Applicability Evaluation of Full-Reference Image Quality Assessment Methods for Computed Tomography Images.

Image quality assessments (IQA) are an important task for providing appropriate medical care. Full-reference IQA (FR-IQA) methods, such as peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), are often used to evaluate imaging conditions, reconstruction conditions, and image processing algorithms, including noise reduction and super-resolution technology. However, these IQA methods may be inapplicable for medical images because they were designed for natural images. Therefore, this study aimed to investigate the correlation between objective assessment by some FR-IQA methods and human subjective assessment for computed tomography (CT) images. For evaluation, 210 distorted images were created from six original images using two types of degradation: noise and blur. We employed nine widely used FR-IQA methods for natural images: PSNR, SSIM, feature similarity (FSIM), information fidelity criterion (IFC), visual information fidelity (VIF), noise quality measure (NQM), visual signal-to-noise ratio (VSNR), multi-scale SSIM (MSSSIM), and information content-weighted SSIM (IWSSIM). Six observers performed subjective assessments using the double stimulus continuous quality scale (DSCQS) method. The performance of IQA methods was quantified using Pearson's linear correlation coefficient (PLCC), Spearman rank order correlation coefficient (SROCC), and root-mean-square error (RMSE). Nine FR-IQA methods developed for natural images were all strongly correlated with the subjective assessment (PLCC and SROCC > 0.8), indicating that these methods can apply to CT images. Particularly, VIF had the best values for all three items, PLCC, SROCC, and RMSE. These results suggest that VIF provides the most accurate alternative measure to subjective assessments for CT images.

Preoperative assessment of localized pleural adhesion: Utility of software-assisted analysis on dynamic-ventilation computed tomography.

PURPOSE: To assess the usefulness of software analysis using dynamic-ventilation CT for localized pleural adhesion (LPA). MATERIALS AND METHODS: Fifty-one patients scheduled to undergo surgery underwent both dynamic-ventilation CT and static chest CT as preoperative assessments. Five observers independently evaluated the presence and severity of LPA on a three-point scale (non, mild, and severe LPA) for 9 pleural regions (upper, middle, and lower pleural aspects on ventral, lateral, and dorsal areas) on the chest CT by three different methods by observing images from: static high-resolution CT (static image); dynamic-ventilation CT (movie image), and dynamic-ventilation CT while referring to the adhesion map (movie image with color map), which was created using research software to visualize movement differences between the lung surface and chest wall. The presence and severity of LPA was confirmed by intraoperative thoracoscopic findings. Parameters of diagnostic accuracy for LPA presence and severity were assessed among the three methods using Wilcoxon signed rank test in total and for each of the three pleural aspects. RESULTS: Mild and severe LPA were confirmed in 14 and 8 patients. Movie image with color map had higher sensitivity (56.9 ±â€¯10.7 %) and negative predictive value (NPV) (91.4 ±â€¯1.7 %) in LPA detection than both movie image and static image. Additionally, for severe LPA, detection sensitivity was the highest with movie image with color map (82.5 ±â€¯6.1 %), followed by movie image (58.8 ±â€¯17.0 %) and static image (38.8 ±â€¯13.9 %). For LPA severity, movie image with color map was similar to movie image and superior to static image in accuracy as well as underestimation and overestimation, with a mean value of 80.2 %. CONCLUSION: Software-assisted dynamic-ventilation CT may be a useful novel imaging approach to improve the detection performance of LPA.

Peripheral bronchial luminal conspicuity on dynamic-ventilation computed tomography: association with radiation doses and temporal resolution by using an ex vivo porcine lung phantom.

BACKGROUND: It is still unclear which image reconstruction algorithm is appropriate for peripheral bronchial luminal conspicuity (PBLC) on dynamic-ventilation computed tomography (DVCT). PURPOSE: To assess the influence of radiation doses and temporal resolution (TR) on the association between movement velocity (MV) and PBLC on DVCT. MATERIAL AND METHODS: An ex vivo porcine lung phantom with simulated respiratory movement was scanned by 320-row CT at 240 mA and 10 mA. Peak and dip CT density and luminal area adjusted by values at end-inspiration (CTDpeak and CTDdip, luminal area ratio [LAR]) for PBLC and MVs were measured and visual scores (VS) were obtained at 12 measurement points on 13 frame images obtained at half and full reconstructions (TR 340 and 190 ms) during expiration. Size-specific dose estimate (SSDE) was applied to presume radiation dose. VS, CTDpeak, CTDdip, LAR, and their cross-correlation coefficients with MV (CCC) were compared among four methods with combinations of two reconstruction algorithms and two doses. RESULTS: The dose at 10 mA was presumed as 26 mA by SSDE for standard proportion adults. VS, CTDdip, CTDpeak, and LAR with half reconstruction at 10 mA (2.52 ± 0.59, 1.016 ± 0.221, 0.948 ± 0.103, and 0.990 ± 0.527) were similar to those at 240 mA except for VS, and different from those with full reconstruction at both doses (2.24 ± 0.85, 0.830 ± 0.209, 0.986 ± 0.065, and 1.012 ± 0.438 at 240 mA) (P < 0.05). CCC for CTDdip with half reconstruction (-0.024 ± 0.552) at 10 mA was higher compared with full reconstruction (-0.503 ± 0.291) (P < 0.05). CONCLUSION: PBLC with half reconstruction at 10 mA was comparable to that at 240 mA and better than those with full reconstruction on DVCT.

Preoperative assessment of pleural adhesion by Four-Dimensional Ultra-Low-Dose Computed Tomography (4D-ULDCT) with Adaptive Iterative Dose Reduction using Three-Dimensional processing (AIDR-3D).

PURPOSE: To assess the feasibility of Four-Dimensional Ultra-Low-Dose Computed Tomography (4D-ULDCT) for distinguishing pleural aspects with localized pleural adhesion (LPA) from those without. METHODS: Twenty-seven patients underwent 4D-ULDCT during a single respiration with a 16cm-coverage of the body axis. The presence and severity of LPA was confirmed by their intraoperative thoracoscopic findings. A point on the pleura and a corresponding point on the outer edge of the costal bone were placed in identical axial planes at end-inspiration. The distance of the two points (PCD), traced by automatic tracking functions respectively, was calculated at each respiratory phase. The maximal and average change amounts in PCD (PCDMCA and PCDACA) were compared among 110 measurement points (MPs) without LPA, 16MPs with mild LPA and 10MPs with severe LPA in upper lung field cranial to the bronchial bifurcation (ULF), and 150MPs without LPA, 17MPs with mild LPA and 9MPs with severe LPA in lower lung field caudal to the bronchial bifurcation (LLF) using the Mann-Whitney U test. RESULTS: In the LLF, PCDACA as well as PCDMCA demonstrated a significant difference among non-LPA, mild LPA and severe LPA (18.1±9.2, 12.3±6.2 and 5.0±3.3mm) (p<0.05). Also in the ULF, PCDACA showed a significant difference among three conditions (9.2±5.5, 5.7±2.8 and 2.2±0.4mm, respectively) (p<0.05), whereas PCDMCA for mild LPA was similar to that for non-LPA (12.3±5.9 and 17.5±11.0mm). CONCLUSIONS: Four D-ULDCT could be a useful non-invasive preoperative assessment modality for the detection of the presence or severity of LPA.