Improvements to image quality using hybrid and model-based iterative reconstructions: a phantom study

Background The number of computed tomography (CT) examinations is increasing and leading to an increase in total patient exposure. It is therefore important to optimize CT scan imaging conditions in order to reduce the radiation dose. The introduction of iterative reconstruction methods has enabled an improvement in image quality and a reduction in radiation dose. Purpose To investigate how image quality depends on reconstruction method and to discuss patient dose reduction resulting from the use of hybrid and model-based iterative reconstruction. Material and Methods An image quality phantom (Catphan® 600) and an anthropomorphic torso phantom were examined on a Philips Brilliance iCT. The image quality was evaluated in terms of CT numbers, noise, noise power spectra (NPS), contrast-to-noise ratio (CNR), low-contrast resolution, and spatial resolution for different scan parameters and dose levels. The images were reconstructed using filtered back projection (FBP) and different settings of hybrid (iDose4) and model-based (IMR) iterative reconstruction methods. Results iDose4 decreased the noise by 15–45% compared with FBP depending on the level of iDose4. The IMR reduced the noise even further, by 60–75% compared to FBP. The results are independent of dose. The NPS showed changes in the noise distribution for different reconstruction methods. The low-contrast resolution and CNR were improved with iDose4, and the improvement was even greater with IMR. Conclusion There is great potential to reduce noise and thereby improve image quality by using hybrid or, in particular, model-based iterative reconstruction methods, or to lower radiation dose and maintain image quality.

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Evaluation of an iterative model-based reconstruction of pediatric abdominal CT with regard to image quality and radiation dose

Acta Radiologica ◽

10.1177/0284185117728415 ◽

2017 ◽

Vol 59 (6) ◽

pp. 740-747

Author(s):

Marie-Louise Aurumskjöld ◽

Marcus Söderberg ◽

Fredrik Stålhammar ◽

Kristina Vult von Steyern ◽

Anders Tingberg ◽

...

Keyword(s):

Image Quality ◽

Radiation Dose ◽

Iterative Reconstruction ◽

Low Dose ◽

Pediatric Patients ◽

Standard Dose ◽

Reconstruction Method ◽

Abdominal Ct ◽

Model Based ◽

Iterative Model

Background In pediatric patients, computed tomography (CT) is important in the medical chain of diagnosing and monitoring various diseases. Because children are more radiosensitive than adults, they require minimal radiation exposure. One way to achieve this goal is to implement new technical solutions, like iterative reconstruction. Purpose To evaluate the potential of a new, iterative, model-based method for reconstructing (IMR) pediatric abdominal CT at a low radiation dose and determine whether it maintains or improves image quality, compared to the current reconstruction method. Material and Methods Forty pediatric patients underwent abdominal CT. Twenty patients were examined with the standard dose settings and 20 patients were examined with a 32% lower radiation dose. Images from the standard examination were reconstructed with a hybrid iterative reconstruction method (iDose4), and images from the low-dose examinations were reconstructed with both iDose4 and IMR. Image quality was evaluated subjectively by three observers, according to modified EU image quality criteria, and evaluated objectively based on the noise observed in liver images. Results Visual grading characteristics analyses showed no difference in image quality between the standard dose examination reconstructed with iDose4 and the low dose examination reconstructed with IMR. IMR showed lower image noise in the liver compared to iDose4 images. Inter- and intra-observer variance was low: the intraclass coefficient was 0.66 (95% confidence interval = 0.60–0.71) for the three observers. Conclusion IMR provided image quality equivalent or superior to the standard iDose4 method for evaluating pediatric abdominal CT, even with a 32% dose reduction.

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Can optimized model-based iterative reconstruction improve the contrast of liver lesions in CT?

Acta Radiologica ◽

10.1177/02841851211070119 ◽

2022 ◽

pp. 028418512110701

Author(s):

Jonas Oppenheimer ◽

Keno Kyrill Bressem ◽

Fabian Henry Jürgen Elsholtz ◽

Bernd Hamm ◽

Stefan Markus Niehues

Keyword(s):

Image Quality ◽

Iterative Reconstruction ◽

Visual Analysis ◽

Liver Lesion ◽

Lesion Detection ◽

Focal Liver Lesions ◽

Reconstruction Method ◽

Liver Lesions ◽

Low Contrast ◽

Model Based

Background Computed tomography is a standard imaging procedure for the detection of liver lesions, such as metastases, which can often be small and poorly contrasted, and therefore hard to detect. Advances in image reconstruction have shown promise in reducing image noise and improving low-contrast detectability. Purpose To examine a novel, specialized, model-based iterative reconstruction (MBIR) technique for improved low-contrast liver lesion detection. Material and Methods Patient images with reported poorly contrasted focal liver lesions were retrospectively reconstructed with the low-contrast attenuating algorithm (FIRST-LCD) from primary raw data. Liver-to-lesion contrast, signal-to-noise, and contrast-to-noise ratios for background and liver noise for each lesion were compared for all three FIRST-LCD presets with the established hybrid iterative reconstruction method (AIDR-3D). An additional visual conspicuity score was given by two experienced radiologists for each lesion. Results A total of 82 lesions in 57 examinations were included in the analysis. All three FIRST-LCD algorithms provided statistically significant increases in liver-to-lesion contrast, with FIRSTMILD showing the largest increase (40.47 HU in AIDR-3D; 45.84 HU in FIRSTMILD; P < 0.001). Substantial improvement was shown in contrast-to-noise metrics. Visual analysis of the lesions shows decreased lesion visibility with all FIRST methods in comparison to AIDR-3D, with FIRSTSTR showing the closest results ( P < 0.001). Conclusion Objective image metrics show promise for MBIR methods in improving the detectability of low-contrast liver lesions; however, subjective image quality may be perceived as inferior. Further improvements are necessary to enhance image quality and lesion detection.

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