CT Scans Of Patients Research Articles

Net water uptake as a predictive neuroimaging marker for acute ischemic stroke outcomes: a meta-analysis.

To assess the role of net water uptake (NWU) in predicting outcomes in acute ischemic stroke (AIS) patients. A systematic review and meta-analysis were performed, adhering to established guidelines. The search covered PubMed, Scopus, Web of Science, and Embase databases until July 1, 2023. Eligible studies reporting quantitative ischemic lesion NWU in admission CT scans of AIS patients, stratified based on outcomes, were included. Data analysis was performed using R software version 4.2.1. Incorporating 17 original studies with 2217 AIS patients, NWU was significantly higher in patients with poor outcomes compared to those with good outcomes (difference of medians: 5.06, 95% CI: 3.00-7.13, p < 0.001). Despite excluding one outlier study, considerable heterogeneity persisted among the included studies (I2 = 90.8%). The meta-regression and subgroup meta-analyses demonstrated significantly higher NWU in patients with poor functional outcome, as assessed by modified Rankin Scale (difference of medians: 3.83, 95% CI: 1.98-5.68, p < 0.001, I2 = 72.9%), malignant edema/infarct (difference of medians: 8.30, 95% CI: 4.01-12.58, p < 0.001, I2 = 95.6%), and intracranial hemorrhage (difference of medians: 5.43, 95% CI: 0.44-10.43, p = 0.03, I2 = 91.1%). NWU on admission CT scans shows promise as a predictive marker for outcomes in AIS patients. Prospective, multicenter trials with standardized, automated NWU measurement are crucial for robustly predicting diverse clinical outcomes. The potential of net water uptake as a biomarker for predicting outcomes in acute ischemic stroke patients holds significant promise. Further validation through additional research could lead to its integration into clinical practice, potentially improving the accuracy of clinical decision-making and allowing for the development of more precise patient care strategies. • Net water uptake, a CT-based biomarker, quantifies early brain edema after acute ischemic stroke. • Net water uptake is significantly higher in poor outcome acute ischemic stroke patients. • Net water uptake on CT scans holds promise in predicting diverse acute ischemic stroke outcomes.

Implication of Bone Mineral Density and Body Composition Parameters for Length of Hospital Stay in Patients with COVID-19.

Multisystem information, including musculoskeletal information, can be captured from chest CT scans of patients with COVID-19 without further examination. This study aims to assess the relationship between chest CT-extracted baseline bone mineral density (BMD) and body composition parameters and the length of hospital stay in these patients. A retrospective analysis was performed in a cohort of 88 patients with COVID-19. Correlation analysis and a generalized linear model (GLM) were used to assess the associations between the length of hospital stay and covariates, including age, sex, body mass index (BMI), BMD and body composition variables. The mean length of hospital stay was 27.4±8.7 days. The length of hospital stay was significantly positively associated with age (r=0.202, p=0.046) and the paraspinal muscle fat ratio (r=0.246, p=0.021). The GLM involving age, sex, BMD, paraspinal muscle fat ratio, subcutaneous adipose tissue (SAT) area, visceral adipose tissue (VAT) area, and liver fat fraction (LFF) showed that the length of hospital stay was positively correlated with VAT area (β coefficients, 95% CI: 9.304, 1.141-17.478, p=0.025). The musculoskeletal features extracted from chest CT correlated with the prognosis of COVID-19 patients. Factors including old age, a higher paraspinal muscle fat ratio and a larger VAT area in patients with COVID-19 were associated with longer hospital stays.

Rare Case of Caecal Non Hodgkins Lymphoma Presented as Intussusception – Case Report and Literature Review

A 68-year-old man presented at Pacific institute of medical sciences emergency department in May 2023 with pain in the epigastric region. Physical examination revealed no pertinent findings. Blood and urine tests were normal, and erect abdominal x-ray revealed a distended small intestine. CT scan shows ileo-colic intussusception. During laparotomy a large mass of 5x5 cm in size was detected in the caecum. It is very important to do CT scan for patients with long- standing abdominal pain and vomiting to achieve a definitive diagnosis of intussusception.

Automatic deep learning method for third lumbar selection and body composition evaluation on CT scans of cancer patients.

The importance of body composition and sarcopenia is well-recognized in cancer patient outcomes and treatment tolerance, yet routine evaluations are rare due to their time-intensive nature. While CT scans provide accurate measurements, they depend on manual processes. We developed and validated a deep learning algorithm to automatically select and segment abdominal muscles [SM], visceral fat [VAT], and subcutaneous fat [SAT] on CT scans. A total of 352 CT scans were collected from two cancer centers. The detection of the third lumbar vertebra and three different body tissues (SM, VAT, and SAT) were annotated manually. The 5-fold cross-validation method was used to develop the algorithm and validate its performance on the training cohort. The results were validated on an external, independent group of CT scans. The algorithm for automatic L3 slice selection had a mean absolute error of 4 mm for the internal validation dataset and 5.5 mm for the external validation dataset. The median DICE similarity coefficient for body composition was 0.94 for SM, 0.93 for VAT, and 0.86 for SAT in the internal validation dataset, whereas it was 0.93 for SM, 0.93 for VAT, and 0.85 for SAT in the external validation dataset. There were high correlation scores with sarcopenia metrics in both internal and external validation datasets. Our deep learning algorithm facilitates routine research use and could be integrated into electronic patient records, enhancing care through better monitoring and the incorporation of targeted supportive measures like exercise and nutrition.

MECHANICALLY EVOLUTIVE 3D-PRINTED SCAFFOLDS FOR BONE REGENERATION

Developments in the field of additive manufacturing have allowed significant improvements in the design and production of scaffolds with biologically relevant features to treat bone defects. Unfortunately, the workflow to generate personalized scaffolds is source of inaccuracies leading to a poor fit between the implant and patients' bone defects. In addition, scaffolds are often brittle and fragile, uneasing their handling by surgeons, with significant risks of fracture during their insertion in the defect. Consequently, we developed organo-mineral cementitious scaffolds displaying evolutive mechanical properties which are currently being evaluated to treat maxillofacial bone deformities in veterinary clinics. Treatment of dog patients was approved by ethic and welfare committees (CERVO-2022-14-V). To date, 8 puppies with cleft palate/lip deformities received the following treatment. Two weeks prior surgery, CT-scan of patient's skull was performed to allow for surgical planning and scaffold designing. Organo-mineral printable pastes were formulated by mixing an inorganic cement precursor (α-Ca3(PO4)2) to a self-reticulating hydrogel (silanized hyaluronic acid) supplemented with a viscosifier (hydroxymethylpropylcellulose). Scaffolds were produced by robocasting of these pastes. Surgical interventions included the reconstruction of soft tissues, and the insertion of the scaffold soaked with autologous bone marrow. Bone formation was monitored 3 and 6 months after reconstruction, and a biopsy at 6 months was performed for more detailed analyses. Scaffolds displayed great handling properties and were inserted within bone defects without significant issue with a relevant bone edges/scaffold contact. Osteointegration of the scaffolds was observed after 3 months, and regeneration of the defect at 6 months seemed quite promising. Preliminary results have demonstrated a potential of the set-up strategy to treat cleft lip/palate deformities in real, spontaneous clinical setting. Translation of these innovative scaffolds to orthopedics is planned for a near future.

Validating a 3D-printed endovascular simulator for use in training surgical residents

ObjectiveThree-dimensional (3D)-printed endovascular models can be an accessible alternative to expensive, state-of-the-art endovascular simulators but currently lack the rigorous validation needed to be dependable educational tools. This study describes the manufacture of a 3D-printed endovascular model of an aorta and determines the construct validity and preliminary content and face validity of the model. MethodsA 3D-printed aorta was created using segmented data from a patient computerized tomography scan and a FormLabs 3B 3D printer with FormLabs Clear resin. Participants were asked to perform two tasks from a femoral access point: catheterize the contralateral common iliac artery and the superior mesenteric artery. Participants were assessed for task completion, technique, and time. Performance was compared between levels of education (medical student vs lower-year resident vs upper-year resident vs attending) and levels of endovascular experience (<5 procedures vs 6-20 procedures vs 21-100 procedures vs >100 procedures). Users completed questionnaires assessing the face and content validity of the simulator after their participation. Results48 participants were recruited (12 medical students, 19 lower-year residents, 13 upper-year residents, and 4 attendings). Of these, 26 participants had performed <5 procedures, 10 had performed 6 to 20 procedures, 7 had performed 21 to 100 procedures, and 5 had performed >100 real-world procedures. Neither education level nor experience level correlated with task completion. Increasing levels of training progressively increased rates of correct technique for both tasks combined (8% vs 21% vs 46% vs 75%, P = .032) and decreased cumulative time (307.3 vs 252.2 vs 185.8 vs 139 seconds, P = .005). Similarly, increased levels of experience progressively increased rates of correct technique for both tasks combined (7% vs 50% vs 71% vs 80%, for increasingly experienced groups, P < .001) and decreased cumulative completion times (276 vs 237 vs 187 vs 113 seconds, P = .003) for both tasks. Multivariate analysis showed that training level was not a predictor for time taken to complete any task, while experience level was a predictor for superior mesenteric artery cannulation time (P < .02). Participants rated the model as having somewhat realistic haptics, dissimilar “look and feel” to the operating room, and strongly believed that the model was valuable for practicing endovascular surgery. ConclusionsThese findings verify the construct validity of this endovascular simulator, as those with the most real-world experience used a correct technique more often and completed the tasks the fastest. Survey results supported the content validity of the model. Basic 3D-printed endovascular models should be considered as an affordable, readily accessible adjunct to surgical education.

Navigating the calvaria with mobile mixed reality-based neurosurgical planning: how feasible are smartphone applications as a craniotomy guide?

Virtual simulation and imaging systems have evolved as advanced products of computing technology over the years. With advancements in mobile technology, smartphones, and tablets, the quality of display and processing speed have gradually improved, thanks to faster central processing units with higher capacity. Integrating these two technologies into the fields of healthcare and medical education has had a positive impact on surgical training. However, contemporary neurosurgical planning units are expensive and integrated neuronavigation systems in operating rooms require additional accessories. The aim of this study was to investigate the compatibility of smartphone applications in augmented reality (AR)-based craniotomy planning, which can be available even in disadvantaged workplaces with insufficient facilities. Thirty patients diagnosed with supratentorial glial tumor and who underwent operations between January 2022 and March 2023 were included in the study. The entire stages of the surgical procedures and the surgical plans were executed with neuronavigation systems. The patient CT scans were reconstructed using software and exported as a 3D figure to an AR-enhanced smartphone application. The evaluation of the application's success was based on the spatial relationship of the AR-based artificial craniotomy to the neuronavigation-based craniotomy, with each AR-based craniotomy scaled from 0 to 3. In the comparison between neuronavigation-based and AR fusion-based craniotomies, 8 of 30 (26.6%) patients scored 0 and were considered failed, 6 (20%) scored 1 and were considered ineffective, 7 (23.3%) scored 2 and were considered acceptable, and 9 (30%) scored 3 and were considered favorable. AR technology has great potential to be a revolutionary milestone of neurosurgical planning, training, and education in the near future. In the authors' opinion, with the necessary legal permissions, there is no obstacle to the integration of surgical technological systems with mobile technology devices such as smartphones and tablets that benefit from their low-budget requirements, wide-range availability, and built-in operating systems.

Coexistence of Trigonocephaly and Sylvian Arachnoid Cysts: A Coincidence?

Introduction: The association between trigonocephaly and Sylvian fissure arachnoid cysts (ACs) has been occasionally reported in the literature. However, the real incidence of this association and its clinical relevance remain unknown. Methods: The authors collected and retrospectively reviewed all clinical charts and CT scans of patients surgically treated for trigonocephaly at the Pediatric Neurosurgical Department of Fondazione Policlinico Universitario “Agostino Gemelli” IRCCS from January 2014 to June 2023. Results: During the study period, 136 patients with trigonocephaly underwent surgery. Analysis of the clinical charts revealed that in 39.7% of the cases (54/136), preoperative CT scan depicted the presence of a Sylvian fissure AC. Of these, AC was bilateral in 23 cases and unilateral in the remaining 31. All unilateral ACs were on the left side. The ACs were classified as Galassi grade I in 52 cases (96.3%) and Galassi grade II in 2 cases (3.7%). Interestingly, in 1 case we reported a Galassi grade I AC enlargement during follow-up, thereby necessitating surgical fenestration. Conclusion: ACs and trigonocephaly are well-known conditions for pediatric neurosurgeons; however, their association is poorly defined. Despite the lack of reports on the incidence and clinical significance of this association, it is worth knowing that radiological follow-up is essential in monitoring AC evolution.

Comparison between abdominal CT findings in intensive care unit (ICU) and non-ICU patients with Covid-19: experience from a tertiary care hospital.

16-66% of COVID-19 positive patients may have abdominal symptoms and findings in abdominal CT. The yield of abdominal CT scan in patients having abdominal complaints is not known. The aim of this study was to explore the various abdominal imaging manifestations of COVID-19 and COVID-19 associated Mucormycosis (CAM) and to identify the relevant clinical and laboratory features associated with severity of the symptoms. A retrospective single centre observational study was performed at a tertiary care hospital in Northwest India. All consecutive patients who had COVID positive RT-PCR report and had undergone abdominal Computed Tomography scan from March 2020 to November 2021 for various abdominal complaints were included. Demographic data, CT images and reports and all relevant lab parameters were collected. Out of 75 patients, positive abdominal findings were seen in 65 patients. Hepatobiliary findings were seen in 41.3% (31 of 75; OR=1.9) and bowel abnormalities were found in 37.3% (28 of 75; OR=2.1) of COVID-19 patients. 7 patients who had renal infarcts or bowel ischemia were found to have COVID-19 associated Mucormycosis on histopathology. Chest CT severity score was positively correlated with most of the abdominal manifestations in patients requiring ICU admission. Elevated D-dimer levels were significantly associated with abdominal symptoms.

Chest CT findings in community-acquired pneumonia due to Coxiella burnetii (Q fever) compared to Streptococcus pneumoniae, a cross sectional study in French Guiana, 2013–2017

ObjectivesFew and small studies previously examined chest CT-scan characteristics of Coxiella burnetii (Cb) community-acquired pneumonia (CAP). Larger studies are needed to guide physicians towards diagnosis of Q fever in case of pneumonia. MethodsWe conducted a single-center retrospective observational study between 2013 and 2017. All patients with Cb or Streptococcus pneumoniae (Sp) CAP who had a chest CT-scan on admission at Cayenne Hospital (French Guiana) were included. Chest CT-scan were all analyzed by the same expert radiologist. ResultsWe included 75 patients with Cb CAP and 36 with Sp CAP. Fifty-nine percent of all patients were men (n = 66) and median age was 52 [IQR = 38–62]. Chest CT-scans of Cb CAP patients revealed 67 alveolar condensations (89 %), 52 ground-glass opacities (69 %), 30 cases of lymphadenopathy(ies) (40 %) and 25 pleural effusions (33 %). Parenchyma lesions caused by Cb were predominantly unilateral (67 %). We found high numbers of alveolar condensations in both Cb and Sp CAP (89 % and 75 %; respectively), but the presence of ground-glass opacities was significantly associated with Cb CAP (69 % versus 30 %; p < 0.01). Cb CAP were associated with more lymphadenopathies (40 % vs 17 %; p = 0.01) while Sp CAP showed more bronchial thickening (19 % versus 3 %; p < 0.01) and (micro)nodule(s) ≤1 cm (25 % vs 3 %, p < 0.01). ConclusionsThis large study shows that the most typical aspect of chest CT-scan in case of Cb CAP in French Guiana is a unilateral alveolar consolidation associated with ground glass opacities and lymphadenopathies. C. burnetti and S. pneumoniae both most often cause alveolar consolidations, but present some significantly different CT-scan patterns. This could help physicians through therapeutic choices.

Multiple intrathoracic thrombosis detected on ct scan in patient with antiphospholipid antibody syndrome: case report

Antiphospholipid antibody syndrome (APS) is the clinical correlation between antiphospholipid antibodies and hypercoagulability syndrome. The prevalence of APS in the general population is undetermined. APS disease carries a notable risk of vascular thrombosis. CT scan is the preferred imaging method for assessing thrombosis, although the timing of image acquisition should be considered. The case report detailed the discovery of many intrathoracic thromboses on a CT scan of a patient diagnosed with the uncommon condition APS. Case study: A 34-year-old woman was hospitalized due to dyspnea, cough, and a 3 kg weight loss over a three-month period. She has a background in Deep Vein Thrombosis (DVT). The test results showed abnormalities in protein C, protein S, and high D-dimer levels. The CT scan revealed numerous intrathoracic thrombi. Antiphospholipid syndrome (APS) is an immunological condition that elevates the likelihood of blood clot formation, resulting in thrombosis inside the arteries and veins. The approximate occurrence rate of APS is five occurrences per 100,000 individuals annually. Antiphospholipid syndrome (APS) leads to the formation of blood clots in the legs, a condition referred to as deep vein thrombosis (DVT). This patient had a history of deep vein thrombosis (DVT) and many blood clots within the chest cavity. A CT scan revealed persistent blood clots in the main pulmonary artery and the right and left pulmonary arteries. Antiphospholipid syndrome (APS) can lead to the formation of blood clots in both arteries and veins. CT scan is the preferred method for evaluating thrombosis, and numerous phases are required to examine all blood arteries.

Robustness of Single- and Dual-Energy Deep-Learning-Based Scatter Correction Models on Simulated and Real Chest X-rays

Chest X-rays (CXRs) represent the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field of view required. Scatter in CXRs introduces background in the images, which reduces their contrast. We developed three deep-learning-based models to estimate and correct scatter contribution to CXRs. We used a Monte Carlo (MC) ray-tracing model to simulate CXRs from human models obtained from CT scans using different configurations (depending on the availability of dual-energy acquisitions). The simulated CXRs contained the separated contribution of direct and scattered X-rays in the detector. These simulated datasets were then used as the reference for the supervised training of several NNs. Three NN models (single and dual energy) were trained with the MultiResUNet architecture. The performance of the NN models was evaluated on CXRs obtained, with an MC code, from chest CT scans of patients affected by COVID-19. The results show that the NN models were able to estimate and correct the scatter contribution to CXRs with an error of &lt;5%, being robust to variations in the simulation setup and improving contrast in soft tissue. The single-energy model was tested on real CXRs, providing robust estimations of the scatter-corrected CXRs.

Deep learning for enhancing cancer identification and diagnosis

One of the promising and significant fields of technology is the use of automated computer techniques, particularly machine learning, to facilitate and enhance medical analysis and diagnosis. In the area of artificial intelligence (AI), deep learning techniques using artificial neural networks (CNNs) so-called because they superficially resemble biological neural networks - are computational network models for discovering large, high-dimensional data sets (such as medical datasets) for complex structures and patterns. In this paper, the focus is on summarizing contemporary applications of various deep learning algorithms in the direction of cancer identification and diagnosis, and on re-implementing supervised learning for cancer detection after a new database based on the lung cancer detection project from the book Deep Learning with PyTorch. The automatic detection of lung malignancies from patient CT scans was re-implemented by deep learning. In this paper, the technique is applied to data provided by the Iraqi Oncology Teaching Hospital. The author demonstrates that the application of the new data will also maintain the accuracy of the identification, and thus promises to develop into a more comprehensive and general cancer detection and diagnosis method in the future as the algorithm and technology are further refined.

The Impact of Semaglutide on Liver Fat Assessed by Serial Cardiac CT scans in Patients with Type 2 Diabetes: Results from STOP Trial

IntroductionThere is increasing prevalence of hepatic steatosis. Hepatic steatosis is increasingly recognized as the independent risk factor for cardiovascular mortality. However, there are limited options for the treatment of fatty liver. In this study we evaluated the effect of semaglutide on liver fat as measured by non-contrast cardiac CT scans. MethodsSTOP is a randomized controlled trial that evaluated semaglutide treatment effect on coronary atherosclerosis progression (STOP) in type 2 diabetes. We utilized unenhanced cardiac CT scans to quantify liver fat based on CT Hounsfield attenuation method. A total of 114 subjects qualified for this study of the 140 subjects randomized, 59 in semaglutide group and 55 in the placebo group and were followed for 12 months. Multivariate regression models were used to evaluate the change in liver fat content overtime. Results114 subjects were included in the study, 61% male, mean age of 57.8±8.1 years and mean BMI of 32.0±6.7. The average of the three liver measures showed an improvement in the semaglutide group 1.4±9.0 versus worsening in the placebo group of 1.9±9.5 mean HU. The multivariable linear regression models including age, gender, BMI, hypertension, hyperlipidemia, past smoking and baseline liver attenuation, showed that the semaglutide group average liver attenuation measures improved by 4.4 HU versus placebo across the trial, p=0.002 indicating improvement in the liver fat content in treatment group. ConclusionIn type 2 diabetes patients with hepatic steatosis, treatment with semaglutide resulted in a significant improvement in fatty liver resolution compared to placebo.

Reliability of the CURL classification for proximal ulna fracture-dislocations of the elbow

BackgroundProximal ulna fracture-dislocations are challenging injuries with a myriad of existing classification systems. The Coronoid, proximal Ulna, Radius and Ligaments (CURL) classification is a simple framework designed to focus attention on the key components affecting outcome and guide surgical management. This study evaluates inter- and intra-observer reliability of this new classification. MethodsFour observers independently reviewed plain radiographs and CT scans of patients with proximal ulna fracture-dislocations. Each observer scored the Coronoid (C), proximal Ulna (U) and Radius (R) components for each fracture on two occasions. The osseous components were sub-classified as ‘intact’, ‘simple’ or ‘complex’. The Ligament component (L) was not rated as this requires intra-operative classification. Inter- and intra-observer reliability was calculated using Cohen’s weighted kappa coefficients. X-ray and CT were compared for patients with both imaging modalities. The Landis and Koch criteria were used to interpret the strength of the kappa statistics. Results177 patients had plain X rays, 58 patients had both X ray and CT scans. Overall, in the X ray only cohort, there was ‘almost perfect’ inter-observer reliability for the radial head (k=0.94) and coronoid (k=0.83), and ‘substantial’ reliability (k=0.68) for the proximal ulna. For the X ray and CT cohort, inter-observer reliability was ‘almost perfect’ across both modalities for the radial head (k=0.88 and k=0.93, respectively) and ‘moderate’ for the proximal ulna (k=0.48 and k=0.52, respectively). For the coronoid, inter-observer reliability for X-ray interpretation was ‘substantial’ (k=0.74) and for CT was ‘almost perfect’ (k=0.89). Intra-observer reliability was ‘almost perfect’ for all components, other than CT assessment of the proximal ulna which demonstrated ‘substantial’ reliability (k=0.74). ConclusionThe CURL classification demonstrates strong inter- and intra-observer reliability, supporting use of the classification for proximal ulna fracture-dislocations. CT is recommended for improved characterization of any fracture with a coronoid component.

CT scan and clinical characteristics in COVID-19 patients with and without systemic lupus erythematosus

CT scan and clinical characteristics in COVID-19 patients with and without systemic lupus erythematosus

Application of Power PICC for injection of contrast agent for contrast-enhanced CT scan in patients with biliary tract tumors

Application of Power PICC for injection of contrast agent for contrast-enhanced CT scan in patients with biliary tract tumors

The Intrapelvic Pressure during Retrograde Intrarenal Surgery in the Setting of Ureteral Access Sheath Size: Experimental Study on 3D Printed Model

Introduction: There is no standardised, universal method to assess physical conditions such as pressure in the pelvicalyceal system in real time during RIRS (retrograde intrarenal surgery). Therefore, the problem of increased pressure in the upper urinary tract during the procedure is underestimated. Moreover, it can potentially cause micro-damage and longer postoperative recovery. The aim of this study was to evaluate intrapelvic pressure (IPP) during RIRS procedures. Materials and Methods: The 3D printed models of the pelvicalyceal system were printed based on a CT scan of the real patient. They were used to perform 50 RIRS procedures with laser lithotripsy of artificially synthesised kidney stones with two different sizes of ureteral access sheath-UAS (10/12Fr vs. 12/14Fr) together with different energy settings generated by the holmium:YAG laser. IPP monitoring during RIRS was performed with the use of the PressureWire X Guidewire compatible with the CoroFlow system. Results and Conclusions: The results showed that a high IPP of up to 400 cmH2O would be achieved using a 10/12Fr UAS, while the use of a 12/14Fr UAS would significantly reduce the peak pressure to approximately 100 cmH2O; hence, the size of the UAS is a pivotal factor of the IPP generated during the procedure.

Why we should care about gas pockets in online adaptive MRgRT: a dosimetric evaluation.

Contouring of gas pockets is a time consuming step in the workflow of adaptive radiotherapy. We would like to better understand which gas pockets electronic densitiy should be used and the dosimetric impact on adaptive MRgRT treatment. 21 CT scans of patients undergoing SBRT were retrospectively evaluated. Anatomical structures were contoured: Gross Tumour Volume (GTV), stomach (ST), small bowel (SB), large bowel (LB), gas pockets (GAS) and gas in each organ respectively STG, SBG, LBG. Average HU in GAS was converted in RED, the obtained value has been named as Gastrointestinal Gas RED (GIGED). Differences of average HU in GAS, STG, SBG and LBG were computed. Three treatment plans were calculated editing the GAS volume RED that was overwritten with: air RED (0.0012), water RED (1.000), GIGED, generating respectively APLAN, WPLAN and the GPLAN. 2-D dose distributions were analyzed by gamma analysis. Parameter called active gas volume (AGV) was calculated as the intersection of GAS with the isodose of 5% of prescription dose. Average HU value contained in GAS results to be equal to -620. No significative difference was noted between the average HU of gas in different organ at risk. Value of Gamma Passing Rate (GPR) anticorrelates with the AGV for each plan comparison and the threshold value for GPR to fall below 90% is 41, 60 and 139 cc for WPLANvsAPLAN, GPLANvsAPLAN and WPLANvsGPLAN respectively. GIGED is the right RED for Gastrointestinal Gas. Novel AGV is a useful parameter to evaluate the effect of gas pocket on dose distribution.

EFFECTIVENESS EDGE DETECTION OPERATOR CANNY TO IMPROVE IMAGE QUALITY THORAX CT SCAN IN CASES COVID-19

Background: Thorax CT scan is one of the medical supports that contributes most importantly to the diagnosis, especially cases of COVID-19. The disadvantage that has a CT scan image is noise. When the noise is high then the Signal Noise Ratio (SNR) value produced is low. Canny operator edge detection technique is one solution to animate noise. Purpose: Analyzing differences in image quality and anatomical information on thorax CT scan images in COVID-19 patients before and after the application of canny operator edge detection techniques. Method: A quasi experimental research on thorax CT Scan images before and after the application of canny operator edge detection which amounted to 10 samples. Image assessment is done by measuring noise, SNR, and anatomical information. Differences in image quality (noise and SNR) are tested with paired T-tests. Anatomical information is tested with the Wilcoxon Signed Rank Test. Result: There are differences in image quality in thorax CT scan images in COVID-19 patients before and after the application of canny operator edge detection techniques, with p-value &lt;0.001. There are differences in the anatomical information of thorax CT scan images in COVID-19 patients before and after the application of canny operator edge detection technique with a p-value of 0.004. Conclusion: Edge detection operator canny techniques are able to lower noise values, improve SNR and improve image anatomy information thorax CT scan in COVID-19 patients.