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

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.

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

2016 ◽  
Vol 58 (1) ◽  
pp. 53-61 ◽  
Author(s):  
Marie-Louise Aurumskjöld ◽  
Kristina Ydström ◽  
Anders Tingberg ◽  
Marcus Söderberg
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Iterative Reconstruction ◽  
Power Spectra ◽  
Reconstruction Method ◽  
Noise Power ◽  
Contrast Resolution ◽  
Low Contrast ◽  
Model Based ◽  
Reconstruction Methods

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.

scholarly journals Comparison of low-contrast detectability between uniform and anatomically realistic phantoms—influences on CT image quality assessment

2021 ◽  
Author(s):  
Juliane Conzelmann ◽  
Ulrich Genske ◽  
Arthur Emig ◽  
Michael Scheel ◽  
Bernd Hamm ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Dose Reduction ◽  
Iterative Reconstruction ◽  
Image Quality Assessment ◽  
Lesion Detection ◽  
Detection Accuracy ◽  
Test Environment ◽  
Low Contrast ◽  
Dose Effects

Abstract Objectives To evaluate the effects of anatomical phantom structure on task-based image quality assessment compared with a uniform phantom background. Methods Two neck phantom types of identical shape were investigated: a uniform type containing 10-mm lesions with 4, 9, 18, 30, and 38 HU contrast to the surrounding area and an anatomically realistic type containing lesions of the same size and location with 10, 18, 30, and 38 HU contrast. Phantom images were acquired at two dose levels (CTDIvol of 1.4 and 5.6 mGy) and reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Detection accuracy was evaluated by seven radiologists in a 4-alternative forced choice experiment. Results Anatomical phantom structure impaired lesion detection at all lesion contrasts (p < 0.01). Detectability in the anatomical phantom at 30 HU contrast was similar to 9 HU contrast in uniform images (91.1% vs. 89.5%). Detection accuracy decreased from 83.6% at 5.6 mGy to 55.4% at 1.4 mGy in uniform FBP images (p < 0.001), whereas AIDR 3D preserved detectability at 1.4 mGy (80.7% vs. 85% at 5.6 mGy, p = 0.375) and was superior to FBP (p < 0.001). In the assessment of anatomical images, superiority of AIDR 3D was not confirmed and dose reduction moderately affected detectability (74.6% vs. 68.2%, p = 0.027 for FBP and 81.1% vs. 73%, p = 0.018 for AIDR 3D). Conclusions A lesion contrast increase from 9 to 30 HU is necessary for similar detectability in anatomical and uniform neck phantom images. Anatomical phantom structure influences task-based assessment of iterative reconstruction and dose effects. Key Points • A lesion contrast increase from 9 to 30 HU is necessary for similar low-contrast detectability in anatomical and uniform neck phantom images. • Phantom background structure influences task-based assessment of iterative reconstruction and dose effects. • Transferability of CT assessment to clinical imaging can be expected to improve as the realism of the test environment increases.

Preoperative assessment of focal liver lesions: multidetector computed tomography challenges magnetic resonance imaging

2005 ◽  
Vol 46 (1) ◽  
pp. 9-15 ◽  
Author(s):  
K. Numminen ◽  
H. Isoniemi ◽  
J. Halavaara ◽  
P. Tervahartiala ◽  
H. Mäkisalo ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Magnetic Resonance ◽  
Multidetector Computed Tomography ◽  
Intraoperative Ultrasound ◽  
Preoperative Assessment ◽  
Liver Lesion ◽  
Lesion Detection ◽  
Extrahepatic Disease ◽  
Focal Liver Lesions ◽  
Liver Lesions

Purpose: To investigate prospectively multidetector computed tomography (CT) (MDCT) and magnetic resonance (MR) imaging (MRI) in the preoperative assessment of focal liver lesions. Material and Methods: Multiphasic MDCT and conventional gadolinium‐enhanced MRI were performed on 31 consecutive patients prior to hepatic surgery. All images were blindly analyzed as consensus reading. Lesion counts and their relation to vascular structures and possible extrahepatic disease were determined. The data from the MDCT and MRI were compared with the results obtained by intraoperative ultrasound (IOUS) and palpation. Histopathologic verification was available. Results: At surgery, IOUS and palpation revealed 45 solid liver lesions. From these, preoperative MDCT detected 43 (96%) and MRI 35 (78%) deposits. MDCT performed statistically better than MRI in lesion detection ( P = 0.008). Assessment of lesion vascular proximity was correctly determined by MDCT in 98% of patients and by MRI in 87%. Statistical difference was found ( P = 0.002). IOUS and palpation changed the preoperative surgical plan as a result of extrahepatic disease in 8/31 (26%) cases. In MDCT as well in MRI extrahepatic involvement was suspected in two cases. Conclusion: MDCT was superior to MRI and nearly equal to IOUS in liver lesion detection and in the determination of lesion vascular proximity. However, both techniques fail to reliably detect extrahepatic disease.

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

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.

scholarly journals Impact of dose reduction and iterative model reconstruction on multi-detector CT imaging of the brain in patients with suspected ischemic stroke

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Karolin J. Paprottka ◽  
Karina Kupfer ◽  
Isabelle Riederer ◽  
Claus Zimmer ◽  
Meinrad Beer ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Image Quality ◽  
Iterative Reconstruction ◽  
Standard Dose ◽  
Reconstruction Method ◽  
Reconstruction Algorithms ◽  
Model Based ◽  
Significant Difference ◽  
Noise Ratio

AbstractNon-contrast cerebral computed tomography (CT) is frequently performed as a first-line diagnostic approach in patients with suspected ischemic stroke. The purpose of this study was to evaluate the performance of hybrid and model-based iterative image reconstruction for standard-dose (SD) and low-dose (LD) non-contrast cerebral imaging by multi-detector CT (MDCT). We retrospectively analyzed 131 patients with suspected ischemic stroke (mean age: 74.2 ± 14.3 years, 67 females) who underwent initial MDCT with a SD protocol (300 mAs) as well as follow-up MDCT after a maximum of 10 days with a LD protocol (200 mAs). Ischemic demarcation was detected in 26 patients for initial and in 64 patients for follow-up imaging, with diffusion-weighted magnetic resonance imaging (MRI) confirming ischemia in all of those patients. The non-contrast cerebral MDCT images were reconstructed using hybrid (Philips “iDose4”) and model-based iterative (Philips “IMR3”) reconstruction algorithms. Two readers assessed overall image quality, anatomic detail, differentiation of gray matter (GM)/white matter (WM), and conspicuity of ischemic demarcation, if any. Quantitative assessment included signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) calculations for WM, GM, and demarcated areas. Ischemic demarcation was detected in all MDCT images of affected patients by both readers, irrespective of the reconstruction method used. For LD imaging, anatomic detail and GM/WM differentiation was significantly better when using the model-based iterative compared to the hybrid reconstruction method. Furthermore, CNR of GM/WM as well as the SNR of WM and GM of healthy brain tissue were significantly higher for LD images with model-based iterative reconstruction when compared to SD or LD images reconstructed with the hybrid algorithm. For patients with ischemic demarcation, there was a significant difference between images using hybrid versus model-based iterative reconstruction for CNR of ischemic/contralateral unaffected areas (mean ± standard deviation: SD_IMR: 4.4 ± 3.1, SD_iDose: 3.5 ± 2.3, P < 0.0001; LD_IMR: 4.6 ± 2.9, LD_iDose: 3.2 ± 2.1, P < 0.0001).  In conclusion, model-based iterative reconstruction provides higher CNR and SNR without significant loss of image quality for non-enhanced cerebral MDCT.

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