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.

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.

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.

New transluminal attenuation gradient derived from dynamic coronary CT angiography: diagnostic ability of ischemia detected by 13N-ammonia PET.

Coronary computed tomography angiography (CCTA) has low specificity for detecting significant functional coronary stenosis. We developed a new transluminal attenuation gradient (TAG)-derived dynamic CCTA with dose modulation, and we investigated its diagnostic performance for myocardial ischemia depicted by 13N-ammonia positron emission tomography (PET). Data from 48 consecutive patients who had undergone both dynamic CCTA and 13N-ammonia PET were retrospectively analyzed. Dynamic CCTA was continuously performed in mid-diastole for five cardiac cycles with prospective electrocardiography gating after a 10-s contrast medium injection. One scan of the dynamic CCTA was performed as a boost scan for conventional CCTA at the peak phase of the ascending aorta. Absolute TAG values at five phases around the boost scan were calculated. The dynamic TAG index (DTI) was defined as the ratio of the maximum absolute TAG to the standard deviation of five TAG values. We categorized the coronary territories as non-ischemia or ischemia based on the 13N-ammonia PET results. A receiver operating characteristic (ROC) analysis was performed to determine the optimal cutoff of the DTI for identifying ischemia. The DTI was significantly higher for ischemia compared to non-ischemia (8.8 ± 3.9 vs. 4.6 ± 2.0, p < 0.01). The ROC analysis revealed 5.60 as the optimal DTI cutoff to detect ischemia, with an area under the curve of 0.87, 85.7% sensitivity, and 76.2% specificity. TAG provided no additional diagnostic value for the detection of ischemia. We propose the DTI derived from dynamic CCTA as a novel coronary flow index. The DTI is a valid technique for detecting functional coronary stenosis.

Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.

PURPOSE: In an ultrahigh-resolution CT (U-HRCT), deep learning-based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation doses assuming an abdominal CT protocol. METHODS: For the normal-sized abdominal models, a Catphan 600 was scanned by U-HRCT with 100%, 50%, and 25% radiation doses. In all acquisitions, DLR was compared to model-based iterative reconstruction (MBIR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR). For the quantitative assessment, we compared image noise, which was defined as the standard deviation of the CT number, and spatial resolution among all reconstruction algorithms. RESULTS: Deep learning-based reconstruction yielded lower image noise than FBP and HIR at each radiation dose. DLR yielded higher image noise than MBIR at the 100% and 50% radiation doses (100%, 50%, DLR: 15.4, 16.9 vs MBIR: 10.2, 15.6 Hounsfield units: HU). However, at the 25% radiation dose, the image noise in DLR was lower than that in MBIR (16.7 vs. 26.6 HU). The spatial frequency at 10% of the modulation transfer function (MTF) in DLR was 1.0 cycles/mm, slightly lower than that in MBIR (1.05 cycles/mm) at the 100% radiation dose. Even when the radiation dose decreased, the spatial frequency at 10% of the MTF of DLR did not change significantly (50% and 25% doses, 0.98 and 0.99 cycles/mm, respectively). CONCLUSION: Deep learning-based reconstruction performs more consistently at decreasing dose in abdominal ultrahigh-resolution CT compared to all other commercially available reconstruction algorithms evaluated.

Low Radiation Dose and High Image Quality of 320-Row Coronary Computed Tomography Angiography Using a Small Dose of Contrast Medium and Refined Scan Timing Prediction.

OBJECTIVE: The aim of the study was to investigate the feasibility of coronary computed tomography (CT) angiography with a low kilovoltage peak scan and a refined scan timing prediction using a small contrast medium (CM) dose. METHODS: In protocol A, 120-kVp scanning and a standard CM dose were used. The scan timing was fixed. In protocol B, 80 kVp and a 60% CM dose were used. The scan timing was determined according to the interval from the CM arrival to the peak time in the ascending aorta. We measured the CT number and recorded the radiation dose. RESULTS: Higher CT numbers were observed in the left circumflex (proximal, P = 0.0235; middle, P = 0.0007; distal, P < 0.0001) in protocol B compared with protocol A. The radiation dose in protocol B was significantly lower than in protocol A (2.2 ± 0.9 vs 4.3 ± 1.7 mSv). CONCLUSIONS: Low-contrast, low-radiation dose, high-image quality coronary CT angiography can be performed with low kilovoltage peak scanning and a refined scan timing prediction.

[Reduction of Operator Exposure Radiation Dose and Evaluation of Image Quality Using Half Scan in CT Fluoroscopy].

In recent years, the number of examinations and treatments using computed tomography fluoroscopy (CTF) has been increasing, and there is concern about an increase in the exposure radiation dose of the operator. Use of half scan CTF can be expected to reduce the exposure radiation dose, but there is no report. The purpose of this study was to evaluate the exposure radiation dose at the operator's position and image quality when using a half scan CTF. The left side facing the gantry was the operator's position, and the ambient dose equivalent at 160 cm, 130 cm, and 100 cm from the floor was measured using an ionization chamber survey meter. The absorbed dose at the forceps holding position of the operator was measured using a fluorescent glass dosimeter with the forceps holding position 15 cm caudal from the scan center. The imaging conditions used a tube voltage of 120 kV and a tube current of 50 mA. Half scan CTF was performed by changing the center angle of the half scan on the console every 45°. As a result, the set angles were 135°and 90°at the operator's position, and 135°at the operator's forceps holding position. In addition, we evaluated the effect of half scan CTF on image quality. CTF images were collected with a cryogenic needle used for cryotherapy punctured in a water-equivalent self-made phantom. The profile curves of the obtained images were drawn and compared using analysis software to evaluate the effects of artifacts. Then, the SD of the CT value of the region of interest with and without the artifact was measured, and the relative artifact index was calculated and evaluated. Using the same image, CT value and SD were tested to evaluate noise. Half scan CTF had no effect on the image quality due to artifacts and noise.

[Usefulness of Biological Fingerprints and Template Matching Techniques in Bedside Chest Radiography for Patient Identification and Preventing Filing Mistakes].

The purpose of this study was to investigate whether patients can be identified by using biological fingerprints extracted from bedside chest radiographs and template matching techniques for preventing filing mistakes in a picture archiving and communication system (PACS) server. A total of 400 bedside chest radiographs from 100 male and 100 female patients with current and previous images were used for evaluating patient identification performance. Five biological fingerprints were extracted from 200 previous images using the averaged bedside chest radiographs, produced for each sex and detector size. The correlation values of 200 same patients and 39,800 different patients were calculated as a similarity index, and used for the receiver operating characteristic (ROC) analysis. The patient identification performance was examined by using the correlation index calculated by the summation of correlation values obtained from five biological fingerprints. The sensitivity at 90.0% specificity was calculated using the correlation index. The correlation index for same patients was higher than that for different patients. The area under the ROC curve was 0.974. The patient identification performance was 76.0% (152/200), and the sensitivity at 90.0% specificity was 93.4% (37168/39800). Our results suggest that the proposed method may potentially be useful for preventing filing mistakes in bedside chest radiographs on a PACS server.

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.

Influence of cardiac cycle on myocardial extracellular volume fraction measurements with dual-layer computed tomography.

Background: In cardiac computed tomography (CT), the best image quality is obtained at mid-diastole at low heart rates (HRs) and at end-systole at high HRs. On the other hand, extracellular volume (ECV) measurements may be influenced by the cardiac phase. Therefore, we aimed to clarify the influence of the cardiac phase on the image quality and ECV values obtained using dual-layer spectral computed tomography (DLCT). Methods: Fifty-five patients (68.0±14.5 years; 26 men) with cardiac diseases who underwent retrospective electrocardiogram-gated myocardial CT delayed enhancement (CTDE) between February 2019 to April 2022 were enrolled. The ECVs at the right ventricle (RV) and left ventricle (LV) walls in the end-systolic and mid-diastolic phases were calculated using iodine-density measurements from CTDE spectral data. Iodine-density image quality was classified on a 4-point scale. ECV and image quality across cardiac phases were compared using the t-test and Wilcoxon signed-rank test, respectively. Inter- and intraobserver variability were evaluated using intraclass correlation coefficient (ICC) values. Results: The ECV of the septal regions during mid-diastole was significantly higher than that during end-systole. Other regions showed similar ECV measurements in both groups (P=0.13-0.97), except for the LV anterior wall and LV posterior wall at the base-ventricular level. The image-quality score in end-systole was significantly higher than that in mid-diastole (systole vs. diastole: 3.6±0.5 vs. 3.2±0.7; P=0.0195). Intra- and interobserver variabilities for RV ECV measurements at the end-systolic phase were superior to those at the mid-diastolic phase, whereas the corresponding values for LV ECV measurements were similar. Conclusions: Septal ECV showed small but significant differences while other region ECV showed no difference during the cardiac cycle. RV ECV measurements in the end-systolic phase were more reproducible than those in the mid-diastolic phase.

Evaluation of PTV margin in CBCT-based online adaptive radiation therapy for gastric mucosa-associated lymphoid tissue lymphoma.

The aim of this study was to investigate planning target volume (PTV) margin in online adaptive radiation therapy (oART) for gastric mucosa-associated lymphoid tissue (MALT) lymphomas. Four consecutive patients with gastric MALT lymphoma who received oART (30 Gy in 15 fractions) on the oART system were included in this study. One hundred and twenty cone-beam computed tomography (CBCT) scans acquired pre- and post-treatment of 60 fractions for all patients were used to evaluate intra- and interfractional motions. Patients were instructed on breath-holding at exhalation during image acquisition. To assess the intrafraction gastric motion, different PTVs were created by isotropically extending the CTV contoured on a pre-CBCT image (CTVpre) at1 mm intervals. Intrafraction motion was defined as the amount of expansion covering the contoured CTV on post-CBCT images (CTVpost). Interfractional motion was defined as the amount of reference CTV expansion that could cover each CTVpre, as well as the evaluation of the intrafractional motion. PTV margins were estimated from the cumulative proportion of fraction covering the intra- and interfractional motions. The extent of expansion covering the CTVs in 90% of fractions was adopted as the PTV margin. The PTV margin for intrafractional gastric motion using the oART system with breath-holding was 14 mm. In contrast, the PTV margin for interfractional gastric organ motion without the oART system was 25 mm. These results indicated that the oART system can reduce the PTV margin by >10 mm. Our results could be valuable data for oART cases.

Improvement of image quality for bright-blood image in VISIBLE (volume isotropic simultaneous interleaved bright- and black-blood examination) by using k-space reordering and startup echoes.

PURPOSE: A volume isotropic simultaneous interleaved bright- and black-blood examination (VISIBLE) can simultaneously acquire images with suppressed vascular signals (black-blood images) and images without suppression (bright-blood images). We aimed to improve of the bright-blood images by adjusting the k-space filling and using startup echo. METHODS: The k-space arrangement of bright-blood images in the conventional VISIBLE followed a low-to-high frequency order, whereas that in the proposed VISIBLE sequence was in the reversed order, and a startup echo was added. The effects of startup echo on the signal-to-noise ratio (SNR) were evaluated using phantoms, considering both white matter (WM) and post-contrast blood. Data from copper sulfate phantoms were acquired in 1D Fourier transform mode using both the conventional and proposed methods of the two VISIBLE sequences. The signal behavior with each sequence was evaluated. Fourteen patients with a total of 21 metastases were included in the study. For each patient, VISIBLE images of both conventional and proposed methods were obtained consecutively after the contrast agent administration. Using clinical images, we conducted a comparison of the SNR and contrast-to-noise ratio (CNR) for tumors, normal WM, and blood vessels between the conventional and proposed VISIBLE sequences. RESULTS: There was no significant difference in SNRs for both black- and bright-blood images between the conventional sequence and the proposed sequence with different number of startup echoes, however, the SNR of the proposed sequence decreased with increasing number of startup echoes in both black- and bright-images. The signal behavior of the bright-blood image reached a "steady state" when the startup echo exceeded 20. The SNRs of blood vessels in the bright-blood images did not differ significantly between conventional and proposed VISIBLE sequences. The SNRs of WM in the bright-blood images was significantly larger in the conventional sequence than in the proposed sequence. The SNRs of tumors in bright blood images was significantly larger in the proposed sequence than in the conventional sequence. The CNRs between tumors and WM, vessels and WM in the bright-blood images were significantly higher in the proposed sequence than in the conventional sequence. CONCLUSION: The use of the startup echo in combination with the high-to-low frequency k-space ordering method resulted in improved CNR of the bright-blood images in the VISIBLE sequence.

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.

[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.

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.

[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.

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.