techniques, which can further reduce the patient radiation dose by 80% (35,36), have produced promising results for the detection of pulmonary nodules (37,38). Hence, this could potentially allow a complete PET/CT lung screening scan to be obtained at a total dose under 1 mSv, which is roughly equivalent to 30% of 1 y of average natural background.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Accuracy and Lesion Detectability of Low-Dose ¹⁸F-FDG PET for Lung Cancer Screening

et al. 2016

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Lung cancer remains responsible for more deaths worldwide than any other cancer, but recently there has been a significant shift in the clinical paradigm regarding the initial management of subjects at high risk for this disease. Low-dose CT has demonstrated significant improvements over planar x-ray screening for patient prognoses and is now performed in the United States. Specificity of this modality, however, is poor, and the additional information from PET has the potential to improve its accuracy. Routine screening requires consideration of the effective dose delivered to the patient, and this work investigates image quality of PET for low-dose conditions, in the context of lung lesion detectability. Reduced radiotracer doses were simulated by randomly discarding counts from clinical lung cancer scans acquired in list-mode. Bias and reproducibility of lesion activity values were relatively stable even at low total counts of around 5 million trues. Additionally, numeric observer models were developed and trained with the results of 2 physicians and 3 postdoctoral researchers with PET experience in a detection task; detection sensitivity of the observers was well correlated with lesion signal-to-noise ratio. The models were used prospectively to survey detectability of lung cancer lesions, and the findings suggested a lower limit around 10 million true counts for maximizing performance. Under the acquisition parameters used in this study, this translates to an effective patient dose of less than 0.4 mSv, potentially allowing a complete low-dose PET/CT lung screening scan to be obtained under 1 mSv.

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“…Noise and artifact reductions are necessary steps toward dose reduction in CT. The recent burst of research activities in iterative reconstruction can also be credited to the increased awareness of the radiation dose generated by a CT scan [52][53][54][55][56][57][58][59], and advancements in reconstruction hardware capability.…”

Section: Iterative Reconstructionmentioning

confidence: 99%

Recent Advances in CT Image Reconstruction

et al. 2013

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Over the past two decades, rapid system and hardware development of x-ray computed tomography (CT) technologies has been accompanied by equally exciting advances in image reconstruction algorithms. The algorithmic development can generally be classified into three major areas: analytical reconstruction, model-based iterative reconstruction, and application-specific reconstruction. Given the limited scope of this chapter, it is nearly impossible to cover every important development in this field; it is equally difficult to provide sufficient breadth and depth on each selected topic. As a compromise, we have decided, for a selected few topics, to provide sufficient high-level technical descriptions and to discuss their advantages and applications.

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Model-Based Iterative Reconstruction Technique for Ultralow-Dose Computed Tomography of the Lung

Cited by 132 publications

References 37 publications

Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study

Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study

Quantitative Accuracy and Lesion Detectability of Low-Dose ¹⁸F-FDG PET for Lung Cancer Screening

Recent Advances in CT Image Reconstruction

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Model-Based Iterative Reconstruction Technique for Ultralow-Dose Computed Tomography of the Lung

Cited by 132 publications

References 37 publications

Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study

Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study

Quantitative Accuracy and Lesion Detectability of Low-Dose 18F-FDG PET for Lung Cancer Screening

Recent Advances in CT Image Reconstruction

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Quantitative Accuracy and Lesion Detectability of Low-Dose ¹⁸F-FDG PET for Lung Cancer Screening