Submilisievert ultralow-dose CT colonography using iterative reconstruction technique: a feasibility study.

BACKGROUND: Computed tomography (CT) colonography is a well established modality for the examination of symptomatic patients as well as in screening. Recent technical advances in improving image quality by iterative reconstruction contribute to the reduction of the radiation dose which is a major concern in CT imaging. PURPOSE: To evaluate image quality of ultralow-dose submilisievert CT colonography using hybrid iterative reconstruction technique. MATERIAL AND METHODS: Sixteen patients underwent contrast-enhanced CT colonography with standard protocol in supine position and ultralow-dose protocol in prone position. Ultralow-dose datasets were reconstructed with filtered back projection and an advanced hybrid iterative reconstruction technique. Two radiologists independently evaluated 96 colonic segments for image quality in the endoluminal view and axial thin sections. Colonic distension, smoothness of colonic wall and distortion of folds in the endoluminal view, sharpness of colonic wall delineation, perceived image noise, and presence of photon starvation artifact were rated on a five-point scale. Intraluminal noise expressed as standard deviation of Hounsfield density was measured in all segments. RESULTS: The mean radiation dose was 0.42 mSv and 5.48 mSv in prone and supine scans, respectively. All distended segments were rated evaluable in standard dose and ultralow-dose series reconstructed with the iterative reconstruction technique, whereas in 61% segments image quality was rated poor or unacceptable in ultralow-dose series where filtered back projection was used with worst ratings in the rectum and the sigmoid colon. CONCLUSION: This pilot study shows that iterative reconstruction technique is a feasible method to decrease the radiation dose from CT colonography for both positions below 1mSv. Further investigations of larger scale need to be done to clarify, whether such a low radiation dose would influence the detection of polyps.

Deep-learning-based reconstruction of T2-weighted magnetic resonance imaging of the prostate accelerated by compressed sensing provides improved image quality at half the acquisition time.

Background: Deep-learning-based reconstruction (DLR) improves the quality of magnetic resonance (MR) images which allows faster acquisitions. The aim of this study was to compare the image quality of standard and accelerated T2 weighted turbo-spin-echo (TSE) images of the prostate reconstructed with and without DLR and to find associations between perceived image quality and calculated image characteristics. Methods: In a cohort of 47 prospectively enrolled consecutive patients referred for bi-parametric prostate magnetic resonance imaging (MRI), two T2-TSE acquisitions in the transverse plane were acquired on a 3T scanner-a standard T2-TSE sequence and a short sequence accelerated by a factor of two using compressed sensing (CS). The images were reconstructed with and without DLR in super-resolution mode. The image quality was rated in six domains. Signal-to-noise ratio (SNR), and image sharpness were measured. Results: The mean acquisition time was 281±23 s for the standard and 140±12 s for the short acquisition (P<0.0001). DLR images had higher sharpness compared to non-DLR (P<0.001). Short and short-DLR had lower SNR than the standard and standard-DLR (P<0.001). The perceived image quality of short-DLR was rated better in all categories compared to the standard sequence (P<0.001 to P=0.004). All domains of subjective evaluation were correlated with measured image sharpness (P<0.001). Conclusions: T2-TSE acquisition of the prostate accelerated using CS combined with DLR reconstruction provides images with increased sharpness that have a superior quality as perceived by human readers compared to standard T2-TSE. The perceived image quality is correlated with measured image contrast.

Can pyrolysis and composting of sewage sludge reduce the release of traditional and emerging pollutants in agricultural soils? Insights from field and laboratory investigations.

The potential extractability, crop uptake, and ecotoxicity of conventional and emerging organic and metal(loid) contaminants after the application of pre-treated (composted and pyrolysed) sewage sludges to two agricultural soils were evaluated at field and laboratory scale. Metal(loid) extractability varied with sludge types and pre-treatments, though As, Cu, and Ni decreased universally. In the field, the equivalent of 5 tons per hectare of both composted and pyrolysed sludges brought winter wheat grain metal(loid) concentrations below statutory limits. Carbamazepine, diclofenac, and telmisartan were the only detected organic pollutants in crops decreasing in order of root > shoot > grains, whilst endocrine-disrupting chemicals, such as bisphenol A and perfluorochemicals were heavily reduced by composting (up to 71%) or pyrolysis (up to below detection limit) compared to raw sludges. As a consequence, no detectable concentrations were measured in soils 12 months after field application. This study highlights the potential advantages of processing sewage sludge before soil applications, especially in the context of reducing the mobility of emerging contaminants, though further studies are required on a broad range of soils and crops before land application can be considered.

Reduced Radiation Exposure Protocol during Computer Tomography of the Left Atrium Prior to Catheter Ablation in Patients with Atrial Fibrillation.

(1) Background: Computer tomography (CT) is an imaging modality used in the pre-planning of radiofrequency catheter ablation (RFA) procedure in patients with cardiac arrhythmias. However, it is associated with a considerable ionizing radiation dose for patients. This study aims to develop and validate low-dose CT scanning protocols of the left atrium (LA) for RFA guidance. (2) Methods: 68 patients scheduled for RFA of atrial fibrillation were sequentially assigned to four groups of ECG-gated scanning protocols, based on the set tube current (TC): Group A (n = 20, TC = 33 mAs), Group B (n = 18, TC = 67 mAs), Group C (n = 10, TC = 135 mAs), and control Group D (n = 20, TC = 600 mAs). We used a 256-row multidetector CT with body weight-dependent tube voltage of 80 kVp (<70 kg), 100 kVp (70−90 kg), and 120 kVp (>90 kg). We evaluated scanning parameters including radiation dose, total scanning procedure time and signal-to-noise ratio (SNR). (3) Results: The average effective radiation dose (ED) was lower in Group A in comparison to Group B, C and D (0.83 (0.76−1.10), 1.55 (1.36−1.67), 2.91 (2.32−2.96) and 9.35 (8.00−10.04) mSv, p < 0.05). The total amount of contrast media was not significantly different between groups. The mean SNR was 6.5 (5.8−7.3), 7.1 (5.7−8.2), 10.8 (10.1−11.3), and 12.2 (9.9−15.7) for Group A, B, C and D, respectively. The comparisons of SNR in group A vs. B and C vs. D were without significant differences. (4) Conclusions: Optimized pre-ablation CT scanning protocols of the LA can reduce an average ED by 88.7%. Three dimensional (3D) models created with the lowest radiation protocol are useful for the integration of electro-anatomic-guided RFA procedures.

Learning-based vertebra localization and labeling in 3D CT data of possibly incomplete and pathological spines.

BACKGROUND AND OBJECTIVE: We present a fully automatic system based on learning approaches, which aims to localization and identification (labeling) of vertebrae in 3D computed tomography (CT) scans of possibly incomplete spines in patients with bone metastases and vertebral compressions. METHODS: The framework combines a set of 3D algorithms for i) spine detection using a convolution neural network (CNN) ii) spinal cord tracking based on combination of a CNN and a novel growing sphere method with a population optimization, iii) intervertebral discs localization using a novel approach of spatially variant filtering of intensity profiles and iv) vertebra labeling using a CNN-based classification combined with global dynamic optimization. RESULTS: The proposed algorithm has been validated in testing databases, including also a publicly available dataset. The mean error of intervertebral discs localization is 4.4 mm, and for vertebra labeling, the average rate of correctly identified vertebrae is 87.1%, which can be considered a good result with respect to the large share of highly distorted spines and incomplete spine scans. CONCLUSIONS: The proposed framework, which combines several advanced methods including also three CNNs, works fully automatically even with incomplete spine scans and with distorted pathological cases. The achieved results allow including the presented algorithms as the first phase to the fully automated computer-aided diagnosis (CAD) system for automatic spine-bone lesion analysis in oncological patients.

Stability and stabilizing efficiency of Mg-Fe layered double hydroxides and mixed oxides in aqueous solutions and soils with elevated As(V), Pb(II) and Zn(II) contents.

Although the mechanisms of metal(loid) removal from aqueous solutions using LDHs (layered double hydroxides) and mixed oxides (thermally treated LDHs; CLDHs) have been studied, research dealing with their stability, stabilizing efficiency and remediation potential for contaminated soils remains scarce. We present a complex study investigating the stabilizing efficiency of Mg-Fe LDHs and CLDHs at different conditions, including aqueous solutions and real soils with highly elevated As(V), Pb(II) and Zn(II) concentrations. All studied materials showed excellent (ad)sorption efficiency for As(V), Pb(II) and Zn(II) in aqueous solutions. Additionally, the reconstruction ability of CLDHs at different conditions that could improve their adsorption properties was also evaluated, and the dependence on time, pH and the concentrations of metal(loid)s was shown. In general, CLDHs showed higher stability and stabilizing efficiency in aqueous and soil solutions; however, LDHs were more efficient in contaminated soils. Furthermore, solid state analyses coupled with geochemical modeling showed the formation of new phases corresponding to Mg­carbonates/silicates on the surfaces of LDH/CLDH after their incubation in soils. Both LDHs and CLDHs significantly decreased the bioavailable/labile fraction of As(V) and Zn(II) in the studied soils. In general, our work shows Mg-Fe LDHs and CLDHs as prospective materials for water and soil remediation.

Deep-learning-based fully automatic spine centerline detection in CT data.

In this contribution, we present a fully automatic approach, that is based on two convolution neural networks (CNN) together with a spine tracing algorithm utilizing a population optimization algorithm. Based on the evaluation of 130 CT scans including heavily distorted and complicated cases, it turned out that this new combination enables fast and robust detection with almost 90% of correctly determined spinal centerlines with computing time of fewer than 20 seconds.

Synthesis of modified amorphous manganese oxide using low-cost sugars and biochars: Material characterization and metal(loid) sorption properties.

In this study, amorphous Mn oxides (AMOs) and their composites with biochar (BC) were synthesized using different sugars (glucose, sucrose, and molasses), and their sorption efficiency toward Zn(II), Cd(II), and As(V) was tested. Additionally, detailed characterization of synthesized materials using various solid-state analysis methods (e.g. XRD, FTIR-ATR, and/or SEM-EDX) was also performed. Despite glucose-based AMOs presented higher sorption efficiency for As(V), i.e., 0.73 mmol g-1 (glucose) > 0.27 mmol g-1 (sucrose and molasses), similar sorption efficiency toward Zn(II), i.e., 0.80 mmol g-1 (glucose and molasses) > 0.66 (sucrose) and Cd(II) (0.71-0.74 mmol g-1 (sucrose and molasses) > 0.36 mmol g-1 (glucose), was observed for sucrose- and molasses-based AMOs under the given conditions. Next, the sorption efficiency of all AMO/BC composites was proportional to their AMO content. Finally, Mn(II) leaching from the structure of the new AMOs was negligible compared to that observed for the glucose-based AMOs, in this study as well as in other similar studies. Moreover, using molasses as reducing agent during AMO synthesis dramatically decreased the total cost of the final materials, which suggested that these new AMOs could represent interesting alternatives for standard remediation technologies. The AMOs synthesized using low-cost sugars could, therefore, be promising materials for real field applications, since the main disadvantages of using standard AMOs are mitigated. Nevertheless, the efficiency and stability of these composites under real-life conditions must be tested prior to their direct application for remediation technologies.

Iterative machine learning based rotational alignment of brain 3D CT data.

The optimal rotational alignment of brain Computed Tomography (CT) images to a required standard position has a crucial importance for both automatic and manual diagnostic analysis. In this contribution, we present a novel two-step iterative approach for the automatic 3D rotational alignment of brain CT data. The angles of axial and coronal rotations are determined by an unsupervised by localisation of the Midsagittal Plane (MSP) method. This includes detection and pairing of medially symmetrical feature points. The sagittal rotation angle is subsequently estimated by regression convolutional neural network (CNN). The proposed methodology has been evaluated on a dataset of CT data manually aligned by radiologists. It has been shown that the algorithm achieved the low error of estimated rotations (≈1 degree) and in a significantly shorter time than the experts (≈2 minutes per case).

Deep convolutional neural network-based segmentation and classification of difficult to define metastatic spinal lesions in 3D CT data.

This paper aims to address the segmentation and classification of lytic and sclerotic metastatic lesions that are difficult to define by using spinal 3D Computed Tomography (CT) images obtained from highly pathologically affected cases. As the lesions are ill-defined and consequently it is difficult to find relevant image features that would enable detection and classification of lesions by classical methods of texture and shape analysis, the problem is solved by automatic feature extraction provided by a deep Convolutional Neural Network (CNN). Our main contributions are: (i) individual CNN architecture, and pre-processing steps that are dependent on a patient data and a scan protocol - it enables work with different types of CT scans; (ii) medial axis transform (MAT) post-processing for shape simplification of segmented lesion candidates with Random Forest (RF) based meta-analysis; and (iii) usability of the proposed method on whole-spine CTs (cervical, thoracic, lumbar), which is not treated in other published methods (they work with thoracolumbar segments of spine only). Our proposed method has been tested on our own dataset annotated by two mutually independent radiologists and has been compared to other published methods. This work is part of the ongoing complex project dealing with spine analysis and spine lesion longitudinal studies.

AMOchar: Amorphous manganese oxide coating of biochar improves its efficiency at removing metal(loid)s from aqueous solutions.

A novel sorbent made from biochar modified with an amorphous Mn oxide (AMOchar) was compared with pure biochar, pure AMO, AMO+biochar mixtures and biochar+birnessite composite for the removal of various metal(loid)s from aqueous solutions using adsorption and solid-state analyses. In comparison with the pristine biochar, both Mn oxide-biochar composites were able to remove significantly greater quantities of various metal(loid)s from the aqueous solutions, especially at a ratio 2:1 (AMO:biochar). The AMOchar proved most efficient, removing almost 99, 91 and 51% of Pb, As and Cd, respectively. Additionally, AMOchar and AMO+biochar mixture exhibited reduced Mn leaching, compared to pure AMO. Therefore, it is concluded that the synthesis of AMO and biochar is able to produce a double acting sorbent ('dorbent') of enhanced efficiency, compared with the individual deployment of their component materials.

Whole-body low-dose computed tomography in multiple myeloma staging: Superior diagnostic performance in the detection of bone lesions, vertebral compression fractures, rib fractures and extraskeletal findings compared to radiography with similar radiation exposure.

The primary objective of the present prospective study was to compare the diagnostic performance of conventional radiography (CR) and whole-body low-dose computed tomography (WBLDCT) with a comparable radiation dose reconstructed using hybrid iterative reconstruction technique, in terms of the detection of bone lesions, skeletal fractures, vertebral compressions and extraskeletal findings. The secondary objective was to evaluate lesion attenuation in relation to its size. A total of 74 patients underwent same-day skeletal survey by CR and WBLDCT. In CR and WBLDCT, two readers assessed the number of osteolytic lesions at each region and stage according to the International Myeloma Working Group (IMWG) criteria. A single reader additionally assessed extraskeletal findings and their significance, the number of vertebral compressions and bone fractures. The radiation exposure was 2.7±0.9 mSv for WBLDCT and 2.5±0.9 mSv for CR (P=0.054). CR detected bone involvement in 127 out of 486 regions (26%; P<0.0001), confirmed by WBLDCT. CR underestimated the disease stage in 16% and overestimated it in 8% of the patients (P=0.0077). WBLDCT detected more rib fractures compared with CR (188 vs. 47; P<0.0001), vertebral compressions (93 vs. 67; P=0.010) and extraskeletal findings (194 vs. 52; P<0.0001). There was no correlation observed between lesion size (≥5 mm) and its attenuation (r=-0.006; P=0.93). The inter-observer agreement for the presence of osteolytic lesions was κ=0.76 for WBLDCT, and κ=0.55 for CR. The present study concluded that WBLDCT with hybrid iterative reconstruction technique demonstrates superiority to CR with an identical radiation dose in the detection of bone lesions, skeletal fractures, vertebral compressions and extraskeletal findings, which results in up- or downstaging in 24% patients according to the IMWG criteria. The attenuation of osteolytic lesions can be measured with the avoidance of the partial volume effect.

Sub-milliSievert ultralow-dose CT colonography with iterative model reconstruction technique.

Purpose. The purpose of this study was to evaluate the technical and diagnostic performance of sub-milliSievert ultralow-dose (ULD) CT colonograpy (CTC) in the detection of colonic and extracolonic lesions. Materials and Methods. CTC with standard dose (SD) and ULD acquisitions of 64 matched patients, half of them with colonic findings, were reconstructed with filtered back projection (FBP), hybrid (HIR) and iterative model reconstruction techniques (IMR). Image noise in six colonic segments, in the left psoas muscle and aorta were measured. Image quality of the left adrenal gland and of the colon in the endoscopic and 2D view was rated on a five point Likert scale by two observers, who also completed the reading of CTC for colonic and extracolonic findings. Results. The mean radiation dose estimate was 4.1 ± 1.4 mSv for SD and 0.86 ± 0.17 mSv for ULD for both positions (p < 0.0001). In ULD-IMR, SD-IMR and SD-HIR, the endoluminal noise was decreased in all colonic segments compared to SD-FBP (p < 0.001). There were 27 small (6-9 mm) and 17 large (≥10 mm) colonic lesions that were classified as sessile polyps (n = 38), flat lesions (n = 3), or as a mass (n = 3). Per patient sensitivity and specificity were 0.82 and 0.93 for ULD-FBP, 0.97 and 0.97 for ULD-HIR, 0.97 and 1.0 for ULD-IMR. Per polyp sensitivity was 0.84 for ULD-FBP, 0.98 for ULD-HIR, 0.98 for ULD-IMR. Significantly less extracolonic findings were detected in ULD-FBP and ULD-HIR, but in the E4 category by C-RADS (potentially important findings), the detection was similar. Conclusion. Both HIR and IMR are suitable for sub-milliSievert ULD CTC without sacrificing diagnostic performance of the study.

Novel registration-based framework for CT angiography in lower legs.

Proper subtraction and visualization of contrast-enhanced blood vessels in lower extremities using computed tomography angiography (CTA) is based on precise masking of all non-contrasted structures in the area, and it is the main prerequisite for correct diagnosis and decision on treatment for peripheral arterial occlusive disease (PAOD). Because of possible motion of patients during the CTA examination, precise elimination of non-contrasted tissues, including bones, calcifications, and soft tissue, is still very challenging for lower legs, that is, from knees to toes. We propose novel registration-based framework for detection and correction of the motion in lower legs, which typically occurs between and during CTA pre-contrast and post-contrast acquisitions. Within the framework, two registration cores are proposed as alternatives, and resulting CTA subtraction images are compared with Advanced Vessel Analysis considered one of the reference commercial tools among clinical applications for CTA of lower extremities. The CTA subtraction images of 55 patients examined for PAOD are evaluated visually by four expert observers on the Philips Extended Brilliance Workspace using four criteria assessing the overall robustness of tested methods. According to the complex evaluation, the proposed framework enabled valuable improvements of CTA examination of lower legs.

Phantom-less QCT BMD system as screening tool for osteoporosis without additional radiation.

PURPOSE: Phantom-less bone mineral density (PLBMD) systems are easily integrated into the CT workflow for non-dedicated Quantitative CT (QCT) BMD measurements in thoracic and abdominal scans. This in vivo retrospective study aims to determine accuracy and precision of the PLBMD option located on the Extended Brilliance Workspace (Philips Medical Systems, Cleveland, OH, US) from both cross-sectional and longitudinal image data. MATERIALS AND METHODS: The cross-sectional comparison with phantom-based QCT BMD was performed for 82 patients (61 female, 21 male) with a mean age of (63.0±11.8 SD) years on 197 vertebrae. This was followed by an interobserver variability analysis on 71 vertebrae. The longitudinal PLBMD study was carried out on 45 vertebrae from 10 patients (5 female, 5 male) with a mean age of (64.4±11.5 SD) years. They were re-scanned with standardized scan and contrast-injection protocols within a mean and median of (33±41 SD) and 8 days, respectively. All CT scans were acquired on an Mx8000 Quad (Philips) at Florence-Nightingale Hospital, Kaiserswerth, Germany, in a spiral acquisition mode. RESULTS: A negligible BMD bias of -0.9mg/cm(3) for the PLBMD option was observed with respect to phantom-based QCT BMD. Applying CT number matching of muscle and fat ROIs, the analysis of cross-sectional interobserver and of longitudinal variability yielded precision values of 3.1mg/cm(3) (CV%=4.0) and 4.2mg/cm(3) (CV%=5.3), respectively. CONCLUSION: Although the precision is inferior to phantom-based BMD systems, PLBMD is a robust clinical utility for the detection of lowered BMD in a large patient population. This can be achieved without additional radiation exposure from non-contrasted CT scans, to perform an ancillary diagnosis of osteopenia or osteoporosis.

Improved disparity based image processing in 3D CT subtractive angiography.

The paper describes a set of approaches and routines designed to improve results in CT based 3D subtractive angiography of lower extremities via better global locally defined image data registration. Starting from the generic concept of 3D disparity-based flexible registration, modifications of this idea are made founded on prior anatomical knowledge, as segmentation into individual bone areas, their rigid registration followed by constrained flexible registration, and flexible registration of soft tissue volumes. After final subtraction, fusion of the individually derived volumes into the full volume of extremities provides the medically assessable results. The level of detail in minor vessels, and continuity of vessels including those in direct contact with the bones, have been found much better clinically than those achieved by standard contemporary commercial software.

Evaluation of left atrial function by multidetector computed tomography before left atrial radiofrequency-catheter ablation: comparison of a manual and automated 3D volume segmentation method.

INTRODUCTION: The purpose of this study was to compare a manual and automated 3D volume segmentation tool for evaluation of left atrial (LA) function by 64-slice multidetector-CT (MDCT). METHODS AND MATERIALS: In 33 patients with paroxysmal atrial fibrillation a MDCT scan was performed before radiofrequency-catheter ablation. Atrial function (minimal volume (LAmin), maximal volume (LAmax), stroke volume (SV), ejection fraction (EF)) was evaluated by two readers using a manual and an automatic tool and measurement time was evaluated. RESULTS: Automated LA volume segmentation failed in one patient due to low LA enhancement (103HU). Mean LAmax, LAmin, SV and EF were 127.7 ml, 93 ml, 34.7 ml, 27.1% by the automated, and 122.7 ml, 89.9 ml, 32.8 ml, 26.3% by the manual method with no significant difference (p>0.05) and high Pearsons correlation coefficients (r=0.94, r=0.94, r=0.82 and r=0.85, p<0.0001), respectively. The automated method was significantly faster (p<0.001). Interobserver variability was low for both methods with Pearson's correlation coefficients between 0.98 and 0.99 (p<0.0001). CONCLUSIONS: Evaluation of LA volume and function with 64-slice MDCT is feasible with a very low interobserver variability. The automatic method is as accurate as the manual method but significantly less time consuming permitting a routine use in clinical practice before RF-catheter ablation.