Clinical application of four-dimensional noise reduction filtering with a similarity algorithm in dynamic myocardial computed tomography perfusion imaging

The Feasibility of a Model-Based Iterative Reconstruction Technique Tuned for the Myocardium on Myocardial Computed Tomography Late Enhancement

OBJECTIVES

This study evaluated the feasibility of a model-based iterative reconstruction technique (MBIR) tuned for the myocardium on myocardial computed tomography late enhancement (CT-LE).

METHODS

Twenty-eight patients who underwent myocardial CT-LE and late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) within 1 year were retrospectively enrolled. Myocardial CT-LE was performed using a 320-row CT with low tube voltage (80 kVp). Myocardial CT-LE images were scanned 7 min after CT angiography (CTA) without additional contrast medium. All myocardial CT-LE images were reconstructed with hybrid iterative reconstruction (HIR), conventional MBIR (MBIR_cardiac), and new MBIR tuned for the myocardium (MBIR_myo). Qualitative (5-grade scale) scores and quantitative parameters (signal-to-noise ratio [SNR] and contrast-to-noise ratio [CNR]) were assessed as image quality. The sensitivity, specificity, and accuracy of myocardial CT-LE were evaluated at the segment level using an American Heart Association (AHA) 16-segment model, with LGE-MRI as a reference standard. These results were compared among the different CT image reconstructions.

RESULTS

In 28 patients with 448 segments, 160 segments were diagnosed with positive by LGE-MRI. In the qualitative assessment of myocardial CT-LE, the mean image quality scores were 2.9 ± 1.2 for HIR, 3.0 ± 1.1 for MBIR_cardiac, and 4.0 ± 1.0 for MBIR_myo. MBIR_myo showed a significantly higher score than HIR (P < 0.001) and MBIR_cardiac (P = 0.018). In the quantitative image quality assessment of myocardial CT-LE, the median image SNR was 10.3 (9.1-11.1) for HIR, 10.8 (9.8-12.1) for MBIR_cardiac, and 16.8 (15.7-18.4) for MBIR_myo. The median image CNR was 3.7 (3.0-4.6) for HIR, 3.8 (3.2-5.1) for MBIR_cardiac, and 6.4 (5.0-7.7) for MBIR_myo. MBIR_myo significantly improved the SNR and CNR of CT-LE compared to HIR and MBIR_cardiac (P < 0.001). The sensitivity, specificity, and accuracy for the detection of myocardial CT-LE were 70%, 92%, and 84% for HIR; 71%, 92%, and 85% for MBIR_cardiac; and 84%, 92%, and 89% for MBIR_myo, respectively. MBIR_myo showed significantly higher image quality, sensitivity, and accuracy than the others (P < 0.05).

CONCLUSIONS

MBIR tuned for myocardium improved image quality and diagnostic performance for myocardial CT-LE assessment.

CT image denoising methods for image quality improvement and radiation dose reduction

With the ever-increasing use of computed tomography (CT), concerns about its radiation dose have become a significant public issue. To address the need for radiation dose reduction, CT denoising methods have been widely investigated and applied in low-dose CT images. Numerous noise reduction algorithms have emerged, such as iterative reconstruction and most recently, deep learning (DL)-based approaches. Given the rapid advancements in Artificial Intelligence techniques, we recognize the need for a comprehensive review that emphasizes the most recently developed methods. Hence, we have performed a thorough analysis of existing literature to provide such a review. Beyond directly comparing the performance, we focus on pivotal aspects, including model training, validation, testing, generalizability, vulnerability, and evaluation methods. This review is expected to raise awareness of the various facets involved in CT image denoising and the specific challenges in developing DL-based models.

Feasibility of four-dimensional similarity filter for radiation dose reduction in dynamic myocardial computed tomography perfusion imaging

Rationale and objectives

We aimed to evaluate the impact of four-dimensional noise reduction filtering using a four-dimensional similarity filter (4D-SF) on radiation dose reduction in dynamic myocardial computed tomography perfusion (CTP).

Materials and methods

Forty-three patients who underwent dynamic myocardial CTP using 320-row computed tomography (CT) were included in the study. The original images were reconstructed using iterative reconstruction (IR). Three different CTP datasets with simulated noise, corresponding to 25%, 50%, and 75% reduction of the original dose (300 mA), were reconstructed using a combination of IR and 4D-SF. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed, and CT-derived myocardial blood flow (CT-MBF) was quantified. The results were compared between the original and simulated images with radiation dose reduction.

Results

The median SNR (first quartile-third quartile) at the original, 25%-, 50%-, and 75%-dose reduced-simulated images with 4D-SF was 8.3 (6.5-10.2), 16.5 (11.9-21.7), 15.6 (11.0-20.1), and 12.8 (8.8-18.1) and that of CNR was 4.4 (3.2-5.8), 6.7 (4.6-10.3), 6.6 (4.3-10.1), and 5.5 (3.5-9.1), respectively. All the dose-reduced-simulated CTPs with 4D-SF had significantly higher image quality scores in SNR and CNR than the original ones (25%-, 50%-, and 75%-dose reduced vs. original images, p < 0.05, in each). The CT-MBF in 75%-dose reduced-simulated CTP was significantly lower than 25%-, 50%- dose-reduced-simulated, and original CTPs (vs. 75%-dose reduced-simulated images, p < 0.05, in each).

Conclusion

4D-SF has the potential to reduce the radiation dose associated with dynamic myocardial CTP imaging by half, without impairing the robustness of MBF quantification.

Dynamic CT Myocardial Perfusion: The Role of Functional Evaluation in the Diagnosis of Coronary Artery Disease

Coronary computed tomography angiography (CTA) is a widely accepted, non-invasive diagnostic modality for the evaluation of patients with suspected coronary artery disease (CAD). However, a limitation of CTA is its inability to provide information on the hemodynamic significance of the coronary lesion. The recently developed stress dynamic CT perfusion technique has emerged as a potential solution to this diagnostic challenge. Dynamic CT myocardial perfusion provides information on the hemodynamic consequences of coronary stenosis and is used to detect myocardial ischemia. The combination of stress dynamic CT myocardial perfusion with CTA provides a comprehensive assessment that integrates anatomical and functional information. CT myocardial perfusion has been validated in several clinical studies and has shown comparable accuracy to Positron Emission Tomography (PET) and stress magnetic resonance imaging (MRI) in the diagnosis of hemodynamically significant coronary stenosis and superior performance to Single Photon Emission Computed Tomography (SPECT). More importantly, CTP-derived myocardial perfusion has been shown to have a strong correlation with FFR, and the use of CTP results in a reduction of negative catheterizations. In the context of suspected stable coronary artery disease, the CT protocol with dynamic perfusion imaging combined with CTA eliminates the need for additional testing, making it a convenient "one-stop-shop" method and an effective gatekeeper to an invasive approach.

Assessment of Computed Tomography Perfusion Research Landscape: A Topic Modeling Study

The number of scholarly articles continues to rise. The continuous increase in scientific output poses a challenge for researchers, who must devote considerable time to collecting and analyzing these results. The topic modeling approach emerges as a novel response to this need. Considering the swift advancements in computed tomography perfusion (CTP), we deem it essential to launch an initiative focused on topic modeling. We conducted a comprehensive search of the Scopus database from 1 January 2000 to 16 August 2023, to identify relevant articles about CTP. Using the BERTopic model, we derived a group of topics along with their respective representative articles. For the 2020s, linear regression models were used to identify and interpret trending topics. From the most to the least prevalent, the topics that were identified include "Tumor Vascularity", "Stroke Assessment", "Myocardial Perfusion", "Intracerebral Hemorrhage", "Imaging Optimization", "Reperfusion Therapy", "Postprocessing", "Carotid Artery Disease", "Seizures", "Hemorrhagic Transformation", "Artificial Intelligence", and "Moyamoya Disease". The model provided insights into the trends of the current decade, highlighting "Postprocessing" and "Artificial Intelligence" as the most trending topics.

Dynamic myocardial CT perfusion imaging-state of the art

In patients with suspected coronary artery disease (CAD), dynamic myocardial computed tomography perfusion (CTP) imaging combined with coronary CT angiography (CTA) has become a comprehensive diagnostic examination technique resulting in both anatomical and quantitative functional information on myocardial blood flow, and the presence and grading of stenosis. Recently, CTP imaging has been proven to have good diagnostic accuracy for detecting myocardial ischemia, comparable to stress magnetic resonance imaging and positron emission tomography perfusion, while being superior to single photon emission computed tomography. Dynamic CTP accompanied by coronary CTA can serve as a gatekeeper for invasive workup, as it reduces unnecessary diagnostic invasive coronary angiography. Dynamic CTP also has good prognostic value for the prediction of major adverse cardiovascular events. In this article, we will provide an overview of dynamic CTP, including the basics of coronary blood flow physiology, applications and technical aspects including protocols, image acquisition and reconstruction, future perspectives, and scientific challenges. KEY POINTS: • Stress dynamic myocardial CT perfusion combined with coronary CTA is a comprehensive diagnostic examination technique resulting in both anatomical and quantitative functional information. • Dynamic CTP imaging has good diagnostic accuracy for detecting myocardial ischemia comparable to stress MRI and PET perfusion. • Dynamic CTP accompanied by coronary CTA may serve as a gatekeeper for invasive workup and can guide treatment in obstructive coronary artery disease.

Multireader image quality evaluation of dynamic myocardial computed tomography perfusion imaging with a novel four-dimensional noise reduction filter

BACKGROUND

Dynamic myocardial computed tomography perfusion (CTP) is a novel technique able to depict cardiac ischemia.

PURPOSE

To evaluate the impact of a four-dimensional noise reduction filter (similarity filter [4D-SF]) on image quality in dynamic CTP imaging, allowing for substantial radiation dose reduction.

MATERIAL AND METHODS

Dynamic CTP datasets of 30 patients (16 women) with suspected coronary artery disease, acquired with a 320-slice CT system, were retrieved, reconstructed with the deep learning-based algorithm of the system (DLR), and filtered with the 4D-SF. For each case, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in six regions of interest (33-38mm²) were calculated before and after filtering, in four-chamber and short-axis views, and t-tested. Furthermore, six radiologists of different expertise evaluated subjective image preference by answering five visual grading analysis-type questions (regarding acceptable level of noise, absence of artifacts, natural appearance, cardiac contour sharpness, diagnostic acceptability) using a 5-point scale. The results were analyzed using visual grade characteristics (VGC) and intraclass correlation coefficient (ICC).

RESULTS

Mean SNR in four-chamber view (unfiltered vs. filtered) were: septum=4.1 ± 2.1 versus 7.6 ± 5.6; lateral wall=4.5 ± 2.0 versus 8.0 ± 4.9; CNRseptum=16.6 ± 8.9 versus 31.7 ± 28; lateral wall=16.2 ± 8.9 versus 31.3 ± 28.9. Similar results were obtained in short-axis view. The perceived filtered image quality indicated decreased noise (VGC_AUC=0.96) and artifacts (0.65), improved natural appearance (0.59), cardiac contour sharpness (0.74), and diagnostic acceptability (0.78). The inter-observer variability was excellent (ICC=0.79). All results were statistically significant (P < 0.05).

CONCLUSION

Similarity filtering after DLR improves image quality, possibly enabling dose reduction in dynamic CTP imaging in patient with suspected chronic coronary syndrome.

A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging

PURPOSE

Bayesian estimation with advanced noise reduction (BEANR) in CT perfusion (CTP) could deliver more reliable cerebral blood flow (CBF) measurements than the commonly used reformulated singular value decomposition (rSVD). We compared the efficacy of CBF measurement by CTP using BEANR and rSVD, evaluating both relative to N-isopropyl-p-[(123) I]- iodoamphetamine (¹²³I-IMP) single-photon emission computed tomography (SPECT) as a reference standard, in patients with cerebrovascular disease.

METHODS

Thirty-one patients with suspected cerebrovascular disease underwent both CTP on a 320 detector-row CT system and SPECT. We applied rSVD and BEANR in the ischemic and contralateral regions to create CBF maps and calculate CBF ratios from the ischemic side to the healthy contralateral side (CBF index). The analysis involved comparing the CBF index between CTP methods and SPECT using Pearson's correlation and limits of agreement determined with Bland-Altman analyses, before comparing the mean difference in the CBF index between each CTP method and SPECT using the Wilcoxon matched pairs signed-rank test.

RESULTS

The CBF indices of BEANR and ¹²³I-IMP SPECT were significantly and positively correlated (r = 0.55, p < 0.0001), but there was no significant correlation between the rSVD method and SPECT (r = 0.15, p > 0.05). BEANR produced smaller limits of agreement for CBF than rSVD. The mean difference in the CBF index between BEANR and SPECT differed significantly from that between rSVD and SPECT (p < 0.001).

CONCLUSIONS

BEANR has a better potential utility for CBF measurement in CTP than rSVD compared to SPECT in patients with cerebrovascular disease.

Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death with a 5-year survival rate of 10%. Quantitative CT perfusion (CTP) can provide additional diagnostic information compared to the limited accuracy of the current standard, contrast-enhanced CT (CECT). This systematic review evaluates CTP for diagnosis, grading, and treatment assessment of PDAC. The secondary goal is to provide an overview of scan protocols and perfusion models used for CTP in PDAC. The search strategy combined synonyms for 'CTP' and 'PDAC.' Pubmed, Embase, and Web of Science were systematically searched from January 2000 to December 2020 for studies using CTP to evaluate PDAC. The risk of bias was assessed using QUADAS-2. 607 abstracts were screened, of which 29 were selected for full-text eligibility. 21 studies were included in the final analysis with a total of 760 patients. All studies comparing PDAC with non-tumorous parenchyma found significant CTP-based differences in blood flow (BF) and blood volume (BV). Two studies found significant differences between pathological grades. Two other studies showed that BF could predict neoadjuvant treatment response. A wide variety in kinetic models and acquisition protocol was found among included studies. Quantitative CTP shows a potential benefit in PDAC diagnosis and can serve as a tool for pathological grading and treatment assessment; however, clinical evidence is still limited. To improve clinical use, standardized acquisition and reconstruction parameters are necessary for interchangeability of the perfusion parameters.