Two-view topogram-based anatomy-guided CT reconstruction for prospective risk minimization.

To facilitate a prospective estimation of the effective dose of an CT scan prior to the actual scanning in order to use sophisticated patient risk minimizing methods, a prospective spatial dose estimation and the known anatomical structures are required. To this end, a CT reconstruction method is required to reconstruct CT volumes from as few projections as possible, i.e. by using the topograms, with anatomical structures as correct as possible. In this work, an optimized CT reconstruction model based on a generative adversarial network (GAN) is proposed. The GAN is trained to reconstruct 3D volumes from an anterior-posterior and a lateral CT projection. To enhance anatomical structures, a pre-trained organ segmentation network and the 3D perceptual loss are applied during the training phase, so that the model can then generate both organ-enhanced CT volume and organ segmentation masks. The proposed method can reconstruct CT volumes with PSNR of 26.49, RMSE of 196.17, and SSIM of 0.64, compared to 26.21, 201.55 and 0.63 using the baseline method. In terms of the anatomical structure, the proposed method effectively enhances the organ shapes and boundaries and allows for a straight-forward identification of the relevant anatomical structures. We note that conventional reconstruction metrics fail to indicate the enhancement of anatomical structures. In addition to such metrics, the evaluation is expanded with assessing the organ segmentation performance. The average organ dice of the proposed method is 0.71 compared with 0.63 for the baseline model, indicating the enhancement of anatomical structures.

Training of a deep learning based digital subtraction angiography method using synthetic data.

BACKGROUND: Digital subtraction angiography (DSA) is a fluoroscopy method primarily used for the diagnosis of cardiovascular diseases (CVDs). Deep learning-based DSA (DDSA) is developed to extract DSA-like images directly from fluoroscopic images, which helps in saving dose while improving image quality. It can also be applied where C-arm or patient motion is present and conventional DSA cannot be applied. However, due to the lack of clinical training data and unavoidable artifacts in DSA targets, current DDSA models still cannot satisfactorily display specific structures, nor can they predict noise-free images. PURPOSE: In this study, we propose a strategy for producing abundant synthetic DSA image pairs in which synthetic DSA targets are free of typical artifacts and noise commonly found in conventional DSA targets for DDSA model training. METHODS: More than 7,000 forward-projected computed tomography (CT) images and more than 25,000 synthetic vascular projection images were employed to create contrast-enhanced fluoroscopic images and corresponding DSA images, which were utilized as DSA image pairs for training of the DDSA networks. The CT projection images and vascular projection images were generated from eight whole-body CT scans and 1,584 3D vascular skeletons, respectively. All vessel skeletons were generated with stochastic Lindenmayer systems. We trained DDSA models on this synthetic dataset and compared them to the trainings on a clinical DSA dataset, which contains nearly 4,000 fluoroscopic x-ray images obtained from different models of C-arms. RESULTS: We evaluated DDSA models on clinical fluoroscopic data of different anatomies, including the leg, abdomen, and heart. The results on leg data showed for different methods that training on synthetic data performed similarly and sometimes outperformed training on clinical data. The results on abdomen and cardiac data demonstrated that models trained on synthetic data were able to extract clearer DSA-like images than conventional DSA and models trained on clinical data. The models trained on synthetic data consistently outperformed their clinical data counterparts, achieving higher scores in the quantitative evaluation of peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) metrics for DDSA images, as well as accuracy, precision, and Dice scores for segmentation of the DDSA images. CONCLUSIONS: We proposed an approach to train DDSA networks with synthetic DSA image pairs and extract DSA-like images from contrast-enhanced x-ray images directly. This is a potential tool to aid in diagnosis.

Computed Tomography 2.0: New Detector Technology, AI, and Other Developments.

ABSTRACT: Computed tomography (CT) dramatically improved the capabilities of diagnostic and interventional radiology. Starting in the early 1970s, this imaging modality is still evolving, although tremendous improvements in scan speed, volume coverage, spatial and soft tissue resolution, as well as dose reduction have been achieved. Tube current modulation, automated exposure control, anatomy-based tube voltage (kV) selection, advanced x-ray beam filtration, and iterative image reconstruction techniques improved image quality and decreased radiation exposure. Cardiac imaging triggered the demand for high temporal resolution, volume acquisition, and high pitch modes with electrocardiogram synchronization. Plaque imaging in cardiac CT as well as lung and bone imaging demand for high spatial resolution. Today, we see a transition of photon-counting detectors from experimental and research prototype setups into commercially available systems integrated in patient care. Moreover, with respect to CT technology and CT image formation, artificial intelligence is increasingly used in patient positioning, protocol adjustment, and image reconstruction, but also in image preprocessing or postprocessing. The aim of this article is to give an overview of the technical specifications of up-to-date available whole-body and dedicated CT systems, as well as hardware and software innovations for CT systems in the near future.

Optimized Camera-Based Patient Positioning in CT: Impact on Radiation Exposure.

OBJECTIVE: The aim of this study was to evaluate whether a 3-dimensional (3D) camera can outperform highly trained technicians in precision of patient positioning and whether this transforms into a reduction in patient exposure. MATERIALS AND METHODS: In a single-center study, 3118 patients underwent computer tomography (CT) scans of the chest and/or abdomen on a latest generation single-source CT scanner supported with an automated patient positioning system by 3D camera. One thousand five hundred fifty-seven patients were positioned laser-guided by a highly trained radiographer (camera off) and 1561 patients with 3D camera (camera on) guidance. Radiation parameters such as effective dose, organ doses, CT dose index, and dose length product were analyzed and compared. Isocenter accuracy and table height were evaluated between the 2 groups. RESULTS: Isocenter positioning was significantly improved with the 3D camera ( P < 0.001) as compared with visual laser-guided positioning. Absolute table height differed significantly ( P < 0.001), being higher with camera positioning (165.6 ± 16.2 mm) as compared with laser-guided positioning (170.0 ± 20.4 mm). Radiation exposure decreased using the 3D camera as indicated by dose length product (321.1 ± 266.6 mGy·cm; camera off: 342.0 ± 280.7 mGy·cm; P = 0.033), effective dose (3.3 ± 2.7 mSv; camera off: 3.5 ± 2.9; P = 0.053), and CT dose index (6.4 ± 4.3 mGy; camera off: 6.8 ± 4.6 mGy; P = 0.011). Exposure of radiation-sensitive organs such as colon ( P = 0.015) and red bone marrow ( P = 0.049) were also lower using the camera. CONCLUSIONS: The introduction of a 3D camera improves patient positioning in the isocenter of the scanner, which results in a lower and also better balanced dose reduction for the patients.

Patient-specific radiation risk-based tube current modulation for diagnostic CT.

PURPOSE: Modern CT scanners use automatic exposure control (AEC) techniques, such as tube current modulation (TCM), to reduce dose delivered to patients while maintaining image quality. In contrast to conventional approaches that minimize the tube current time product of the CT scan, referred to as mAsTCM in the following, we herein propose a new method referred to as riskTCM, which aims at reducing the radiation risk to the patient by taking into account the specific radiation risk of every dose-sensitive organ. METHODS: For current mAsTCM implementations, the mAs product is used as a surrogate for the patient dose. Thus, they do not take into account the varying dose sensitivity of different organs. Our riskTCM framework assumes that a coarse CT reconstruction, an organ segmentation, and an estimation of the dose distribution can be provided in real time, for example, by applying machine learning techniques. Using this information, riskTCM determines a tube current curve that minimizes a patient risk measure, for example, the effective dose, while keeping the image quality constant. We retrospectively applied riskTCM to 20 patients covering all relevant anatomical regions and tube voltages from 70 to 150 kV. The potential reduction of effective dose at same image noise is evaluated as a figure of merit and compared to mAsTCM and to a situation with a constant tube current referred to as noTCM. RESULTS: Anatomical regions like the neck, thorax, abdomen, and the pelvis benefit from the proposed riskTCM. On average, a reduction of effective dose of about 23% for the thorax, 31% for the abdomen, 24% for the pelvis, and 27% for the neck has been evaluated compared to today's state-of-the-art mAsTCM. For the head, the resulting reduction of effective dose is lower, about 13% on average compared to mAsTCM. CONCLUSIONS: With a risk-minimizing TCM, significant higher reduction of effective dose compared to mAs-minimizing TCM is possible.

[Updated S2k AWMF guideline on obstructive sialadenitis]. / Aktualisierte AWMF-S2k-Leitlinie zur obstruktiven Sialadenitis.

The update of this guideline was an important step to define standards for the use of sialendoscopy and other emerging minimally invasive techniques for the therapy of sialolithiasis and other obstructive salivary gland diseases. The current actualization was necessary to adapt the diagnostic and therapeutic algorithms to the current scientific knowledge. In this article they are presented in a shortened version with a focus on conservative therapeutic measures which are especially relevant for daily practice.

Deep learning-based coronary artery motion estimation and compensation for short-scan cardiac CT.

PURPOSE: During a typical cardiac short scan, the heart can move several millimeters. As a result, the corresponding CT reconstructions may be corrupted by motion artifacts. Especially the assessment of small structures, such as the coronary arteries, is potentially impaired by the presence of these artifacts. In order to estimate and compensate for coronary artery motion, this manuscript proposes the deep partial angle-based motion compensation (Deep PAMoCo). METHODS: The basic principle of the Deep PAMoCo relies on the concept of partial angle reconstructions (PARs), that is, it divides the short scan data into several consecutive angular segments and reconstructs them separately. Subsequently, the PARs are deformed according to a motion vector field (MVF) such that they represent the same motion state and summed up to obtain the final motion-compensated reconstruction. However, in contrast to prior work that is based on the same principle, the Deep PAMoCo estimates and applies the MVF via a deep neural network to increase the computational performance as well as the quality of the motion compensated reconstructions. RESULTS: Using simulated data, it could be demonstrated that the Deep PAMoCo is able to remove almost all motion artifacts independent of the contrast, the radius and the motion amplitude of the coronary artery. In any case, the average error of the CT values along the coronary artery is about 25 HU while errors of up to 300 HU can be observed if no correction is applied. Similar results were obtained for clinical cardiac CT scans where the Deep PAMoCo clearly outperforms state-of-the-art coronary artery motion compensation approaches in terms of processing time as well as accuracy. CONCLUSIONS: The Deep PAMoCo provides an efficient approach to increase the diagnostic value of cardiac CT scans even if they are highly corrupted by motion.

Effectiveness of Radiation Protection Caps for Lowering dose to the Brain and the Eye Lenses.

PURPOSE: This work was designed to study the effectiveness of radiation protection caps in lowering the dose to the brain and the eye lens during fluoroscopically guided interventions. MATERIALS AND METHODS: Two types of radiation protection caps were examined with regards to their capacity to lower the radiation dose. One cap is equipped with lateral flaps, the other one is not. These caps were fitted to the head of an anthropomorphic Alderson-Rando (A.-R.) phantom. The phantom was positioned aside an angiographic table simulating the position of the first operator during a peripheral arterial intervention. One of the brain slices and both eyes of the A.-R. phantom were equipped with thermoluminescence dosimeters (TLDs). RESULTS: The analysis of the data showed that the cap without lateral flaps reduced the dose to the brain by 11,5-27,5 percent depending on the position within the brain. The cap with lateral protection flaps achieved a shielding effect between 44,7 and 78,9 percent. When evaluating the dose to the eye, we did see an increase of dose reduction from 63,3 to 66,5 percent in the left eye and from 45,8 to 46,8 percent in the right eye for the cap without lateral protection. When wearing the cap with lateral protection we observed an increase of dose reduction from 63,4 to 67,2 percent in the left eye and from 45,8 to 50,0 percent in the right eye. CONCLUSION: Radiation protection caps can be an effective tool to reduce the dose to the brain and the eyes.

3D-Visualization of Neurovascular Compression at the Ventrolateral Medulla in Patients with Arterial Hypertension.

PURPOSE: Controversy exists on the association of arterial hypertension (HTN) and neurovascular compression (NVC) at the ventrolateral medulla (VLM). No standardized and reproducible technique has been introduced yet for detection of NVC in HTN. This study aimed to generate, analyze and compare different results of exact reproducible anatomical 3D-representations of the VLM in patients with HTN, based on magnetic resonance imaging (MRI). METHODS: A 3T scanner provided MRI (T2-constructive interference in steady state (CISS) high resolution imaging and three-dimensional Time-of-flight (3D-TOF) angiography) from the posterior fossa of 44 patients with clinical treatment-resistant HTN. Image processing consists of segmentation of the CISS data, registration and fusion of the CISS and TOF data and visualization. For each patient two 3D-visualizations (before and after fusion) were obtained. The reproduction quality of the vessels, flow-related signal variability and pulsation artifacts were analyzed and compared, using a ranking score. RESULTS: Integrating vascular information from TOF into CISS data reduced artifacts in 3D-visualizations of exclusively processed CISS data. The quality of 3D-visualization of the vessels near the brain stem was significantly improved (p = 0.004). The results were reproducible and reliable. The quality of the 3D-presentations of neurovascular relationships at the VLM improved significantly (p < 0.001). CONCLUSION: The 3D-visualization of fused image data provides an excellent overview of the relationship between cranial nerves and vessels at the VLM and simplifies the detection of NVC in HTN. It provides a powerful tool for future clinical and scientific research. Although microvascular decompression (MVD) in treatment resistant HTN is not a standard procedure, it can be discussed in selected patients with intractable severe HTN.

High Intensity Resistance Exercise Training vs. High Intensity (Endurance) Interval Training to Fight Cardiometabolic Risk Factors in Overweight Men 30-50 Years Old.

Cardiovascular and cardiometabolic diseases are leading causes of death worldwide. Exercise favorably affects this problem, however only few invest (enough) time to favorably influence cardiometabolic risk-factors and cardiac morphology/performance. Time-effective, high-intensity, low-volume exercise protocols might increase people's commitment to exercise. To date, most research has focused on high-intensity interval training (HIIT), the endurance type of HIT, while corresponding HIT-resistance training protocols (HIT-RT) are rarely evaluated. In this study we compared the effect of HIIT vs. HIT-RT, predominately on cardiometabolic and cardiac parameters in untrained, overweight-obese, middle-aged men. Eligible, untrained men aged 30-50 years old in full-time employment were extracted from two joint exercise studies that randomly assigned participants to a HIIT, HIT-RT or corresponding control group. HIIT predominately consisted of interval training 90 s-12 min, (2-4 sessions/week), HIT-RT (2-3 sessions/week) was applied as a single set resistance training to muscular failure. Core intervention length of both protocols was 16 weeks. Main inclusion criteria were overweight-obese status (BMI 25-35 kg/m2) and full employment (occupational working time: ≥38.5 h/week). Primary study-endpoint was the Metabolic Syndrome (MetS) Z-Score, secondary study-endpoints were ventricular stroke volume index (SVI) and myocardial mass index (MMI) as determined by Magnetic Resonance Imaging. The Intention to treat (ITT) principle was applied to analyze the summarized data set. Twenty-seven eligible men of the HIT-RT and 30 men of the HIIT group were included in the ITT. Both interventions significantly (p < 0.001) improve the MetS Z-Score, however the effect of HIIT was superior (p = 0.049). In parallel, HIT-RT and HIIT significantly affect SVI and MMI, with the effect of HIIT being much more pronounced (p < 0.001). Although HIIT endurance exercise was superior in favorably affecting cardiometabolic risk and particularly cardiac performance, both exercise methods positively affect cardiometabolic risk factors in this overweight to obese, middle-aged cohort of males with low time resources. Thus, the main practical application of our finding might be that in general overweight-obese people can freely choose their preferred exercise type (HIIT-END or HIT-RT) to improve their cardiometabolic health, while investing an amount of time that should be feasible for everybody. Trial Registrations: NCT01406730, NCT01766791.

Diagnostic value of 3D dynamic contrast-enhanced magnetic resonance imaging in lymph node metastases of head and neck tumors: a correlation study with histology.

BACKGROUND: Accurate staging of cervical lymph nodes (LN) is pivotal for further clinical management of patients with head and neck cancer. Functional magnetic resonance imaging (MRI) such as three-dimensional (3D) dynamic contrast-enhanced (DCE) acquisition might improve the diagnosis of cervical LN metastases. PURPOSE: To evaluate the additional diagnostic value of high-resolution 3D T1-weighted DCE in detecting LN metastasis compared to standard morphological imaging criteria in patients with head and neck tumors as correlated to histopathology. MATERIAL AND METHODS: Standard MRI with 3D DCE acquisition at voxel sizes of 1 × 1×1 mm was performed in 15 patients before surgery; 92 LN of the head and neck were histopathologically analyzed. A logistic regression analysis of semi-quantitative DCE parameters, time-intensity curve (TIC) shapes, and morphological criteria was performed to differentiate benign from malignant LN. RESULTS: Standard MRI was sufficient for diagnosis of malignancy in LN with a short-axis diameter ≥ 15 mm (n = 17). For LN metastases with a short-axis diameter <15 mm (n = 12), however, the combination of 3D DCE MRI parameters, TIC shapes, and LN diameter significantly increased the sensitivity and specificity of diagnosing metastases (DCE + TIC shape + LN diameter: 92% and 88% vs. DCE only: 83% and 68% (P < 0.01) vs. LN diameter only: 83% and 77% (P = 0.04). CONCLUSION: MRI including isotropic high-resolution 3D DCE acquisition combined with morphological criteria allows an accurate assessment of small cervical LN metastases in patients with head and neck cancer. For LN ≥ 15 mm diameter, morphologic imaging may suffice to diagnose metastatic disease to the LN.

[Artificial intelligence-based algorithms : Decision-making support for computed tomography of the chest]. / Algorithmen mit künstlicher Intelligenz : Entscheidungsunterstützung für Computertomographien des Thorax.

Artificial intelligence (AI) algorithms are increasingly used in radiology. The main areas of application are, for example, the detection of lung lesions and the diagnosis of chronic obstructive and interstitial lung diseases. The aim of our study was to train and evaluate a package of algorithms that analyze data from computed tomographic (CT) images of the chest and provide quantitative measurements to the radiologist. The following algorithms were trained: lung lesion detection and measurement, lung lobe segmentation, vessel segmentation and measurement, coronary calcium scoring, measurement and density analysis of vertebral bodies. AI-supported algorithms will become part of daily routine of the radiologist in the future. Tasks that do not require medical expertise can be performed by AI. However, our results show that, based on the current accuracy, verification by an experienced radiologist is necessary.

Predictive Value of VIBE using Subtraction to Evaluate Idiopathic Facial Palsy after Starting Therapy.

PURPOSE: To determine the predictive value of 3-dimensional spoiled gradient-echo volumetric interpolated breath-hold examination (VIBE) using subtraction to evaluate the short-term effect of therapy for facial palsy. MATERIALS AND METHODS: We included 97 patients with idiopathic facial palsy (52 male, 45 female; aged 50.7 ±â€Š19.4 years) who underwent MR imaging with a contrast agent after starting therapy. The mean interval between onset and therapy was 1.55 ±â€Š1.69 days, between therapy and MR imaging was 3.19 ±â€Š2.78 days, and between MR imaging and assessment of the therapeutic effect was 3.50 ±â€Š0.71 days. The degree of therapeutic effect was determined using a 4-grade scale based on the House-Brackmann scale for grading facial nerve function. Two radiologists reviewed VIBE with pre- and postcontrast subtraction using the 4-point scale. We evaluated the diagnostic performance and compared the degree of therapeutic effect and enhancement of facial nerves that were divided into 5 segments bilaterally. RESULTS: We identified 98 facial palsy initially and significant enhancement in 55 facial nerves after the start of therapy and residual palsy in 87. Sensitivity for all facial palsy was 62.0 %, specificity was 90.9 %, positive predictive value was 98.2 %, negative predictive value was 23.3 %, and accuracy was 65.3 %. Eleven patients recovered completely, 1 showed significant enhancement, and the remaining 10 did not show significant enhancement of the facial nerve. CONCLUSION: VIBE has a potential to predict the prognostic outcome and assess facial palsy after the start of therapy. KEY POINTS: · Three-dimensional spoiled gradient-echo volumetric interpolated breath-hold examination (VIBE) using subtraction can be useful to predict residual facial palsy after initial therapy.. · Strong enhancement of the facial nerve on VIBE using subtraction was associated with residual facial palsy after the start of therapy.. · Patients with a favorable prognosis did not show strong enhancement.. CITATION FORMAT: · Tomita H, Detmar K, Nakajima Y et al. Predictive Value of VIBE using Subtraction to Evaluate Idiopathic Facial Palsy after Starting Therapy. Fortschr Röntgenstr 2020; 192: 1183 - 1189.

Effects of Conventional Uric Acid-Lowering Therapy on Monosodium Urate Crystal Deposits.

OBJECTIVE: Few studies have systematically and quantitatively addressed the impact of urate-lowering therapy on monosodium urate (MSU) deposits. This study was undertaken to analyze the effect of lifestyle measures and conventional urate-lowering therapy on MSU deposits in patients with gout. METHODS: In this prospective study, subjects with gout according to the American College of Rheumatology/European League Against Rheumatism classification criteria and presence of MSU deposits seen on dual-energy computed tomography (DECT) scans received either lifestyle intervention or conventional urate-lowering therapy for a mean period of 18 months before a follow-up DECT scan. Detected MSU deposits were quantified by volumetric measurement and validated by semiquantitative scoring, and baseline and follow-up measurements were compared. RESULTS: Baseline and follow-up DECT scans were available for all 83 subjects. Six subjects discontinued treatment, and 77 subjects underwent a lifestyle intervention (n = 24) or were treated with allopurinol (n = 29), febuxostat (n = 22), or benzbromarone (n = 2) over the entire observation period. The mean serum uric acid (UA) level decreased from 7.2 to 5.8 mg/dl in the overall population. In patients who discontinued treatment, no change in MSU deposits or serum UA levels was observed. The burden of MSU deposits significantly decreased in patients undergoing lifestyle intervention (MSU volume P = 0.007; MSU score P = 0.001), and in patients treated with allopurinol (MSU volume and score P < 0.001) or febuxostat (MSU volume P < 0.001; MSU score P = 0.001). No significant decline in MSU deposits was noted in patients who discontinued treatment. CONCLUSION: These data show that lifestyle intervention and xanthine oxidase inhibitors significantly decrease the MSU deposit burden. Hence, conventional gout therapy not only lowers serum UA levels, but also reduces pathologic MSU deposits.

Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks.

PURPOSE: Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissues compared to conventional single-energy CT (SECT). Recent research shows that automatic multi-organ segmentation of DECT data can improve DECT clinical applications. However, most segmentation methods are designed for SECT, while DECT has been significantly less pronounced in research. Therefore, a novel approach is required that is able to take full advantage of the extra information provided by DECT. METHODS: In the scope of this work, we proposed four three-dimensional (3D) fully convolutional neural network algorithms for the automatic segmentation of DECT data. We incorporated the extra energy information differently and embedded the fusion of information in each of the network architectures. RESULTS: Quantitative evaluation using 45 thorax/abdomen DECT datasets acquired with a clinical dual-source CT system was investigated. The segmentation of six thoracic and abdominal organs (left and right lungs, liver, spleen, and left and right kidneys) were evaluated using a fivefold cross-validation strategy. In all of the tests, we achieved the best average Dice coefficients of 98% for the right lung, 98% for the left lung, 96% for the liver, 92% for the spleen, 95% for the right kidney, 93% for the left kidney, respectively. The network architectures exploit dual-energy spectra and outperform deep learning for SECT. CONCLUSIONS: The results of the cross-validation show that our methods are feasible and promising. Successful tests on special clinical cases reveal that our methods have high adaptability in the practical application.

Recent and Upcoming Technological Developments in Computed Tomography: High Speed, Low Dose, Deep Learning, Multienergy.

The advent of computed tomography (CT) has revolutionized radiology, and this revolution is still going on. Starting as a pure head scanner, modern CT systems are now able to perform whole-body examinations within a couple of seconds in isotropic resolution, single-rotation whole-organ perfusion, and temporal resolution to fulfill the needs of cardiac CT. Because of the increasing number of CT examinations in all age groups and overall medical-driven radiation exposure, dose reduction remains a hot topic. Although fast gantry rotation, broad detector arrays, and different dual-energy solutions were main topics in the past years, new techniques such as photon counting detectors, powerful x-ray tubes for low-kV scanning, automated image preprocessing, and machine learning algorithms have moved into focus today.The aim of this article is to give an overview of the technical specifications of up-to-date available CT systems and recent hardware and software innovations for CT systems in the near future.

Transhepatic forceps biopsy after PTCD for histological assessment of bile duct stenoses or occlusions.

PURPOSE: The goal of this study was to evaluate the experience of 11 years of wire-guided forceps biopsy via PTCD in patients with obstructive jaundice. MATERIALS AND METHODS: In a retrospective approach, 56 biopsies in 51 patients were analyzed (22 female, 29 male). Data was collected from 2006 to 2016. Mean age was 71 years (range: 34 - 86 years). Data was extracted from dig. Patients' records (KIS, PACS, RIS) to be analyzed in Microsoft Excel. RESULTS: All 56 procedures were technically successful. Stenosis in anastomoses were benign due to scarring in 7 patients and in 9 due to papillitis or others. In 4 patients, results in anastomosis were malignant. In 19 patients without anastomosis, CCC was the diagnosis, thereof 10 klatskin, 9 stenosis in other locations, followed by gastric, pancreatic, and colon carcinoma in 5, 3, and 2 patients. Three patients had a CUP (multimetering in case of more than 1 related category). Overall results were 35 mal. and 16 benign, 76.8 % of all proc. had a correct histopathologic result, and 23.2 % were false negative. Sensitivity was 65.8 %, which results in negative predictive value of 58.1 %. There was no false positive and so specificity was 100 %, as was the positive predictive value. False negative results (no malignancy but clinically and imaging suspect) were corrected by rerunning the procedure, by CT-guided biopsy or by 1 PET-CT. In 1 case the surg. sample brought the result. Minor complications occurred in 8 patients: shivering in 1 case, distinct but hemodynamically not relevant hemobilia in 5 cases, 2 portovenal bleedings. All bleedings were short-term and self-limiting. CONCLUSION: Despite good feasibility, low peri- and post-interv. risk and high validity the forceps biopsy via PTCD is not widely used. For experienced interventionalists, it is an effective method for obtaining histology.

Evaluation of ventricular septal defects using high pitch computed tomography angiography of the chest in children with complex congenital heart defects below one year of age.

BACKGROUND: Aim of this study was to assess the accuracy of ventricular septal defects (VSD) using high pitch computed tomography angiography (CTA) of the chest in children below 1 year of age, compared to the intraoperative findings and echocardiography. METHODS: Out of 154 patients that underwent Dual-Source CTA of the chest using a high-pitch protocol at low tube voltages (70-80 kV), 55 underwent surgical repair of a VSD (median age 8 days, range 1-348 days). The margins of the VSDs and their relation to the surrounding structures were reproduced by en-face views using multiplanar reformations (MPR). Absolute diameter, normalized area and relative area compared to the aortic valve annulus were used for discrimination between restrictive and non-restrictive defects. Localization was classified into four subtypes. The results were compared to two-dimensional echocardiography and intraoperative findings. RESULTS: Median absolute size of VSDs did not differ significantly between CTA-measurements (10.8 mm, range 2.8-18.1 mm) and intraoperative findings (12.0 mm, 3.0-25.0 mm, p = 0.09). Echocardiographic values were significantly lower (9.6 mm, 3.0-18.5 mm, both p < 0.01). The classification of the location and orientation matched the intraoperative situs in 96.4% of all cases using CT and in 87.3% using echocardiography. Echocardiography missed the relation to valves in 11% of all cases. Pre-interventional sensitivity and specificity for detection of a VSD were 97.2/98.9% compared to echocardiography. Median radiation dose was 0.32 mSv (range 0.12-2.00 mSv) and differed significantly between second and third generation Dual-Source CT (0.43 vs. 0.22 mSv, p = 0.003). CONCLUSION: Size and subtype of VSDs can be accurately assessed by CTA of the chest in patients with complex congenital heart defects at a very low radiation dose.

Impact of voxel size and scan time on the accuracy of three-dimensional radiological imaging data from cone-beam computed tomography.

PURPOSE: Three-dimensional (3D) radiological imaging plays an important role in surgical planning used in modern dentistry. The aim of this study was to optimize imaging parameters with a special focus on voxel size and scan time. MATERIAL AND METHODS: A virtual 3D master model of a macerated human skull was generated using an industrial optical noncontact white light scanner. The skull was X-rayed with cone-beam computed tomography that was applied using different settings for voxel size and acquisition time (voxel edge length of 0.3 mm, scan times 4.8 s and 8.9 s; voxel edge length of 0.2 mm, scan times 14.7 s and 26.9 s). The scan was repeated 10 times at each setting. The CBCT scans were converted into 3D virtual models (actual value), which were superimposed with the 3D master model (reference value) to detect absolute differences. RESULTS: The mean value of deviation increased with increasing voxel size and decreasing scan time. For a voxel edge length of 0.3 mm, the mean values of deviation were 0.33 mm and 0.22 mm with scan times of 4.8 s and 8.9 s, respectively. For a voxel edge length of 0.2 mm, the mean deviations were 0.16 mm and 0.14 mm with scan times of 14.7 s and 26.9 s, respectively. CONCLUSIONS: When using small voxel sizes, the scan time does not have a significant impact on image accuracy and therefore the scan time can be shortened. However, for larger voxel sizes, shorter scan times can lead to increased inaccuracy.