Physical characteristics of deep learning-based image processing software in computed tomography: a phantom study.

PURPOSE: This study aimed to assess the image characteristics of deep-learning-based image processing software (DLIP; FCT PixelShine, FUJIFILM, Tokyo, Japan) and compare it with filtered back projection (FBP), model-based iterative reconstruction (MBIR), and deep-learning-based reconstruction (DLR). METHODS: This phantom study assessed the object-specific spatial resolution (task-based transfer function [TTF]), noise characteristics (noise power spectrum [NPS]), and low-contrast detectability (low-contrast object-specific contrast-to-noise ratio [CNRLO]) at three different output doses (standard: 10 mGy; low: 3.9 mGy; ultralow: 2.0 mGy). The processing strength of DLIPFBP with A1, A4, and A9 was compared with those of FBP, MBIR, and DLR. RESULT: The standard dose with high-contrast TTFs of DLIPFBP exceeded that of FBP. Low-contrast TTFs were comparable to or lower than that of FBP. The NPS peak frequency (fP) of DLIPFBP shifts to low spatial frequencies of up to 8.6% at ultralow doses compared to the standard FBP dose. MBIR shifted the most fP compared to FBP-a marked shift of up to 49%. DLIPFBP showed a CNRLO equal to or greater than that of DLR in standard or low doses. In contrast, the CNRLO of the DLIPFBP was equal to or lower than that of the DLR in ultralow doses. CONCLUSION: DLIPFBP reduced image noise while maintaining a resolution similar to commercially available MBIR and DLR. The slight spatial frequency shift of fP in DLIPFBP contributed to the noise texture degradation suppression. The NPS suppression in the low spatial frequency range effectively improved the low-contrast detectability.

Fact-finding survey on the competencies and literacy of radiological technologists regarding radiation disasters.

BACKGROUND: Radiological technologists serve as risk communicators who aim to lessen patients' anxiety about radiation exposure, in addition to performing radiological examinations. OBJECTIVE: We conducted a fact-finding survey on knowledge and awareness of radiation disasters among the radiological technologists to reveal their literacy and competencies regarding radiation disasters. METHODS: A paper questionnaire was distributed to 1,835 radiological technologists at 166 National Hospital Organization facilities in Japan. The 28-item questionnaire covered knowledge and awareness of radiation protection and radiation disasters. Radiological technologists were divided into 2 groups by regionality: areas where a nuclear power station was present/nearby (NPS areas) and non-NPS areas. RESULTS: Completed questionnaires were returned from 148 facilities with a facility response rate of 89.2% and from 1,391 radiological technologists with a response rate of 75.8%. There were 1,290 valid responses with a valid response rate of 70.3%. The correct answer rate for knowledge of radiation protection and radiation disasters was high in the 24 NPS areas. There were no differences in awareness of radiation disasters between NPS and non-NPS areas. CONCLUSIONS: Establishing a nationwide, region-independent training system can be expected to improve literacy regarding radiation disasters among radiological technologists. Willingness to assist during disasters was high among radiological technologists irrespective of area, indicating that the competencies of radiological technologists represent a competency model for radiation disaster assistance.

Validation of a convolutional neural network for the automated creation of curved planar reconstruction images along the main pancreatic duct.

PURPOSE: To evaluate the accuracy and time-efficiency of newly developed software in automatically creating curved planar reconstruction (CPR) images along the main pancreatic duct (MPD), which was developed based on a 3-dimensional convolutional neural network, and compare them with those of conventional manually generated CPR ones. MATERIALS AND METHODS: A total of 100 consecutive patients with MPD dilatation (≥ 3 mm) who underwent contrast-enhanced computed tomography between February 2021 and July 2021 were included in the study. Two radiologists independently performed blinded qualitative analysis of automated and manually created CPR images. They rated overall image quality based on a four-point scale and weighted κ analysis was employed to compare between manually created and automated CPR images. A quantitative analysis of the time required to create CPR images and the total length of the MPD measured from CPR images was performed. RESULTS: The κ value was 0.796, and a good correlation was found between the manually created and automated CPR images. The average time to create automated and manually created CPR images was 61.7 s and 174.6 s, respectively (P < 0.001). The total MPD length of the automated and manually created CPR images was 110.5 and 115.6 mm, respectively (P = 0.059). CONCLUSION: The automated CPR software significantly reduced reconstruction time without compromising image quality.

Impact of pixel value truncation on image quality of low dose chest CT.

PURPOSE: In some noisy low dose CT lung cancer screening images, we noticed that the CT density values of air were increased and the visibility of emphysema was distinctly decreased. By examining histograms of these images, we found that the CT density values were truncated at -1024 HU. The purpose of this study was to investigate the effect of pixel value truncation on the visibility of emphysema using mathematical models. METHODS AND MATERIALS: Assuming CT noise follows a normal distribution, we derived the relationship between the mean CT density value and the standard deviation (SD) when the pixel values below -1024 HU are truncated and replaced by -1024 HU. To validate our mathematical model, 20 untruncated phantom CT images were truncated by simulation, and the mean CT density values and SD of air in the images were measured and compared with the theoretical values. In addition, the mean CT density values and SD of air were measured in 100 cases of real clinical images obtained by GE, Siemens, and Philips scanners, respectively, and the agreement with the theoretical values was examined. Next, the contrast-to-noise ratio (CNR) between air (-1000 HU) and lung parenchyma (-850 HU) was derived from the mathematical model in the presence and absence of truncation as a measure of the visibility of emphysema. In addition, the radiation dose ratios required to obtain the same CNR in the case with and without truncation were also calculated. RESULTS: The mathematical model revealed that when the pixel values are truncated, the mean CT density values are proportional to the noise magnitude when the magnitude exceeds a certain level. The mean CT density values and SD measured in the images with pixel values truncated by simulation and in the real clinical images acquired by GE and Philips scanners agreed well with the theoretical values from our mathematical model. In the Siemens images, the measured and theoretical values agreed well when a portion of the truncated values were replaced by random values instead of simply replacing by -1024 HU. The CNR of air and lung parenchyma was lowered by truncating CT density values compared to that of no truncation. Furthermore, it was found that higher radiation dose was required to obtain the same CNR with truncation as without. As an example, when the noise SD was 60 HU, the radiation dose required for the GE and Philips truncation method was about 1.2 times higher than that without truncation, and that for the Siemens truncation method was about 1.4 times higher. CONCLUSIONS: It was demonstrated mathematically that pixel value truncation causes a brightening of the mean CT density value and decreases the CNR of emphysema. Our results indicate that it is advisable to turn off truncation at -1024 HU, especially when scanning at low and ultra-low radiation doses in the thorax.

Noise reduction profile: A new method for evaluation of noise reduction techniques in CT.

PURPOSE: Noise power spectrum (NPS) is a commonly used performance metric to evaluate noise-reduction techniques (NRT) in imaging systems. The images reconstructed with and without an NRT can be compared via their NPS to better understand the NRT's effects on image noise. However, when comparing NPSs, simple visual assessments or a comparison of NPS peaks or medians are often used. These assessments make it difficult to objectively evaluate the effect of noise reduction across all spatial frequencies. In this work, we propose a new noise reduction profile (NRP) to facilitate a more complete and objective evaluation of NPSs for a range of NRTs used specifically in computed tomography (CT). METHODS AND MATERIALS: The homogeneous section of the ACR or Catphan phantoms was scanned on different CT scanners equipped with the following NRTs: AIDR3D, AiCE, ASiR, ASiR-V, TrueFidelity, iDose, SAFIRE, and ADMIRE. The images were then reconstructed with all strengths of each NRT in reference to the baseline filtered back projection (FBP) images. One set of the baseline FBP images was also processed with PixelShine, an NRT based on artificial intelligence. The NPSs of the images before and after noise reduction were calculated in both the xy-plane and along the z-direction. The difference in the logarithmic scale between each NPS (baseline FBP and NRT) was then calculated and deemed the NRP. Furthermore, the relationship between the NRP and NPS peak positions was mathematically analyzed. RESULTS: Each NRT has its own unique NRP. By comparing the NPS and NRP for each NRT, it was found that NRP is related to the peak shift of NPS. Additionally, under the assumption that the NPS has one peak and is differentiable, a relationship was mathematically derived between the slope of the NRP at the peak position of the NPS before noise reduction and the shift of the NPS peak position after noise reduction. CONCLUSIONS: A new metric, NRP, was proposed based on NPS to objectively evaluate and compare methods for noise reduction in CT. The NRP can be used to compare the effects of various NRTs on image noise in both the xy-plane and z-direction. It also enables unbiased assessment of the detailed noise reduction properties of each NRT over all relevant spatial frequencies.

Technical Note: Scanner dependence of adaptive statistical iterative reconstruction with 3D noise power spectrum central frequency and noise magnitude ratios.

PURPOSE: In this study, the noise reduction properties of the adaptive statistical iterative reconstruction (IR) on two different CT scanners of 64 and 256-slice were compared and their differences were assessed. METHODS AND MATERIALS: The homogeneous module of the ACR CT phantom was scanned on the 64 and 256 slices CT scanners from the same vendor in the range of 15-40 mA. On each scanner, the data were reconstructed using filtered back projection (FBP) and at all strengths of IR with the STANDARD kernel. For each reconstruction, a 3D noise power spectrum (NPS) was calculated and the central frequency ratio in the xy plane (CFRxy ), CFR in the z-direction (CFRz ), and noise magnitude ratio (NMR) were derived. CFR is the central frequency ratio of NPS between the denoised image and the FBP image, and NMR is the ratio of the areas under the NPS curves. Ideally, both CFRxy and CFRz should be near 1, indicating minimal texture changes in both xy and z directions, while NMR should be as close to 0 as possible, indicating more noise reduction. RESULTS: When comparing strengths with equivalent impact on noise texture, IR on the 64-slice reduced the noise magnitude in the xy plane more than that on the 256-slice. In the z-direction, the IR on the 256-slice produced a central frequency shift on the 256-slice but not on the 64-slice. In addition, the noise reduction effects of the IR on the 256-slice were affected when radiation exposure was below 2.0 mGy, but there was no observable dose-dependence on the 64-slice. CONCLUSIONS: Our noise property analysis revealed that iterative reconstructions on different scanner platforms from the same vendor can be distinct, with unique effects on the noise texture and magnitude in CT images. The IR on a 64-slice scanner provides slightly enhanced noise reduction and maintains a noise reduction rate independent of dose, unlike the one on a 256-slice scanner. Notably, the IR on the 64-slice scanner was a 2D noise reduction technique (NRT), while the one on the 256-slice was a 3D NRT. These observations showcase the impact of different NRTs on clinical CT images, even when comparing the same NRT on different scanners.

Novel imaging detailing the origins of a pneumothorax.

This is a prospective clinical study aimed at introducing a method to visualise the location of an air leak and to identify the bulla responsible on three-dimensional (3-D) cine CT. In 10 patients with spontaneous pneumothorax, dynamic 320-detector row CT was performed with injection of 0.9% saline into the affected pleural cavity via a preplaced chest tube. In eight cases, 3-D cine CT thoracography revealed the location of the air leak and the bulla responsible (7 cases: air stream sign; 1 case: repeated collapse and expansion of a bulla with the patient's breathing).

Peptide Specificity Analysis of Peptide: N-glycanases Using Synthetic Chitobiose-pentapeptides.

BACKGROUND: Peptide: N-glycanase is a deglycosylation enzyme releasing N-glycan from glycoproteins. Although glycan specificity analysis of this enzyme has been reported, recognition requirements for the peptide sequence have not been precisely elucidated. OBJECTIVE: In this study, we carried out peptide specificity analysis of several peptide:N-glycanases. METHODS: Using synthetic chitobiose-pentapeptide substrates having a systematic series of amino acid sequences composed of hydrophobic leucine and hydrophilic serine, we examined the peptide specificities of peptide: N-glycanases comprising yeast cytoplasmic PNGase, bacterial PNGase F, and plant PNGase A by ultra-performance liquid chromatography combined with electrospray ionization mass spectrometry. RESULTS: We found that each of the PNGases had higher activity for the more hydrophobic (leucinerich) chitobiose-pentapeptides, although the sensitivities of the PNGases for hydrophobicity varied. Cytoplasmic PNGase showed broad specificity. In contrast, PNGase A showed moderate specificity. PNGase F showed the highest specificity. CONCLUSION: PNGases from different origins had similar but significantly independent peptide specificities.

Glycopeptide probes for understanding peptide specificity of the folding sensor enzyme UGGT.

A systematic series of chitobiose-modified pentapeptides with sequence variations of hydrophobic leucine and hydrophilic serine were synthesized. The resulting glycopeptides were used as molecular probes to elucidate aglycon peptide specificity of the glycoprotein-folding sensor enzyme UGGT. Inhibitory experiments with a synthetic fluorescent glyco-substrate and the glycopeptides revealed that UGGT prefers a serine residue directly linked to C-terminal of the N-glycosylation site in its substrate recognition.

Evaluation of a near-infrared-type contrast medium extravasation detection system using a swine model.

PURPOSE: To refine the development and evaluate the near-infrared (NIR) extravasation detection system and its ability to detect extravasation during a contrast-enhanced computed tomography (CT) examination. MATERIALS AND METHODS: The NIR extravasation detection system projects the NIR light through the surface of the human skin then, using its sensory system, will monitor the changes in the amount of NIR that reflected, which varies based on absorption properties.Seven female pigs were used to evaluate the contrast media extravasation detection system, using a 20-gauge intravenous catheter, when injected at a rate of 1 mL/s into 4 different locations just under the skin in the thigh section. Using 3-dimensional CT images, we evaluated the extravasations between time and volume, depth and volume, and finally depth and time to detect. RESULTS: We confirmed that the NIR light, 950-nm wavelength, used by the extravasation detection system is well absorbed by contrast media, making changes easy to detect. The average time to detect an extravasation was 2.05 seconds at a depth of 2.0 mm below the skin with a volume of 1.3 mL, 2.57 seconds at a depth between 2.1 and 5 mm below the skin and a volume of 3.47 mL, 10.5 seconds for depths greater than 5.1 mm and a volume of 11.1 mL. The detection accuracy was significantly deteriorated when the depth exceeded 5.0 mm (Tukey-Kramer, P < 0.05) CONCLUSIONS: The extravasation system detection system that is using NIR has a high level of detection sensitivity. The sensitivity enables the system to detect extravasation at depths less than 2 mm with a volume of 1.5 mL and at depths less than 5 mm with a volume of 3.5 mL. The extravasation detection system could be suitable for use during examinations.

A new method to detect air leakage in a patient with pneumothorax using saline solution and multidetector-row spiral CT scan.

BACKGROUND: The purpose of this study was to establish a new CT scan method to show signs of air leakage and to detect the point of the lung leak in patients with spontaneous pneumothorax by using saline solution and phonation. METHODS: Eleven patients with spontaneous pneumothorax who had a chest tube placed and underwent an operation because of continuing air leakage were studied. After a plain chest CT scan was performed, 0.9% saline was injected into the affected pleural cavity. A CT scan was acquired again while the patient vocalized continuously. The CT images were evaluated by two thoracic surgeons. All patients underwent video-assisted thoracoscopic surgery to confirm their points of leakage and were treated for spontaneous pneumothorax. RESULTS: Bubble shadows were seen in nine of 11 cases. In seven of those nine cases, multiple bubbles formed foam or wave shadows. These cases had a small pleural fistula. In the other two cases with a large fistula, air-fluid level in bulla and ground-glass attenuation areas were seen in the pulmonary parenchyma. In all 11 cases, some air-leakage signs were seen on CT scan, and a culprit lesion was presumed to exist by analyzing CT imaging findings and confirming with a surgical air-leak test. CONCLUSIONS: With a saline injection and vocalization, CT scan could demonstrate air-leak signs in patients with spontaneous pneumothorax. This method does not require contrast medium, special instruments, or high skill and, thus, is a novel and useful examination to detect the culprit lesion in pneumothorax.

Estimation of the left ventricular diastolic function with cardiac MDCT: correlation of the slope of the time-enhancement-curve with the mitral annulus diastolic velocity.

Patients with diastolic heart failure tend to have a poor outcome, similar to that for patients with systolic heart failure. The aim of this study was to explore the ability of MDCT to estimate the left ventricular diastolic function. Thirty patients with suspected coronary artery disease underwent MDCT and echocardiography. The early transmitral flow velocities (E) and the velocity of mitral annulus early diastolic motion (e') were measured in order to evaluate the diastolic function. The scanning delay of CT was determined using a test injection technique. The aortic enhancement was measured over the aortic-root lumen, and it was plotted over time to yield a time-enhancement-curve. A gamma variate function was then fit to the time-enhancement-curve and thereafter both the 'slope' of enhancement for each patient and the region of interest [ROI] were calculated. According to a univariate analysis, the slope of the time-enhancement-curve was found to correlate with the e' (r = 0.686, P = 0.000) and E/e' (r = -0.482, P = 0.007), however, no significant correlation was observed with the systolic parameters of the left ventricle. These results indicate that the slope of the time-enhancement-curve in the aorta significantly correlates with e', i.e. the diastolic parameters, which are independent of the systolic parameters. Based on these findings, we propose that the slope of the time-enhancement-curve may serve as a parameter for the left ventricular diastolic function on MDCT.

Physical evaluation of multidetector-row computed tomography (MDCT) scan methods and conditions for improvement of carbon beam distribution.

To reduce errors in the carbon beam distribution between the treatment planning system and the actual situation, we evaluated the geometrical accuracy, volume accuracy, water-equivalent length (WEL), and treatment planning, and compared the results of evaluation of axial and helical scan methods with various scan parameters. The results indicated that both scan methods showed good geometrical accuracy for thin slice images, but for thick slice images it is easier to understand the phantom as a sphere from the helical as compared with the axial scan. Treatment planning with a thin slice thickness (ST) provided accurate dose distribution for both scan methods, and the dose distribution on the treatment planning system was almost the same as that in the actual situation. Not all institutes, however, can obtain thin slice CT images, and some have used thick slice CT images in planning. For the axial scan, such thick slice images induced differences in dose distribution between treatment planning and the actual situation. Helical scans with a small, reconstructed increment reduced these differences even with relatively thick CT images. To achieve a more accurate dose distribution, radiation therapy planning should be performed using a thin ST for both scan methods or the helical scan with a small, reconstructed increment. Although we reached this conclusion using a carbon beam, it also may be applicable to proton beam therapy.