Approach to anaerobic bio-degradation of natural and synthetic fabrics: Physico-chemical study of the alteration processes.

In this paper, the mesophilic Biochemical Methane Potential of several fabrics was assessed at different Total Solid concentrations (1-4%TS). Physico-chemical techniques were applied to explore the arising structural changes on fibers during the anaerobic digestion process. Additionally, the modified Gompertz model was used to assess and compare the AD performance of the fabrics. In cellulose-based fibers the production of biogas was enhanced thanks to the easy solubilization of acetate, which is generated upon partial breakage of cellulose bonds. The crystallinity of vegetal fibers decreased significantly from day 19. The highest methane yields were attained for silk and wool fabrics at the lowest TS concentrations. Conformational changes in fibroin and keratin were detected. The highest degrees of degradation were observed in solid samples with lower solid concentrations. Accordingly, the maximum methane yields were reported in the reactors operating with lower TS.

PIMA-CT: Physical Model-Aware Cyclic Simulation and Denoising for Ultra-Low-Dose CT Restoration.

A body of studies has proposed to obtain high-quality images from low-dose and noisy Computed Tomography (CT) scans for radiation reduction. However, these studies are designed for population-level data without considering the variation in CT devices and individuals, limiting the current approaches' performance, especially for ultra-low-dose CT imaging. Here, we proposed PIMA-CT, a physical anthropomorphic phantom model integrating an unsupervised learning framework, using a novel deep learning technique called Cyclic Simulation and Denoising (CSD), to address these limitations. We first acquired paired low-dose and standard-dose CT scans of the phantom and then developed two generative neural networks: noise simulator and denoiser. The simulator extracts real low-dose noise and tissue features from two separate image spaces (e.g., low-dose phantom model scans and standard-dose patient scans) into a unified feature space. Meanwhile, the denoiser provides feedback to the simulator on the quality of the generated noise. In this way, the simulator and denoiser cyclically interact to optimize network learning and ease the denoiser to simultaneously remove noise and restore tissue features. We thoroughly evaluate our method for removing both real low-dose noise and Gaussian simulated low-dose noise. The results show that CSD outperforms one of the state-of-the-art denoising algorithms without using any labeled data (actual patients' low-dose CT scans) nor simulated low-dose CT scans. This study may shed light on incorporating physical models in medical imaging, especially for ultra-low level dose CT scans restoration.

Comparison of CT image quality between the AIDR 3D and FIRST iterative reconstruction algorithms: an assessment based on phantom measurements and clinical images.

Modern CT iterative reconstruction algorithms are transitioning from a statistical-based to model-based approach. However, increasing complexity does not ensure improved image quality for all indications, and thorough characterization of new algorithms is important to understand their potential clinical impacts. This study performs both quantitative and qualitative analyses of image quality to compare Canon's statistical-based Adaptive Iterative Dose Reduction 3D (AIDR 3D) algorithm to its model-based algorithm, Forward-projected model-based Iterative Reconstruction SoluTion(FIRST). A phantom was used to measure the task-specific modulation transfer function (MTFTask), the noise power spectrum (NPS), and the low-contrast object-specific CNR (CNRLO) for each algorithm using three dose levels and the convolution algorithm (kernel) appropriate for abdomen, lung, and brain imaging. Additionally, MTFTaskwas measured at four contrast levels, and CNRLOwas measured for two object sizes. Lastly, three radiologists participated in a preference study to compare clinical image quality for three study types: non-contrast abdomen, pulmonary embolism (PE), and lung screening. Nine questions related to the appearance of anatomical features or image quality characteristics were scored for twenty exams of each type. The behavior of both algorithms depended strongly on the kernel selected. Phantom measurements suggest that FIRST should be beneficial over AIDR 3D for abdomen imaging, but do not suggest a clear overall benefit to FIRST for lung or brain imaging; metrics suggest performance may be equivalent to or slightly favor AIDR 3D, depending on the size of the object being imaged and whether spatial resolution or low-contrast resolution is more important for the task at hand. Overall, radiologists strongly preferred AIDR 3D for lung screening, slightly preferred AIDR 3D for non-contrast abdomen, and had no preference for PE. FIRST was superior for the reduction of metal artifacts. Radiologist preference may be influenced by changes to noise texture.

Accuracy and reproducibility of effective atomic number and electron density measurements from sequential dual energy CT.

PURPOSE: This study assesses the accuracy of effective atomic number (Zeff ) and electron density measurements acquired from dual energy CT and characterizes the response to clinically relevant variables representative of challenges in patient imaging, including: phantom size, material position within the phantom, variation over time, off-center positioning, and large cone beam angle. METHODS: The Gammex Multi-Energy CT head and body phantoms were used to measure Zeff and electron density from 35 rod inserts that mimic tissues and varying concentrations of iodine and calcium. Scans were performed on a Canon Aquilion ONE Genesis CT scanner over a period of 6 months using default dual energy protocols appropriate for each phantom size. Theoretical Zeff and electron density values were calculated using data provided by the phantom manufacturer and compared to the measurements. Sources of variance were separated and quantified to identify the influences of random photon statistics, ROI placement, and variation over time. A subset of measurements were repeated with the phantom shifted in the vertical and horizontal directions, and over all slices in the volumetric scan. RESULTS: All measurements showed strong correlation (r > 0.98) with their corresponding theoretical values; however, the system did demonstrate a bias of -0.58 atomic units in the body phantom and 0.28 atomic units in the head phantom for Zeff measurements. The mean absolute percent error (MAPE) was 6.3% for the body phantom and 3.2% for the head phantom. Electron density measurements of the body and head phantoms gave MAPE values of 4.6% and 1.0%, respectively. Zeff and electron density measurements significantly varied within the solid water background, showing a positional dependence within the phantom that dominated the total standard deviation in measurements. Zeff values dropped by 0.2 atomic units when the phantom was off-center; electron density measurements were less affected by phantom position. Along the z-axis, the accuracy drops off markedly at more than 50-60 mm from the central slice. CONCLUSION: The Canon dual energy system offers an accurate way of measuring the Zeff and electron density of clinically relevant materials. Accuracy could be improved further by calibration to remove bias, careful attention to centering within the FOV, and avoiding measurements at the edges of the cone beam.

Comparison of metal artifact reduction using single-energy CT and dual-energy CT with various metallic implants in cadavers.

OBJECTIVES: The purpose of this study was to compare the effectiveness of metal artifact reduction using Single Energy Metal Artifact Reduction (SEMAR) and Dual Energy CT (DECT). MATERIALS AND METHODS: Six cadavers containing metal implants in the head, neck, abdomen, pelvis, and extremities were scanned with Standard, SEMAR, and DECT protocols on a 320-slice CT scanner. Four specialized radiologists blinded to acquisition methods rated severity of metal artifacts, visualization of anatomic structures, diagnostic interpretation, and image preference with a 5-point grading scale. RESULTS: Scores were significantly better for SEMAR than Standard images in the hip, knee, pelvis, abdomen, and maxillofacial scans (3.25 ±â€¯0.88 versus 2.14 ±â€¯0.93, p < 0.001). However, new reconstruction artifacts developed in SEMAR images that were not present in Standard images. Scores for severity of metal artifacts and visualization of smooth structures were significantly better for DECT than Standard images in the cervical spine (3.50±0.50 versus 2.0±0.58, p < 0.001) and was preferred over Standard images by one radiologist. In all other cases, radiologists preferred the Standard image over the DECT image due to increased image noise and reduced low-contrast resolution with DECT. In all cases, SEMAR was preferred over Standard and DECT images. CONCLUSION: SEMAR was more effective at reducing metal artifacts than DECT. Radiologists should be aware of new artifacts and review both the original and SEMAR images. When the anatomy or implant is relatively small, DECT may be superior to SEMAR without additional artifacts. However, radiologist should be aware of a reduction in soft tissue contrast.

Patient size matters: Effect of tube current modulation on size-specific dose estimates (SSDE) and image quality in low-dose lung cancer screening CT.

PURPOSE: We compare the effect of tube current modulation (TCM) and fixed tube current (FTC) on size-specific dose estimates (SSDE) and image quality in lung cancer screening with low-dose CT (LDCT) for patients of all sizes. METHODS: Initially, 107 lung screening examinations were performed using FTC, which satisfied the Centers for Medicare & Medicaid Services' volumetric CT dose index (CTDIvol ) limit of 3.0 mGy for standard-sized patients. Following protocol modification, 287 examinations were performed using TCM. Patient size and examination parameters were collected and water-equivalent diameter (Dw ) and SSDE were determined for each patient. Regression models were used to correlate CTDIvol and SSDE with Dw . Objective and subjective image quality were measured in 20 patients who had consecutive annual screenings with both FTC and TCM. RESULTS: CTDIvol was 2.3 mGy for all FTC scans and increased exponentially with Dw (range = 0.96-4.50 mGy, R2  = 0.73) for TCM scans. As patient Dw increased, SSDE decreased for FTC examinations (R2  = 1) and increased for TCM examinations (R2  = 0.54). Image quality measurements were superior with FTC for smaller sized patients and with TCM for larger sized patients (R2  > 0.5, P < 0.005). Radiologist graded all images acceptable for diagnostic evaluation of lung cancer screening. CONCLUSION: Although FTC protocol offered a consistently low CTDIvol for all patients, it yielded unnecessarily high SSDE for small patients and increased image noise for large patients. Lung cancer screening with LDCT using TCM produces radiation doses that are appropriately reduced for small patients and increased for large patients with diagnostic image quality for all patients.

Impact of patient centering in CT on organ dose and the effect of using a positioning compensation system: Evidence from OSLD measurements in postmortem subjects.

The purpose of this study was to investigate the frequency and impact of vertical mis-centering on organ doses in computed tomography (CT) exams and evaluate the effect of a commercially available positioning compensation system (PCS). Mis-centering frequency and magnitude was retrospectively measured in 300 patients examined with chest-abdomen-pelvis CT. Organ doses were measured in three postmortem subjects scanned on a CT scanner at nine different vertical table positions (maximum shift ± 4 cm). Organ doses were measured with optically stimulated luminescent dosimeters inserted within organs. Regression analysis was performed to determine the correlation between organ doses and mis-centering. Methods were repeated using a PCS that automatically detects the table offset to adjust tube current output accordingly. Clinical mis-centering was >1 cm in 53% and 21% of patients in the vertical and lateral directions, respectively. The 1-cm table shifts resulted in organ dose differences up to 8%, while 4-cm shifts resulted in organ dose differences up to 35%. Organ doses increased linearly with superior table shifts for the lung, colon, uterus, ovaries, and skin (R2  = 0.73-0.99, P < 0.005). When the PCS was utilized, organ doses decreased with superior table shifts and dose differences were lower (average 5%, maximum 18%) than scans performed without PCS (average 9%, maximum 35%) at all table shifts. Mis-centering occurs frequently in the clinic and has a significant effect on patient dose. While accurate patient positioning remains important for maintaining optimal imaging conditions, a PCS has been shown to reduce the effects of patient mis-centering.