Browsing by Author "Kalisz, Kevin"

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    ItemOpen Access
    Evaluation of the impact of a novel denoising algorithm on image quality in dual-energy abdominal CT of obese patients.
    (European radiology, 2023-04) Schwartz, Fides R; Clark, Darin P; Rigiroli, Francesca; Kalisz, Kevin; Wildman-Tobriner, Benjamin; Thomas, Sarah; Wilson, Joshua; Badea, Cristian T; Marin, Daniele

    Objectives

    Evaluate a novel algorithm for noise reduction in obese patients using dual-source dual-energy (DE) CT imaging.

    Methods

    Seventy-nine patients with contrast-enhanced abdominal imaging (54 women; age: 58 ± 14 years; BMI: 39 ± 5 kg/m2, range: 35-62 kg/m2) from seven DECT (SOMATOM Flash or Force) were retrospectively included (01/2019-12/2020). Image domain data were reconstructed with the standard clinical algorithm (ADMIRE/SAFIRE 2), and denoised with a comparison (ME-NLM) and a test algorithm (rank-sparse kernel regression). Contrast-to-noise ratio (CNR) was calculated. Four blinded readers evaluated the same original and denoised images (0 (worst)-100 (best)) in randomized order for perceived image noise, quality, and their comfort making a diagnosis from a table of 80 options. Comparisons between algorithms were performed using paired t-tests and mixed-effects linear modeling.

    Results

    Average CNR was 5.0 ± 1.9 (original), 31.1 ± 10.3 (comparison; p < 0.001), and 8.9 ± 2.9 (test; p < 0.001). Readers were in good to moderate agreement over perceived image noise (ICC: 0.83), image quality (ICC: 0.71), and diagnostic comfort (ICC: 0.6). Diagnostic accuracy was low across algorithms (accuracy: 66, 63, and 67% (original, comparison, test)). The noise received a mean score of 54, 84, and 66 (p < 0.05); image quality 59, 61, and 65; and the diagnostic comfort 63, 68, and 68, respectively. Quality and comfort scores were not statistically significantly different between algorithms.

    Conclusions

    The test algorithm produces quantitatively higher image quality than current standard and existing denoising algorithms in obese patients imaged with DECT and readers show a preference for it.

    Clinical relevance statement

    Accurate diagnosis on CT imaging of obese patients is challenging and denoising algorithms can increase the diagnostic comfort and quantitative image quality. This could lead to better clinical reads.

    Key points

    • Improving image quality in DECT imaging of obese patients is important for accurate and confident clinical reads, which may be aided by novel denoising algorithms using image domain data. • Accurate diagnosis on CT imaging of obese patients is especially challenging and denoising algorithms can increase quantitative and qualitative image quality. • Image domain algorithms can generalize well and can be implemented at other institutions.
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    ItemOpen Access
    Utility of virtual monoenergetic images derived from a dual-layer detector-based spectral CT in the assessment of aortic anatomy and pathology: A retrospective case control study.
    (Clinical imaging, 2018-11) Chalian, Hamid; Kalisz, Kevin; Rassouli, Negin; Dhanantwari, Amar; Rajiah, Prabhakar
    OBJECTIVES:To evaluate the ability of the retrospectively generated virtual monoenergetic images (VMIs) from a dual-layer detector-based spectral computed tomography (SDCT) to augment aortic enhancement for the evaluation of aortic anatomy and pathology. METHODS:98 patients with suboptimal aortic enhancement (≤200 HU) were retrospectively identified from SDCT scans. VMI from 40 to 80 keV were generated. Attenuation, noise, SNR, and CNR were measured at seven levels in the aorta. Image quality was graded on a 5-point scale, 5 being the best. From the VMI, an ideal set was chosen with mean vascular attenuation above 200 HU while maintaining diagnostic quality. Image parameters and quality of this ideal-set were compared to the standard 120-kVp images. RESULTS:The mean attenuation of all seven measured anatomical regions was 156.6 ± 61.7 HU in the 120-kVp images. Attenuation of the VMI from 40 to 70 keV were higher than the 120-kVp image, measuring 439.2 ± 215.3 HU, 298.5 ± 140.6 HU, 213.4 ± 94.3 HU, and 164.7 ± 90.2 HU, for 40 keV, 50 keV, 60 keV, and 70 keV, respectively (p value <0.01 for 40, 50, 60 keV; 0.07 for 70 keV). SNR and CNR showed similar trends. The 50 keV VMI had the best image quality (4.48 ± 0.84 vs. 2.24 ± 0.92 on 120-kVp images, p < 0.001). Attenuation, CNR, and SNR increased by 90.6%, 85.0%, and 108.1% at 50 keV compared to 120-kVp. CONCLUSIONS:A contrast-enhanced CT study can be optimized for the assessment of the aorta by using low-energy VMI obtained using SDCT. At the optimal monoenergetic level, attenuation, SNR, CNR and image quality were significantly higher than that of conventional polyenergetic images.