Amide proton transfer-weighted imaging with a short acquisition time based on a self B0 correction using the turbo spin echo-Dixon method: A phantom study.

PURPOSE: Conventional amide proton transfer (APT)-weighted imaging requires a chemical exchange saturation transfer (CEST) sequence with multiple saturation frequency offsets and a B0 correction sequence, plus a long acquisition time that can be reduced by applying the conventional method using CEST images with seven radiation pulses (i.e., the seven-points method). For a further reduction of acquisition times, we propose fast two-dimensional (2D) APT-weighted imaging based on a self B0 correction using the turbo spin echo (TSE)-Dixon method. We conducted a phantom study to investigate the accuracy of TSE-Dixon APT-weighted imaging. METHODS: We prepared two types of phantoms with six samples for a concentrationdependent evaluation and a pH-dependent evaluation. APT-weighted images were acquired by the conventional, seven-points, and TSE-Dixon methods. Linear regression analyses assessed the dependence between each method's APT signal intensities (SIs) and the concentration or pH. We performed a one-way analysis of variance with Tukey's honestly significant difference post hoc test to compare the APT SIs among the three methods. The agreement of the APT SIs between the conventional and seven-points or TSE-Dixon methods was assessed by a Bland- Altman plot analysis. RESULTS: The APT SIs of all three acquisition methods showed positive concentration dependence and pH dependence. No significant differences were observed in the APT SIs between the conventional and TSE-Dixon methods at each concentration. The Bland-Altman plot analyses showed that the APT SIs measured with the seven-points method resulted in 0.42% bias and narrow 95% limits of agreement (LOA) (0.93%-0.09%) compared to the conventional method. The APT SIs measured using the TSE-Dixon method showed 0.14% bias and similar 95% LOA (-0.33% to 0.61%) compared with the seven-points method. The APT SIs of all three methods showed positive pH dependence. At each pH, no significant differences in the APT SIs were observed among the methods. Bland-Altman plot analyses showed that the APT SIs measured with the seven-points method resulted in low bias (0.03%) and narrow 95% LOA (-0.30% to 0.36%) compared to the conventional method. The APT SIs measured by the TSE-Dixon method showed slightly larger bias (0.29%) and similar 95% LOA (from -0.15% to 0.72%) compared to those measured by the seven-points method. CONCLUSION: These results demonstrated that our proposed method has the same concentration dependence and pH dependence as the conventional method and the seven-points method. We thus expect that APT-weighted imaging with less influence of motion can be obtained in clinical examinations.

Improved temporal resolution and acceleration on 4D-MR angiography based on superselective pseudo-continuous arterial spin labeling combined with CENTRA-keyhole and view-sharing (4D-S-PACK) using an interpolation algorithm on the temporal axis and compressed sensing-sensitivity encoding (CS-SENSE).

PURPOSE: Two major drawbacks of 4D-MR angiography based on superselective pseudo-continuous arterial spin labeling combined with CENTRA-keyhole and view-sharing (4D-S-PACK) are the low temporal resolution and long scanning time. We investigated the feasibility of increasing the temporal resolution and accelerating the scanning time on 4D-S-PACK by using CS-SENSE and PhyZiodynamics, a novel image-processing program that interpolates images between phases to generate new phases and reduces image noise. METHODS: Seven healthy volunteers were scanned with a 3.0 T MR scanner to visualize the internal carotid artery (ICA) system. PhyZiodynamics is a novel image-processing that interpolates images between phases to generate new phases and reduces image noise, and by increasing temporal resolution using PhyZiodynamics, inflow dynamic data (reference) were acquired by changing the labeling durations (100-2000 msec, 31 phases) in 4D-S-PACK. From this set of data, we selected seven time intervals to calculate interpolated time points with up to 61 intervals using ×10 for the generation of interpolated phases with PhyZiodynamics. In the denoising process of PhyZiodynamics, we processed the none, low, medium, high noise reduction dataset images. The time intensity curve (TIC), the contrast-to-noise ratio (CNR) were evaluated. In accelerating with CS-SENSE for 4D-S-PACK, 4D-S-PACK were scanned different SENSE or CS-SENSE acceleration factors: SENSE3, CS3-6. Signal intensity (SI), CNR, were evaluated for accelerating the 4D-S-PACK. With regard to arterial vascular visualization, we evaluated the middle cerebral artery (MCA: M1-4 segments). RESULTS: In increasing temporal resolution, the TIC showed a similar trend between the reference dataset and the interpolated dataset. As the noise reduction weight increased, the CNR of the interpolated dataset were increased compared to that of the reference dataset. In accelerating 4D-S-PACK, the SI values of the SENSE3 dataset and CS dataset with CS3-6 were no significant differences. The image noise increased with the increase of acceleration factor, and the CNR decreased with the increase of acceleration factor. Significant differences in CNR were observed between acceleration factor of SENSE3 and CS6 for the M1-4 (P < 0.05). Visualization of small arteries (M4) became less reliable in CS5 or CS6 images. Significant differences were found for the scores of M2, M3 and M4 segments between SENSE3 and CS6. CONCLUSION: With PhyZiodynamics and CS-SENSE in 4D-S-PACK, we were able to shorten the scan time while improving the temporal resolution.

Refined scan protocol for the evaluation of pulmonary perfusion standardized image quality and reduced radiation dose in dynamic chest radiography.

PURPOSE: Dynamic chest radiography (DCR) is a novel imaging technique used to noninvasively evaluate pulmonary perfusion. However, the standard DCR protocol, which is roughly adapted to the patient's body size, occasionally causes over- or underexposure, which could influence clinical evaluation. Therefore, we proposed a refined protocol by increasing the number of patient body mass index (BMI) categories from three to seven groups and verified its usefulness by comparing the image sensitivity indicators (S-values) and entrance surface doses (ESDs) of the conventional protocol with those of our refined protocol. METHODS: This retrospective observational study included 388 datasets (standing position, 224; supine position, 164) for the conventional protocol (December 2019-April 2021) and 336 datasets (standing position, 233; supine position, 103) for the refined protocol (June-November 2021). The conventional protocol (BMI-3 protocol) divided the patients into three BMI groups (BMI < 17, 17≤BMI < 25, and BMI ≥ 25 kg/m2 ), whereas the refined protocol (BMI-7 protocol) divided the patients into seven BMI groups (BMI < 17, 17 ≤ BMI < 20, 20 ≤ BMI < 23, 23 ≤ BMI < 26, 26 ≤ BMI < 29, 29 ≤ BMI < 32, and BMI ≥ 32 kg/m2 ). The coefficients of variation (CVs) for the S-values and ESDs acquired using the two protocols were compared. RESULTS: The CVs of the S-values in the BMI-7 protocol group were significantly lower than those in the BMI-3 protocol group for the standing (28.8% vs. 16.7%; p < 0.01) and supine (24.5% vs. 17.7%; p < 0.01) positions. The ESDs of patients scanned using the BMI-7 protocol were significantly lower than those scanned using the BMI-3 protocol in the standing (1.3 vs. 1.1 mGy; p < 0.01) and supine positions (2.5 vs. 1.6 mGy; p < 0.01), although the mean BMI of the two groups were similar. CONCLUSION: We introduced the BMI-7 protocol and demonstrated its standardized image quality and reduced radiation exposure in patients undergoing DCR.

The Feasibility of Deep Learning-Based Reconstruction for Low-Tube-Voltage CT Angiography for Transcatheter Aortic Valve Implantation.

OBJECTIVE: The purpose of this study is to evaluate the efficacy of deep learning reconstruction (DLR) on low-tube-voltage computed tomographic angiography (CTA) for transcatheter aortic valve implantation (TAVI). METHODS: We enrolled 30 patients who underwent TAVI-CT on a 320-row CT scanner. Electrocardiogram-gated coronary CTA (CCTA) was performed at 100 kV, followed by nongated aortoiliac CTA at 80 kV using a single bolus of contrast material. We used hybrid-iterative reconstruction (HIR), model-based IR (MBIR), and DLR to reconstruct these images. The contrast-to-noise ratios (CNRs) were calculated. Five-point scales were used for the overall image quality analysis. The diameter of the aortic annulus was measured in each reconstructed image, and we compared the interobserver and intraobserver agreements. RESULTS: In the CCTA, the CNR and image quality score for DLR were significantly higher than those for HIR and MBIR ( P < 0.01). In the aortoiliac CTA, the CNR for DLR was significantly higher than that for HIR ( P < 0.01) and significantly lower than that for MBIR ( P ≤ 0.02). The image quality score for DLR was significantly higher than that for HIR ( P < 0.01). No significant differences were observed between the image quality scores for DLR and MBIR. The measured aortic annulus diameter had high interobserver and intraobserver agreement regardless of the reconstruction method (all intraclass correlation coefficients, >0.89). CONCLUSIONS: In low tube voltage TAVI-CT, DLR provides higher image quality than HIR, and DLR provides higher image quality than MBIR in CCTA and is visually comparable to MBIR in aortoiliac CTA.

[Possible Radiation Dose Reduction in Abdominal Plain CT Using Deep Learning Reconstruction].

PURPOSE: The purposes of this study were to evaluate the low-contrast detectability of CT images assuming hepatocellular carcinoma and to determine whether dose reduction in abdominal plain CT imaging is possible. METHODS: A Catphan 600 was imaged at 350, 250, 150, and 50 mA using an Aquilion ONE PRISM Edition (Canon) and reconstructed using deep learning reconstruction (DLR) and model-based iterative reconstruction (MBIR). A low-contrast object-specific contrast-to-noise ratio (CNRLO) was measured and compared in a 5-mm module with a CT value difference of 10 HU, assuming hepatocellular carcinoma; a visual examination was also performed. Moreover, an NPS within a uniform module was measured. RESULTS: CNRLO was higher for DLR at all doses (1.12 at 150 mA for DLR and 1.07 at 250 mA for MBIR). On visual evaluation, DLR could detect up to 150 mA and MBIR up to 250 mA. The NPS was lower for DLR at 0.1 cycles/mm at 150 mA. CONCLUSION: The low-contrast detection performance was better with DLR than with MBIR, indicating the possibility of dose reduction.

[Dosimetric Properties of Brass Mesh Bolus for High-energy Photon Beam].

PURPOSE: To investigate fundamental dosimetric properties of surface dose, exit dose, and beam profile of the brass mesh bolus for 4, 6, and 10 MV high-energy photon beams in radiation therapy. METHODS: Surface dose and exit dose in the water-equivalent phantom were measured, and percent depth doses (PDDs) were calculated with no bolus, one layer of brass mesh, two layers of brass mesh bolus, three layers of brass mesh bolus, and 0.5 cm tissue-equivalent (TE) bolus. Exit dose was measured at a phantom thickness of 10 cm. Beam profiles were measured at phantom depths of 0 cm and 10 cm. All dosimetry was performed for 4, 6, and 10 MV photon beams using a linear accelerator. RESULTS: The surface dose at a phantom depth of 0 cm increased to 37.3%, 36.3%, and 31.0% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The surface dose decreased with one layer of brass mesh bolus compared to that with the 0.5 cm TE bolus. On the other hand, the exit dose increased to 22.0%, 23.1%, and 22.8% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The beam profile at the depth of 0 cm showed oscillations, and the difference between the maximum and minimum doses was up to 13.1% with one layer of brass mesh bolus. CONCLUSION: It was suggested that the brass mesh bolus not only increases the surface dose but also has different properties from the conventional TE bolus.

Effect of Saturation Pulse Duration and Power on pH-weighted Amide Proton Transfer Imaging: A Phantom Study.

PURPOSE: Amide proton transfer (APT) imaging may detect changes in tissues' pH based on the chemical exchange saturation transfer (CEST) phenomenon, and thus it may be useful for identifying the penumbra in ischemic stroke patients. We investigated the effect of saturation pulse duration and power on the APT effect in phantoms with different pH values. METHODS: Five samples were prepared from a 1:10 solution of egg-white albumin in phosphate-buffered saline at pH 6.53-7.65. The APT signal intensity (SI) was defined as asymmetry of the magnetization transfer ratio at 3.5 ppm. We measured the APT SIs in the egg-white albumin samples of different pH values with saturation pulse durations of 0.5, 1.0, 2.0, and 3.0 sec and saturation pulse powers of 0.5, 1.5, and 2.5 µT. The relative change in the APT SI in relation to the saturation duration and power at different pH values was defined as follows: (APT SI each saturation pulse - APT SI shortest or weakest pulse)/APT SIshortest or weakest pulse. The dependence of the APT SI on pH and the relative change in the APT SI were calculated as the slope of the linear regression. RESULTS: The lower the pH, the larger the relative change in the APT SI, due to the change in saturation pulse duration and power. The APT SI was highly correlated with the pH at all saturation pulse durations and powers. CONCLUSION: The influence of saturation duration and power on the APT effect was greater at lower pH than higher pH. The combination of saturation pulse ≥ 1.0 s and power ≥ 1.5 µT was useful for the sensitive detection of changes in APT effects in the egg-white albumin samples with different pH values.

Characteristics of the deep learning-based virtual monochromatic image with fast kilovolt-switching CT: a phantom study.

PURPOSE: We assessed the physical properties of virtual monochromatic images (VMIs) obtained with different energy levels in various contrast settings and radiation doses using deep learning-based spectral computed tomography (DL-Spectral CT) and compared the results with those from single-energy CT (SECT) imaging. MATERIALS AND METHODS: A Catphan® 600 phantom was scanned by DL-Spectral CT at various radiation doses. We reconstructed the VMIs obtained at 50, 70, and 100 keV. SECT (120 kVp) images were acquired at the same radiation doses. The standard deviations of the CT number and noise power spectrum (NPS) were calculated for noise characterization. We evaluated the spatial resolution by determining the 10% task-based transfer function (TTF) level, and we assessed the task-based detectability index (d'). RESULTS: Regardless of the radiation dose, the noise was the lowest at 70 keV VMI. The NPS showed that the noise amplitude at all spatial frequencies was the lowest among other VMI and 120 kVp images. The spatial resolution was higher for 70 keV VMI compared to the other VMIs, except for high-contrast objects. The d' of 70 keV VMI was the highest among the VMI and 120 kVp images at all radiation doses and contrast settings. The d' of the 70 keV VMIs at the minimum dose was higher than that at the maximum dose in any other image. CONCLUSION: The physical properties of the DL-Spectral CT VMIs varied with the energy level. The 70 keV VMI had the highest detectability by far among the VMI and 120-kVp images. DL-Spectral CT may be useful to reduce radiation doses.

A deep learning model based on fusion images of chest radiography and X-ray sponge images supports human visual characteristics of retained surgical items detection.

PURPOSE: Although a novel deep learning software was proposed using post-processed images obtained by the fusion between X-ray images of normal post-operative radiography and surgical sponge, the association of the retained surgical item detectability with human visual evaluation has not been sufficiently examined. In this study, we investigated the association of retained surgical item detectability between deep learning and human subjective evaluation. METHODS: A deep learning model was constructed from 2987 training images and 1298 validation images, which were obtained from post-processing of the image fusion between X-ray images of normal post-operative radiography and surgical sponge. Then, another 800 images were used, i.e., 400 with and 400 without surgical sponge. The detection characteristics of retained sponges between the model and a general observer with 10-year clinical experience were analyzed using the receiver operator characteristics. RESULTS: The following values from the deep learning model and observer were, respectively, derived: Cutoff values of probability were 0.37 and 0.45; areas under the curves were 0.87 and 0.76; sensitivity values were 85% and 61%; and specificity values were 73% and 92%. CONCLUSION: For the detection of surgical sponges, we concluded that the deep learning model has higher sensitivity, while the human observer has higher specificity. These characteristics indicate that the deep learning system that is complementary to humans could support the clinical workflow in operation rooms for prevention of retained surgical items.

Grading of gliomas using 3D CEST imaging with compressed sensing and sensitivity encoding.

PURPOSE: We evaluated the usefulness of three-dimensional (3D) chemical exchange saturation transfer (CEST) imaging with compressed sensing and sensitivity encoding (CS-SENSE) for differentiating low-grade gliomas (LGGs) from high-grade gliomas (HGGs). METHODS: We evaluated 28 patients (mean age 51.0 ± 13.9 years, 13 males, 15 females) including 12 with LGGs and 16 with HGGs, all acquired using a 3 T magnetic resonance (MR) scanner. Nine slices were acquired for 3D CEST imaging, and one slice was acquired for two-dimensional (2D) CEST imaging. Two radiological technologists each drew a region of interest (ROI) surrounding the high-signal-intensity area(s) on the fluid-attenuated inversion recovery image of each patient. We compared the magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm in the tumors among the (i) single-slice 2D CEST imaging ("2D"), (ii) all tumor slices of the 3D CEST imaging (3Dall), and (iii) a representative tumor slice of 3D CEST imaging (maximum signal intensity [3Dmax]). The relationship between the MTRasym at 3.5 ppm values measured by these three methods and the Ki-67 labeling index (LI) of the tumors was assessed. Diagnostic performance was evaluated with a receiver operating characteristic analysis. The Ki-67LI and MTRasym at 3.5 ppm values were compared between the LGGs and HGGs. RESULTS: A moderate positive correlation between the MTRasym at 3.5 ppm and the Ki-67LI was observed with all three methods. All methods proved a significantly larger MTRasym at 3.5 ppm for the HGGs compared to the LGGs. All methods showed equivalent diagnostic performance. The signal intensity varied depending on the slice position in each case. CONCLUSIONS: The 3D CEST imaging provided the MTRasym at 3.5 ppm for each slice cross-section; its diagnostic performance was also equivalent to that of 2D CEST imaging.

Relationship between image information content and observer performance in digital intraoral radiography.

OBJECTIVES: This study conducted a receiver operating characteristic (ROC) analysis by applying improved cluster signal-to-noise (CSN) analysis to digital intraoral radiographs and develop an observer-free method of analyzing image quality related to the observer performance in the detection task. METHODS: Two aluminum step phantoms with a thickness interval of 1.0 mm were used for this study. One phantom had holes of increasing depth (from 0.05 to 0.35 mm) and the other had no holes. Phantom images were obtained under various exposure dose and image capture modes using a dental X-ray unit, a photostimulable phosphor imaging plate, and scanner system. These phantom images were analyzed using the FindFoci plugin in ImageJ software. Subsequently, true positive rates (TPRs) and false positive rates (FPRs) were calculated by analyzing phantom images with and without holes. We constructed ROC curves by plotting the TPRs against the FPRs and calculated the area under the ROC curve (AUC). Using the same phantom images with holes, eight observers assessed the number of detectable holes. Correlations between observer detection performance and AUC values were evaluated. RESULTS: AUC values increased as the exposure dose increased and showed different tendencies depending on the image capture mode. The AUC values showed a high correlation with observer detection performance (r = 0.76). CONCLUSIONS: AUC values obtained from CSN analysis reflect image quality and replace the observer detection performance test of image quality.

Impact of a new deep-learning-based reconstruction algorithm on image quality in ultra-high-resolution CT: clinical observational and phantom studies.

OBJECTIVES: To demonstrate the effect of an improved deep learning-based reconstruction (DLR) algorithm on Ultra-High-Resolution Computed Tomography (U-HRCT) scanners. METHODS: Clinical and phantom studies were conducted. Thirty patients who underwent contrast-enhanced CT examination during the follow-up period were enrolled. Images were reconstructed using improved DLR [termed, New DLR, i.e., Advanced Intelligent Clear-IQ Engine (AiCE) Body Sharp] and conventional DLR (Conv DLR, AiCE Body) algorithms. Two radiologists assessed the overall image quality using a 5-point scale (5 = excellent; 1 = unacceptable). The noise power spectra (NPSs) were calculated to assess the frequency characteristics of the image noise, and the square root of area under the curve (√AUC NPS) between 0.05 and 0.50 cycle/mm was calculated as an indicator of the image noise. Dunnett's test was used for statistical analysis of the visual evaluation score, with statistical significance set at p < 0.05. RESULTS: The overall image quality of New DLR was better than that of the Conv DLR (4.2 ± 0.4 and 3.3 ± 0.4, respectively; p < 0.0001). All New DLR images had an overall image quality score above the average or excellent. The √AUCNPS value of New DLR was lower than that of Conv DLR (13.8 and 14.2, respectively). The median values of reconstruction time required with New DLR and Conv DLR were 5.0 and 7.8 min, respectively. CONCLUSIONS: The new DLR algorithm improved the image quality within a practical reconstruction time. ADVANCES IN KNOWLEDGE: The new DLR enables us to choose whether to improve image quality or reduce the dose.

Detectability of category 3 or higher microcalcifications on digital mammograms: a comparative study between 5-MP color and monochrome liquid crystal display monitors.

This study explored the detectability of category 3 or higher microcalcifications using 5-MP color and monochrome monitors. Contrast detail mammography phantom with polymethyl methacrylate (PMMA) images were observed in color and monochrome by five radiographers, and the image quality figures (IQF) were calculated based on the gold disc locations identified. Five radiographers and two radiologists observed 200 mammograms from 100 patients (including 36 with microcalcifications) and rated the microcalcifications. The results were analyzed using area under the curve (AUC) and jackknife resampling. A paired t test was used for statistical analysis (p < 0.05). The mean IQF of color and monochrome monitors were 10.73 and 10.49 (30 mm PMMA, p = 0.653) and 8.47 and 8.74 (50 mm PMMA, p = 0.774), respectively. The mean AUC of color and monochrome monitors were 0.917 and 0.936 (p = 0.335), respectively, with windowing and magnification. The detectability of microcalcifications was not significantly different between the monitors.

Evaluation of resolution characteristics of digital intraoral radiographic images using a task transfer function.

OBJECTIVES: This study aimed to quantitatively examine the effect of digital image processing of digital intraoral radiographic images on the resolution characteristics of the output image using a task transfer function (TTF). METHODS: A photostimulable phosphor system with three types of image processing filters, including periodontal, endodontic, and dentine-to-enamel junction filters, was used. Each filter can be used in conjunction with the sharpness filter (+ S). Images were obtained from the original phantom, which combined aluminum disk and plate. The TTF, which indicates the resolution characteristics, was calculated. A one-dimensional profile curve was also measured, and the fluctuation in the pixel value was evaluated in detail. The results were compared to investigate the effects of digital image processing on digital intraoral radiographic images. RESULTS: The TTF values were specific to each filter. The change in the TTF strongly reflected the characteristics of the one-dimensional profile curve. The TTF was compared with a one-dimensional profile curve and was able to quantitatively express the resolution characteristics of all directions in the image. CONCLUSIONS: We attempted to evaluate the resolution characteristics of digital intraoral radiographic images with image processing filters using the TTF. The effect of each image processing filter and the + S filter on the resolution can be simply expressed using the TTF. Our results show that the TTF is useful for characterizing the resolution characteristics of image processing filters for image quality.

Three-dimensional chemical exchange saturation transfer imaging using compressed SENSE for full z-spectrum acquisition.

PURPOSE: To evaluate the accuracy of three-dimensional (3D) chemical exchange saturation transfer (CEST) imaging with a compressed sensing (CS) and sensitivity encoding (SENSE) technique (CS-SENSE) for full z-spectrum acquisition. METHODS: All images were acquired on 3-T magnetic resonance imaging (MRI) scanner. In the phantom study, we used the acidoCEST imaging. The phantoms were prepared in seven vials containing different concentrations of iopamidol mixed in phosphate-buffered solution with different pH values. The CEST ratios were calculated from the two CEST effects. We compared the CEST ratios obtained with three different 3D CEST imaging protocols (CS-SENSE factor 5, 7, 9) with those obtained with the 2D CEST imaging as a reference standard. In the clinical study, 21 intracranial tumor patients (mean 49.7 ± 17.2 years, 7 males and 14 females) were scanned. We compared the intratumor magnetization transfer ratio asymmetry (MTRasym) obtained with 3D CEST imaging with those obtained with 2D CEST imaging as a reference standard. RESULTS: A smaller CS-SENSE factor resulted in higher agreement and better correlations with the 2D CEST imaging in the phantom study (CS-SENSE 5; ICC = 0.977, R2 = 0.8943, P < 0.0001: CS-SENSE 7; ICC = 0.970, R2 = 0.9013, P < 0.0001: CS-SENSE 9; ICC = 0.934, R2 = 0.8156 P < 0.0001). In the brain tumors, the means and percentile values of MTRasym at 2.0 and 3.5 ppm showed high linear correlations (R2 = 0.7325-0.8328, P < 0.0001) and high ICCs (0.859-0.907), which enabled successful multi-slice CEST imaging. CONCLUSIONS: The 3D CEST imaging with CS-SENSE provided equivalent contrast to 2D CEST imaging; moreover, a z-spectrum with a wide scan range could be obtained.

Potential for personal identification using the volume of the mastoid air cells extracted from postmortem computed tomographic images.

This study revealed the usefulness of volumetric analysis of mastoid air cells (MACs) extracted from postmortem computed tomography (PMCT) images in characterizing individuals. To characterize deceased persons, the MACs volumes of 61 Japanese PMCT images were measured after thresholding in Hounsfield units and based on the number of voxels on the right and left sides and the voxel size for each person. The volume differences between the right and left MACs and sex were examined. Although there were no obvious volume differences between males and females, the order of sizes on the two sides varied for each person. Moreover, deceased persons could be roughly classified using the total volume of MACs. Deceased persons with similar total volumes could be distinguished further by comparing the ratio of volumes in bilateral MACs. Although the identification process is dependent on samples and different sizes of bilateral MACs, our pilot study indicated that 81.9% (50/61) of deceased persons could be distinguished. In conclusion, volumetric analysis of MACs measured using PMCT imaging has the potential to identify individuals and reduce the number of candidates.

Importance of the heart rate in ultra-high-resolution coronary CT angiography with 0.35 s gantry rotation time.

PURPOSE: We investigated the effects of the heart rate (HR) on the motion artifact in coronary computed tomography angiography (CCTA) with ultra-high-resolution-CT (U-HRCT), and we clarified the upper limit of optimal HR in CCTA with U-HRCT in a comparison with conventional-resolution-CT (CRCT) on a cardiac phantom and in patients with CCTA. MATERIALS AND METHODS: A pulsating cardiac phantom equipped with coronary models was scanned at static and HR simulations of 40-90 beats/min (bpm) at 10-bpm intervals using U-HRCT and CRCT, respectively. The sharpness and lumen diameter of the coronary model were quantitatively compared between U-HRCT and CRCT stratified by HR in the phantom study. We also assessed the visual inspections of clinical images in CCTA with U-HRCT. RESULTS: At the HRs ≤ 60 bpm, the error of the lumen diameter of the U-HRCT tended to be smaller than that of the CRCT. However, at the HRs > 60 bpm, the inverse was shown. For the image sharpness, the U-HRCT was significantly superior to the CRCT (p < 0.05). In the visual assessment, the scores were negatively correlated with HRs in patients (Spearman r = - 0.71, p < 0.01). A receiver-operating characteristic analysis revealed the HR of 61 bpm as the optimal cutoff of the non-diagnostic image quality, with an area under the curve of 0.87, 95% sensitivity, and 71% specificity. CONCLUSION: At HRs ≤ 60 bpm, U-HRCT was more accurate in the imaging of coronary arteries than CRCT. The upper limit of the optimal HR in CCTA with U-HRCT was approx. 60 bpm.

Is the image quality of conventional chest radiography obtained from a two-layer flat panel detector affected by the internal structure of the detector?

PURPOSE: Recently developed and commercialized dual-layer flat panel detectors (DL-FPDs) with two indirect scintillators are capable of acquiring dual-energy X-ray images. However, in clinical practice, they are utilized to perform conventional radiography using diagnostic X-rays with a wide energy spectrum. The two layers of the DL-FPD may affect the obtained image quality, even when only using one layer for conventional image acquisition, and these effects are yet to be substantiated. Therefore, in this study, we quantitatively evaluated the image quality of a conventional chest radiography using DL-FPD and visually verified the characteristics of the chest anthropomorphic phantom images. METHODS: The physical characteristics of the system were evaluated using the pre-sampled modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), for beam quality RQA 7 and RQA 9. In addition, the subjective visibility of the anthropomorphic chest phantom and simple objects images were compared with those of a conventional single-layer flat-panel detector (SL-FPD). RESULTS: No significant differences were found in the MTF between the SL-FPD and DL-FPD images. In addition, a higher DQE was observed at some exposure doses and in the high spatial frequency regions wherein NNPSs were lower for DL-FPD than for SL-FPD. Furthermore, no significant differences were found in the subjective visibility of the chest phantoms in each system. CONCLUSIONS: We concluded that the image quality of the conventional radiography acquired with DL-FPD is comparable to or better than that of the SL-FPD.

Low-radiation dose scan protocol for preoperative imaging for dental implant surgery using deep learning-based reconstruction in multidetector CT.

OBJECTIVES: This study aimed to investigate the impact of a deep learning-based reconstruction (DLR) technique on image quality and reduction of radiation exposure, and to propose a low-dose multidetector-row computed tomography (MDCT) scan protocol for preoperative imaging for dental implant surgery. METHODS: The PB-1 phantom and a Catphan phantom 600 were scanned using volumetric scanning with a 320-row MDCT scanner. All scans were performed with a tube voltage of 120 kV, and the tube current varied from 120 to 60 to 40 to 30 mA. Images of the mandible were reconstructed using DLR. Additionally, images acquired with the 120-mA protocol were reconstructed using filtered back projection as a reference. Two observers independently graded the image quality of the mandible images using a 4-point scale (4, superior to reference; 1, unacceptable). The system performance function (SPF) was calculated to comprehensively evaluate image quality. The Wilcoxon signed-rank test was employed for statistical analysis, with statistical significance set at p value < 0.05. RESULTS: There was no significant difference between the image quality acquired with the 40-mA tube current and reconstructed with the DLR technique (40DLR), and that acquired with the reference protocol (3.00, 3.00, p = 1.00). The SPF at 1.0 cycles/mm acquired with 40DLR was improved by 156.7% compared to that acquired with the reference protocol. CONCLUSIONS: Our proposed protocol, which achieves a two-thirds reduction in radiation dose, can provide a minimally invasive MDCT scan of acceptable image quality for dental implant surgery.

Angular accuracy of plain radiographic measurements in leg alignment: Teleoroentgenogram versus orthoroentgenogram.

BACKGROUND: The purpose of the present study was to evaluate the accuracy of the measurements associated with leg alignment on a teleoroentgenogram and an orthoroentgenogram. METHODS: The models being irradiated were manufactured and represented 10° varus and 15° varus leg alignment, in which the true values of hip-knee-ankle angle (HKAA), mechanical axis (MA) length, and percentage of MA (%MA) were already known. HKAA, MA length, and %MA were measured in various radiographic conditions of the teleoroentgenogram and orthoroentgenogram. Then, the differences between the radiographic measurement values and the corresponding true values were analyzed. RESULTS: Regarding HKAA, the teleoroentgenogram provided accurate angular measurements with minimal differences between the measurement and true value in both the 10° and 15° varus models, irrespective of the radiographic condition. In the orthoroentgenogram, the modified method measured accurate HKAA; however, the standard method showed significant angular measurement errors with a 0.6° and 1.0° difference from the true value in the 10° and 15° varus models, respectively. This angular measurement error of HKAA in the standard orthoroentgenogram became significantly larger with object-to-image distance. Regarding MA length, the orthoroentgenogram exhibited accurate length measurements. In contrast, the teleoroentgenogram showed a significant length measurement error for the MA length. Regarding %MA, significant differences from the true values of 2.0% and 2.4% were observed in the modified orthoroentgenograms of the 10° and 15° varus models, respectively. The teleoroentgenogram and standard orthoroentgenogram reproduced the accurate measurement value of %MA in the 10° and 15° varus models. CONCLUSION: A teleoroentgenogram is a reliable modality for accurate angular measurements such as HKAA and %MA. An orthoroentgenogram has the potential to measure both HKAA and length accurately if the radiographic condition was modified; however, measurement error in %MA may occur.