CT Scans Of Patients Research Articles

Quantification of the\xa0spatial distribution of primary tumors in the lung to develop new prognostic biomarkers for locally advanced NSCLC

The anatomical location and extent of primary lung tumors have shown prognostic value for overall survival (OS). However, its manual assessment is prone to interobserver variability. This study aims to use data driven identification of image characteristics for OS in locally advanced non-small cell lung cancer (NSCLC) patients. Five stage IIIA/IIIB NSCLC patient cohorts were retrospectively collected. Patients were treated either with radiochemotherapy (RCT): RCT1* (n = 107), RCT2 (n = 95), RCT3 (n = 37) or with surgery combined with radiotherapy or chemotherapy: S1* (n = 135), S2 (n = 55). Based on a deformable image registration (MIM Vista, 6.9.2.), an in-house developed software transferred each primary tumor to the CT scan of a reference patient while maintaining the original tumor shape. A frequency-weighted cumulative status map was created for both exploratory cohorts (indicated with an asterisk), where the spatial extent of the tumor was uni-labeled with 2 years OS. For the exploratory cohorts, a permutation test with random assignment of patient status was performed to identify regions with statistically significant worse OS, referred to as decreased survival areas (DSA). The minimal Euclidean distance between primary tumor to DSA was extracted from the independent cohorts (negative distance in case of overlap). To account for the tumor volume, the distance was scaled with the radius of the volume-equivalent sphere. For the S1 cohort, DSA were located at the right main bronchus whereas for the RCT1 cohort they further extended in cranio-caudal direction. In the independent cohorts, the model based on distance to DSA achieved performance: AUCRCT2 [95% CI] = 0.67 [0.55–0.78] and AUCRCT3 = 0.59 [0.39–0.79] for RCT patients, but showed bad performance for surgery cohort (AUCS2 = 0.52 [0.30–0.74]). Shorter distance to DSA was associated with worse outcome (p = 0.0074). In conclusion, this explanatory analysis quantifies the value of primary tumor location for OS prediction based on cumulative status maps. Shorter distance of primary tumor to a high-risk region was associated with worse prognosis in the RCT cohort.

A Transfer Learning Approach for Improving OAR Segmentation in the Adaptive Therapy or Retreatment of Head and Neck Cancer

<h3>Purpose/Objective(s)</h3> Deep learning-based segmentation has achieved great progress compared with traditional method. However, the generalizability is still an unsolved problem, leading to suboptimal contours for some cases that requires manual editing. A big source of error lies in the abnormal patient anatomy that was not well covered by the training data. In adaptive or retreatment settings, a well-contoured CT is available. However, the current DLSEG algorithm does not allow such information to be utilized. Our proposed solution is to use transfer learning method to tune a trained DLSEG model toward individual patient using the prior segmented scans. <h3>Materials/Methods</h3> A HN DLSEG model was trained on 2015 MICCAI Head and Neck dataset. The model was applied on HNSCC-3DCT-RT dataset from TCIA which contains 3 CT scans at pre-, mid-, and end- treatment course. The DLSEG result was compared with the ground truth contour in the study. Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD) were computed for BrainStem, Mandible, Parotid, SpinalCord and OpticNerve. The standard deviations of these metrics were computed, both within the same patient (IntraPatient variation) and across patients (InterPatient variation). Then, the DLSEG was re-tuned using transfer learning on the pre- treatment CT scan of each individual patient. The re-tuned model was applied to the mid- and end- treatment CT. The segmentation accuracy was evaluated. <h3>Results</h3> All structures showed a much larger InterPatient variation than IntraPatient variation, indicating that patient specific anatomical feature is one of the main contributors to segmentation accuracy. When transfer learning is applied. Nearly all patients saw improvement in contouring accuracy. Statistically significant improvement was observed for BrainStem, Mandible, Parotid and Parotid_L. <h3>Conclusion</h3> Transfer learning is a promising approach to incorporate the existing segmentation on prior CT to improve the segmentation accuracy in the adaptive or re-treatment settings.

Evaluation of Cardiac Conduction System Exposure with Breast Volumetric Modulated Arc Therapy and Intensity Modulated Proton Therapy

Conduction disorders and arrhythmias are reported radiation-induced adverse events. Exposition of cardiac conduction system during breast radiotherapy has never been studied, despite increasing use of intensity modulated radiotherapy which expose larger volumes to low dose bath. We evaluated conduction node exposure during breast irradiation with volumetric modulated arc therapy (VMAT) and estimated the potential dosimetric benefit with intensity modulated proton therapy (IMPT).Atrioventricular (AVN) and sinoatrial (SAN) nodes were retrospectively delineated according to published guidelines on the simulation CT scans of twelve breast cancer patients having undergone conserving surgery and adjuvant locoregional VMAT. According to these guidelines, the SAN was delineated by a 2 cm-diameter sphere, tangent to the external wall of the right atrium, centered at the height of the ascending aorta origin and the AVN was delineated by a 2 cm-diameter sphere centered at the junction between the four cardiac chambers, 1 cm above the last slice where the left atrium is visible. IMPT treatment was re-planned on the simulation CT scans for left-sided breast cancer patients. Mean and maximum doses to the SAN and the AVN were retrieved and compared.Average mean doses to the SAN and to the AVN were 2.8 Gy and 2.3 Gy respectively for left-sided irradiation and 9.6 Gy and 3.6 Gy respectively for right-sided irradiation. Average maximum doses to the SAN and to the AVN were 3.5 Gy and 2.8 Gy respectively for left-sided irradiation and 13.1 Gy and 4.6 Gy respectively for right-sided irradiation. There were no significant differences between mean and maximum dose to the AVN and to the whole heart between right- and left-sided irradiations, while the SAN was significantly more exposed for right-sided irradiation. For left-sided breast cancer patients, IMPT significantly reduces mean dose to the SAN from 2.8 Gy to 0.0 Gy and to the AVN from 2.3 Gy to 0 Gy, and maximum dose to the SAN from 3.5 Gy to 0.2 Gy and to the AVN from 2.8 Gy to 0 Gy (P < 0.01).SAN and AVN can be substantially exposed during breast VMAT, especially for right-sided irradiation, while IMPT delivers virtually no dose to the SAN or the AVN. Cardiotoxicity studies evaluating conduction node exposure might define dose constraints and criteria for additional cardiac sparing techniques, such as respiratory techniques or proton therapy, which could be beneficial to patients with underlying rhythmic or conduction disorders.

A Crowdsourcing Challenge for the Development of Artificial Intelligence Algorithms for Automated Identification and Delineation of Pancreatic Cancer Primary Tumors

To develop a crowdsourced artificial intelligence computational algorithm to accurately identify and delineate pancreatic cancer (PC) primary tumors and major peripancreatic vessels on high-resolution CT images.After IRB approval, a well-curated data set of 243 diagnostic pancreatic-protocol high-resolution CT scans of patients diagnosed with PC was prepared. A data science marathon competition was then hosted online by a third-party company between December 2020 and January 2021. The full data set was randomly partitioned into training, validation and hold-out (scoring) data sets. Contestants were provided a training dataset containing [de-identified files from a high-resolution IV contrast-enhanced CT DICOM image set; de-identified DICOM metadata; de-identified RT structure set file with contours of the tumor and superior mesenteric artery (SMA), celiac axis/common hepatic artery continuum (CA/CHA), and superior mesenteric vein/portal vein continuum (SMV/PV)], along with a smaller validation data set with CT scans without contours to test their trained algorithms. Provisional scores were assigned using the validation data set throughout the competition. Final scoring of submitted algorithms was based on the performance of the algorithms on a hold-out data set (unavailable for the contestants), matched against the expected ground truth data using an F1 scoring metric [2 * precision * recall / (precision + recall)], in which precision = TP / (TP + FP), and recall = TP / (TP + FN). TP is the area (measured in pixels) of the overlap of expected (ground truth delineation) and extracted (submitted algorithm) regions, FP is the area extracted but which does not belong to expected regions, FN is the area of the expected regions that is not covered by extracted regions. The above was calculated separately for the 4 structure types (tumor, SMA, CA/CHA, and SMV/PV), with a weighted average of the four F1 values, where the weight of the tumor was 7, and the weight of each of the vessels was 1. A final average for each contestant was scaled up to 0-100 range.In total, 337 algorithm solutions from 23 competitors were submitted. The winning algorithm achieved an average F1 score of 70.2. The F1 score ranged from 69.8 to 66.7 between the 2nd and 5th best solutions. The winning solution used a 3D-UNet model to develop a 3D semantic segmentation approach that was found to be significantly accurate on tumor and vessel delineation. A comparison between the winning solution and an ensemble between the 2nd to 5th place solutions showed that in 82% of cases, both the winning and the ensembled solution succeeded in achieving an F1 score > 60.A crowdsourced innovation challenge was successfully employed to generate artificial intelligence algorithms capable of accurately delineating pancreatic cancer on a diagnostic CT scan.

Quantitative CT imaging analysis to predict pathology features in patients with a congenital pulmonary airway malformation

BackgroundRisk for infection and potential malignant degeneration are the most common arguments for resecting asymptomatic Congenital Pulmonary Airway Malformations (CPAM). We aimed to investigate if CT- imaging characteristics can be used to predict histopathological features, by using an objective quantitative CT scoring method. MethodsArchival CPAM tissue samples were histologically re-assessed and patients who had a pre-operative volumetric CT-scan were included. Lung disease was quantified using the newly-developed congenital lung abnormality quantification(CLAQ) scoring method and obtained percentages were used to predict histopathological signs of inflammation and presence of mucinous proliferation (MP). Because MP is presumed a precursor for mucinous adenocarcinoma in situ (AIS) this method was also used to compare CT-scans of patients with AIS to those with only CPAM. ResultsThirty-three CPAM patients were included of which 13(39%) had histological signs of inflammation and 8(24%) had a MP. Patients with inflammation had a significantly smaller lesion (14% vs 38%) while those with MP had more extensive disease (54%vs17%). Patients with AIS had a significantly smaller lesion compared to CPAM patients (5%vs29%). Significant predictors for inflammation were smaller lesion size and percentage hypodensity within lesions while a larger lesion size and percentage parenchymal hyperdensity (solid lung tissue components) were predictors for MP as well as AIS. ConclusionsSmaller CPAM lesions may be more susceptible to inflammation while larger lesions may be associated with the presence of MP. Parenchymal hyperdensity is found as a predictor for MP as well as AIS and should therefore elicit more extensive gross sampling. Level of evidenceLevel III.

Abdominopelvic CT-scan in emergency departments for patients with suspected complications of Crohn\u2019s disease: a single tertiary center experience

BackgroundCrohn’s disease (CD) is a chronic disorder with frequent complications. The objective of this study was to assess the predictive factors of finding a complication of CD using abdominopelvic CT-scan in patients with a visit to the emergency department.MethodsPatients with at least one visit to the gastroenterology department of our University hospital during the year with a CD were retrospectively included. All visits to the emergency department of the hospital during the follow-up of these patients were identified.ResultsA total of 638 patients were included and 318 (49.8%) had at least one visit to the emergency department since the beginning of their follow-up. Abdominopelvic CT-scan was performed in 141 (23.7%) of the 595 visits for digestive symptoms. Only 4.3% of these CT-scans were considered as normal; there was luminal inflammation without complication in 24.8%, abscess, fistula or perforation in 22.7%, mechanical bowel obstruction in 36.9% and diagnosis unrelated to CD in 11.3%. In univariate analysis, stricturing phenotype (OR, 2.48; 95% CI, 1.16–5.29; p = 0.02) and previous surgery (OR, 2.90; 95% CI, 1.37–6.14; p = 0.005) were predictive factors of finding a complication of CD using abdominopelvic CT-scan, whereas no independent predictive factor was statistically significant in multivariate analysis.ConclusionIn CD patients consulting in emergency department, CT-scan examination was performed in 24% of visits for digestive symptoms and complications of CD were found in 60%. Complications were more frequent in patients with stricturing phenotype and previous surgery.

The Value of Abdominal and Pelvic CT Scan in Trauma Patients With Low Injury Severity Score and High Glasgow Coma Scale.

Computed tomography scans became the mainstay of emergency department (ED) evaluation of trauma patients including those with a high Glasgow Coma Scale (GCS) and a low Injury Severity Score (ISS). We elected to find the value of abdominal and pelvic CT in patients with negative physical examination and Focused Assessment of Sonography for Trauma (FAST) on arrival to the ED. This study is a retrospective analysis of 901 consecutive patients from 2017 to 2019 who presented to the ED with level 2 and 3 activation criteria. Each patient received a physical examination, CT abdomen and pelvis, and FAST exam. Data were collected on external factor including GCS, ISS, age, sex, comorbidities, anticoagulation use, and surgical intervention. The patients were divided into 2 groups, Group A and B. Group A consisted of patients with a negative physical exam, FAST, and CT result. Group B included patients with a negative physical exam and FAST exam with positive CT findings. Statistical analysis was done using a Student's t-test and chi-square test for significance value of P < .05. Institutional Review Board approval was obtained for this study. A total of 901 patients were analyzed which included 489 (54.3%) male and 412 (45.7%) female with a mean age of 56.2 (SD = 22.62) years. Out of the 901 patients, 461 patients received a physical, FAST, and CT exam. Group A consisted of 442 (95.9%) patients and Group B had 19 (4.1%) patients. Both groups were similar in GCS and ISS scoring with no significance difference in age, sex, comorbidities, and anticoagulation use. There was a significant difference in the ICU and hospital mean length of stay when CT scan was positive [2 (SD = 4.23) days vs. .6 (SD = 1.33) days with P < .0001 and 4.57 (SD ± 4.17) days vs. 2.5 (SD = 2.00) days with P < .0001, respectively]. The CT findings of the 19 patients in group B consisted of 6 incidentalomas, 5 vertebral compression fractures, 4 pelvic bone fractures, 1 minor liver contusion, 1 non-specific bowel thickening, 1 non-displaced rib fracture, and 1 case of small amount of free fluid in the pelvis. None of the CT findings required surgical intervention. Computed tomography of the abdomen and pelvis in trauma patients with high GCS and low ISS with initial negative physical and FAST examination did not provide additional critical information.

Retrospective evaluation of chest computed tomography findings of the patients diagnosed with COVID-19

Aim: In our study, we aimed to analyze laboratory findings, presentation symptoms and thoracic CT findings of patients who were admitted to the emergency department of our hospital with symptoms of COVID-19, had positive results of RT-PCR tests, and were referred to our radiology clinic. Material and Methods: Patients’ demographic data such as age and gender, symptoms on admission, PCR and CT outcomes were recorded and analyzed. In CT examinations, laterality, the presence of consolidation and/or ground-glass opacities (GGO), and central and/or peripheral distribution were analyzed. Results: A total of 74 patients aged 20-87 years who were found to be COVID-19 positive using RT-PCR test were included in our study. When examining the initial admission symptoms, patients were found to have complaints such as fever, cough, shortness of breath, weakness and sore throat. When the thorax CT findings of the patients included in the study were examined, bilateral and unilateral involvement, anterior and posterior localization, presence of apical involvement, peripheral and central distribution, multilobar and unilobar involvement, GGO, consolidation, vascular thickening, crazy paving, fibroatelectasis, subpleural band, air bronchogram, pleural effusion, pleural thickening, cavitation and mediastinal LAP findings were detected. Discussion: It is still premature to use CT alone instead of RT-PCR. However, the findings accumulated in the literature show that a trend has begun to develop in this regard. A definitive diagnosis must be confirmed by CT scan in patients who show typical symptoms of COVID-19, even though the PCR test is negative, especially in adults.

MILIARY METASTATIC ADENOCARCINOMA

TOPIC: Lung Cancer TYPE: Medical Student/Resident Case Reports INTRODUCTION: Miliary opacities are defined as innumerable 1- 4mm pulmonary nodules scattered throughout the lung fields. Differential for miliary pattern is wide including tuberculosis, fungal infection and distinct organ metastasis. We present a case of a 37 year old male with miliary pattern seen on the chest radiograph and CT scan with ostial lesion in his L2 vertebrae, who was initially thought to have miliary TB with Pott's disease later diagnosed with primary adenocarcinoma of the lung with spinal, brain and calvarium metastasis. CASE PRESENTATION: A 37-year-old male with no significant medical history presented to the ED with 2 months of lower back pain. He endorsed shortness of breath and 40 pound unintentional weight loss over 3 months. He was incarcerated 5 years ago at which time his PPD was negative.Chest x-ray showed diffuse bilateral infiltrates with micronodular pattern. Following this, CT scan was obtained to evaluate for lower back pain which showed pathological compression deformity in L2 and innumerable pulmonary nodules consistent with miliary pattern and also showed left upper lobe lung mass.Given his history of incarceration, weight loss, shortness of breath and deformity in his lumbar vertebra, miliary tuberculosis and Potts disease was considered. QuantiFERON gold and AFB sputum were obtained. After AFB x3 negative on sputum studies it was decided to proceed with bronchoscopy with bronchoalveolar lavage (BAL).Lymph node biopsies and BAL pathology reports came back positive for adenocarcinoma. Upon further investigation with MRI of the brain and the spine it was also noted that the patient had Cavalier metastasis, left frontal lobe metastasis and numerous enhancing bone lesions in lumbar and sacral spine with osseous metastasis.Oncology and radiation oncology were consulted and he was started on stereotactic radiation therapy to the left frontal lobe metastasis as well as a right calvarial metastasis and systemic chemotherapy and immunotherapy. DISCUSSION: Miliary opacities are seen in a wide array of conditions including infectious etiologies like miliary TB, histoplasmosis, other fungal infections and noninfectious etiologies including miliary metastasis from thyroid, renal, breast carcinomas, metastatic melanoma. There has also been documentation of miliary patterns seen in Langerhans' cell histiocytosis, hypersensitivity pneumonitis and a few cases of primary pulmonary lung cancers.History is a key component in diagnosis especially for patients coming from areas and populations where TB and other infectious disease are prevalent. Once infectious etiologies have been ruled out approach to rule out malignancies and metastasis should be perused. CONCLUSIONS: It is impossible to distinguish between infectious etiologies and malignancies solely based on CT scan in patient with miliary pattern, hence when definitive diagnosis is uncertain, tissue diagnosis should be perused. REFERENCE #1: Khan D, Danjuma M, Saddique M, U, Murshed K, A, H, Yassin M, A: Adenocarcinoma of the Lung Mimicking Miliary Tuberculosis. Case Rep Oncol 2020;13:139-144. doi: 10.1159/000505685 DISCLOSURES: No relevant relationships by Sarasi Jayaratne, source=Web Response No relevant relationships by Gaurang Prabhu, source=Web Response No relevant relationships by Gaurav Prabhu, source=Web Response

Gastrointestinal Bleeding at CT Angiography and CT Enterography: Imaging Atlas and Glossary of Terms.

Gastrointestinal (GI) bleeding is a common potentially life-threatening medical condition frequently requiring multidisciplinary collaboration to reach the proper diagnosis and guide management. GI bleeding can be overt (eg, visible hemorrhage such as hematemesis, hematochezia, or melena) or occult (eg, positive fecal occult blood test or iron deficiency anemia). Upper GI bleeding, which originates proximal to the ligament of Treitz, is more common than lower GI bleeding, which arises distal to the ligament of Treitz. Small bowel bleeding accounts for 5-10% of GI bleeding cases commonly manifesting as obscure GI bleeding, where the source remains unknown after complete GI tract endoscopic and imaging evaluation. CT can aid in identifying the location and cause of bleeding and is an important complementary tool to endoscopy, nuclear medicine, and angiography in evaluating patients with GI bleeding. For radiologists, interpreting CT scans in patients with GI bleeding can be challenging owing to the large number of images and the diverse potential causes of bleeding. The purpose of this pictorial review by the Society of Abdominal Radiology GI Bleeding Disease-Focused Panel is to provide a practical resource for radiologists interpreting GI bleeding CT studies that reviews the proper GI bleeding terminology, the most common causes of GI bleeding, key patient history and risk factors, the optimal CT imaging technique, and guidelines for case interpretation and illustrates many common causes of GI bleeding. A CT reporting template is included to help generate radiology reports that can add value to patient care. An invited commentary by Al Hawary is available online. Online supplemental material is available for this article. ©RSNA, 2021.

Assessment of intrathoracic lymph nodes by FDG PET/CT in patients with asbestos-related lung cancer.

BackgroundThis study explored the assessment of intrathoracic lymph node metastasis by 18F-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography computed tomography (PET/CT) in patients with asbestos-related lung cancer (ARLC).MethodsWe retrospectively reviewed the data on 35 patients with ARLC who underwent preoperative FDG-PET/CT and surgical resection between January 2012 and December 2018. We collected medical information from medical records and imaging systems and examined the FDG uptake in each lymph nodal region resected by surgery and the presence or absence of pathological lymph node metastasis.ResultsPathological lymph node metastases were detected in 14 (8.70%) of 161 nodal stations. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of FDG-PET/CT were 71.4% (10/14), 87.8% (129/147), 35.7% (10/28), 97.0% (129/133), and 86.3% (139/161), respectively. Six of the eight false-positive patients had bilateral accumulations, whereas all six true-positive patients had unilateral accumulation (P=0.006). On histopathological examination, the false-positive nodes showed disruption of lymphoid follicles in the cortex, infiltration of histiocyte-like cells in the medulla, fibrous micronodules, and severe anthracosis.ConclusionsPET/CT scans of patients with ARLC showed comparable sensitivity and specificity to those of PET/CT scans of patients with conventional lung cancer reported in the literature. Many false-positive cases also showed bilateral symmetric accumulation. This method can be used to evaluate lymph node involvement in lung cancer.

Efficacy of Hounsfield Unit of CT in Prediction of the Chemical Composition of Urinary Stones

Abstract Objectives to make a reliable correlation between the chemical composition of the urinary calculi and its Hounsfield unit on CT scan, upon which we can depend on it for prediction of the type of the urinary calculi. The prediction of the chemical structure of the stone would help us to reach a more efficient therapeutic and prophylactic plan. Methods A retrospective study was performed by interpretation of the preoperative CT scans for patients who were presented by urinary stones. Identification of the chemical structure of the calculi was implemented using Fourier Transform Infrared Spectroscopy (FT-IR spectroscopy). The laboratory report revealed multiple types of stones either of pure or mixed composition. Afterwards, a comparison was done between Hounsfield units of the stones and the chemical structure. Results The chemical structure of the urinary stones revealed four pure types of stones (Uric acid, Calcium Oxalate, Struvite and Cystine) and two types of mixed stones (mixed calcium oxalate+ Uric, and mixed calcium oxalate+ calcium phosphate). Uric acid stone had a mean Hounsfield Unit (HU) density of428 ± 81, which was quite less than the other stones, followed by struvite stones with density ranging about 714 ± 38. Mixed calcium oxalate stones could be differentiated from other types of stones like uric acid, pure calcium oxalate and struvite stones by the Hounsfield unit of Computed Tomography (the mean Hounsfield Unit was 886 ± 139 and 1427 ± 152 for mixed calcium oxalate + uric stone and mixed calcium oxalate + calcium phosphate stones respectively). Moreover, pure calcium oxalate stones were easily differentiated from all other stones using the mean Hounsfield density as it was 1158 ± 83. It was challenging only when it was compared to cystine stones, as they were quiet similar to HU value (997 ± 14). The variation of Hounsfield values among the previously mentioned stones, was statistically significant (p &amp;lt; 0.001). Conclusion The study proved that the Hounsfield Unit of CT scanning is a convenient measure to predict the chemical structure of urinary calculi.

Lung cavitation as a consequence of coronavirus-19 pneumonia.

There are reports confirming that the development of pulmonary cavities is an atypical CT finding in patients after COVID-19 pneumonia. Before the SARS-Cov-2 pandemic, we knew that the most common causes of pulmonary cavities were mycobacterial, fungal or parasitic infections. Rapidly increasing incidence of pneumonia in the course of COVID-19, and thus, tomographic examinations of the lungs proved that one of the rare complications of this disease may also be cavity development. The aim of the study was to assess the incidence of pulmonary cavities in patients after SARS-CoV-2 pneumonia. We also aimed to analyze the changes accompanying the pulmonary cavities in our patients. We performed a retrospective analysis of 206 lung CT scans of patients with SARS-CoV-2 infection. In 28 of them, prior radiological examination revealed the presence of pulmonary lesions - these patients were disqualified for the study. Out of 178 enrolled patients, 6 developed pulmonary cavities (3.37% of all cases). The most frequent changes coexisting with cavitary lesions in our material were: ground glass opacities, reticular pattern, bronchiolectasis and subpleural bands. Our study confirms the similar incidence of pulmonary cavities after COVID-19 than previously reported. It also incites the clinicians to pay attention to the possibility of the occurrence of this complication.

Structured reporting of CT scans of patients with trauma leads to faster, more detailed diagnoses: An experimental study

PurposeThis study aimed to determine whether structured reports (SRs) reduce reporting time and/or increase the level of detail for trauma CT scans compared to free-text reports (FTRs). MethodEight radiology residents used SRs and FTRs to describe 14 whole-body CT scans of patients with polytrauma in a simulated emergency room setting. Each resident created both a brief report and a detailed report for each case using one of the two formats. We measured the time to complete the detailed reports and established a scoring system to objectively measure report completeness and the level of detail. Scoring sheets divided the CT findings into main and secondary criteria. Finally, the radiological residents completed a questionnaire on their opinions of the SRs and FTRs. ResultsThe detailed SRs were completed significantly faster than the detailed FTRs (mean 19 min vs. 25 min; p < 0.001). The maximum allowance of 25 min was used for 25% of SRs and 59% of FTRs. For brief reports, the SRs contained more secondary criteria than the FTRs (p = 0.001), but no significant differences were detected in main criteria. Study participants rated their own SRs as significantly more time-efficient, concise, and clearly structured compared to the FTRs. However, SRs and FTRs were rated similarly for quality, accuracy, and completeness. ConclusionWe found that SRs for whole-body trauma CT add clinical value compared to FTRs because SRs reduce reporting time and increase the level of detail for trauma CT scans.

The impact of dose calculation algorithm for SBRT lung cancer radiotherapy treatment

Introduction: The study aimed to provide the dose accuracy effects between Anisotropic Analytical algorithm (AAA) and the deterministic solver Acuros XB (AXB) that are available on Eclipse TPS (Varian Medical Systems, Palo Alto, CA) treatment planning system (TPS). The different is due to the electron transport difference in case of small fieldsMaterial and methods: For the study non-small cell lung cancer (NSCLC) patient CT scans are used to do retrospective SBRT plans via AAA and recalculated by AXB dose calculation algorithms using Eclipse treatment planning system. The main dosimetric comparison parameters are: Conformity index (CI), Homogeneity Index (HI), Gradient Index (GI), Target mean dose and calculation time. Results: Based on the results, the CI is (1.45±0.55) to (1.85±0.7). The HI are (0.15±0.07) and (0.13±0.08), the Gradient index GI for AAA were (4.8±2.6) and for AXB reaches to (7.4±3.8) and the maximum dose for PTV are differed about 2.3% to 4.5%, mean dose and the calculation time significant similar for AAA and AXB respectively.Conclusion: As the findings using the deterministic solver AXB in calculation for case of low density like lung cases is more accurate than AAA calculation Algorithm in SBRT treatment

A Comparison of Cranial Cavity Extraction Tools for Non-contrast Enhanced CT Scans in Acute Stroke Patients

Cranial cavity extraction is often the first step in quantitative neuroimaging analyses. However, few automated, validated extraction tools have been developed for non-contrast enhanced CT scans (NECT). The purpose of this study was to compare and contrast freely available tools in an unseen dataset of real-world clinical NECT head scans in order to assess the performance and generalisability of these tools. This study included data from a demographically representative sample of 428 patients who had completed NECT scans following hospitalisation for stroke. In a subset of the scans (n = 20), the intracranial spaces were segmented using automated tools and compared to the gold standard of manual delineation to calculate accuracy, precision, recall, and dice similarity coefficient (DSC) values. Further, three readers independently performed regional visual comparisons of the quality of the results in a larger dataset (n = 428). Three tools were found; one of these had unreliable performance so subsequent evaluation was discontinued. The remaining tools included one that was adapted from the FMRIB software library (fBET) and a convolutional neural network- based tool (rBET). Quantitative comparison showed comparable accuracy, precision, recall and DSC values (fBET: 0.984 ± 0.002; rBET: 0.984 ± 0.003; p = 0.99) between the tools; however, intracranial volume was overestimated. Visual comparisons identified characteristic regional differences in the resulting cranial cavity segmentations. Overall fBET had highest visual quality ratings and was preferred by the readers in the majority of subject results (84%). However, both tools produced high quality extractions of the intracranial space and our findings should improve confidence in these automated CT tools. Pre- and post-processing techniques may further improve these results.

Association between nuclear grade of renal cell carcinoma and the aorta-lesion-attenuation-difference

Several features noted on renal mass biopsy (RMB) can influence treatment selection including tumor histology and nuclear grade. However, there is poor concordance between renal cell carcinoma (RCC) nuclear grade on RMB compared to nephrectomy specimens. Here, we evaluate the association of nuclear grade with aorta-lesion-attenuation-difference (ALAD) values determined on preoperative CT scan. A retrospective review of preoperative CT scans and surgical pathology was performed on patients undergoing nephrectomy for solid renal masses. ALAD was calculated by measuring the difference in Hounsfield units (HU) between the aorta and the lesion of interest on the same image slice on preoperative CT scan. The discriminative ability of ALAD to differentiate low-grade (nuclear grade 1 and 2) and high-grade (nuclear grade 3 and 4) tumors was evaluated by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under curve (AUC) using ROC analysis. Sub-group analysis by histologic sub-type was also performed. A total of 368 preoperative CT scans in patients with RCC on nephrectomy specimen were reviewed. Median patient age was 61years (IQR 52-68). The majority of patients were male, 66% (243/368). Tumor histology was chromophobe RCC in 7.6%, papillary RCC in 15.5%, and clear cell RCC in 76.9%. The majority, 69.3% (253/365) of tumors, were stage T1a. Nuclear grade was grade 1 in 5.46% (19/348), grade 2 in 64.7% (225/348), grade 3 in 26.2% (91/348), and grade 4 in 3.2% (11/348). Nephrographic ALAD values for grade 1, 2, 3, and 4 were 73.7, 46.5, 36.4, and 43.1, respectively (p = 0.0043). Nephrographic ALAD was able to differentiate low-grade from high-grade RCC with a sensitivity of 32%, specificity of 89%, PPV of 86%, and NPV of 36%. ROC analysis demonstrated the predictive utility of nephrographic ALAD to predict high- versus low-grade RCC with an AUC of 0.60 (95% CI 0.51-0.69). ALAD was significantly associated with nuclear grade in our nephrectomy series. Strong specificity and PPV for the nephrographic phrase demonstrate a potential role for ALAD in the pre-operative setting that may augment RMB findings in assessing nuclear grade of RCC. Although this association was statistically significant, the clinical utility is limited at this time given the results of the statistical analysis (relatively poor ROC analysis). Sub-group analysis by histologic subtype yielded very similar diagnostic performance and limitations of ALAD. Further studies are necessary to evaluate this relationship further.

US-guided high-intensity focused ultrasound (HIFU) of abdominal tumors: outcome, early ablation-related laboratory changes and inflammatory reaction. A single-center experience from Germany

Introduction High-intensity focused ultrasound (HIFU) is an innovative noninvasive procedure for local ablation of different benign and malignant tumors. Preliminary data of animal studies suggest an ablation-associated immune response after HIFU that is induced by cell necrosis and release of intracellular components. The aim of this study is to evaluate if a HIFU-induced early sterile inflammatory reaction is initiated after ablation of uterine fibroids (UF) and pancreatic carcinoma (PaC) which might contribute to the therapeutic effect. Material and methods A hundred patients with PaC and 30 patients with UF underwent US-guided HIFU treatment. Serum markers of inflammation (leukocytes, CRP, IL-6) and LDH in both collectives as well as tumor markers CA 19-9, CEA and CYFRA in PaC patients were determined in sub-cohorts before and directly after HIFU (0, 2, 5 and 20 h post-ablation) as well as at 3, 6, 9 and 12 months follow-up. Peri-/post interventional imaging included contrast-enhanced MRI of both cohorts and an additional CT scan of PaC patients. Results An early post-ablation inflammatory response was observed in both groups with a significant increase of leukocytes, CRP and LDH within the first 20 h after HIFU. Interestingly, IL-6 was increased at 20 h after HIFU in PaC patients. A significant reduction of tumor volumes was observed during one year follow-up (p < .001) for both tumor entities demonstrating effective treatment outcome. Conclusion Tumor ablation with HIFU induces an early sterile inflammation that might serve as a precondition for long-term tumor immunity and a sustainable therapeutic effect.

Hyperdense middle cerebral artery sign and response to combination of mechanical Thrombectomy plus intravenous thrombolysis in acute stroke patients

Background and purposeCombining intra-arterial mechanical thrombectomy (IAMT) and intravenous thrombolysis (IVT) has shown to have an excellent recanalization rate and better clinical outcome in acute ischemic stroke (AIS) patients. Hyperdense middle cerebral artery sign (HMCAS) on pretreatment non-contrast head CT scan of AIS patients is one of the early ischemic radiological findings in middle cerebral artery territory AIS. We aimed to evaluate whether the presence of HMCAS predicts the outcome of AIS patients receiving combination therapy with IAMT and IVT. MethodsWe retrospectively reviewed medical records and cerebrovascular images of the patients treated with IAMT and IVT for AIS in our center. Patients with occlusion in the terminal internal carotid artery or middle cerebral artery on pretreatment CT angiogram of the head were included. Clinical outcome was compared between subjects with HMCAS and those without. Modified Rankin Score (mRS) and symptomatic intracranial hemorrhage (sICH) were used as measures of efficacy and safety, respectively. ResultsOf 93 patients, 46 (49%) had HMCAS on their initial head CT scan. Both groups had comparable baseline characteristics and stroke severity. After adjusting for age, NIHSS score, time from symptom onset to starting IVT, and history of diabetes mellitus in multivariate logistic regression analysis, there was no difference in terms of a poor outcome (mRS >2) (OR = 0.5 [CI 0.2–1.4], p = 0.188) or rate of sICH (OR = 3.3 [CI 0.6–19.0], p = 0.190) between the two groups. ConclusionsHMCAS is not a predictor of poor outcome in AIS patients receiving combination therapy with IAMT and IVT and does not affect treatment safety.

How specific are patient-specific simulations? Analyzing the accuracy of 3D-printing and modeling to create patient-specific rehearsals for complex urological procedures.

In the field of urology, 3D printing and modeling are now regularly utilized to enhance pre-operative planning, surgical training, patient-specific rehearsals (PSR), and patient education and counseling. Widespread accessibility and affordability of such technologies necessitates development of quality control measures to confirm the anatomical accuracy of these tools. Herein, we present three methods utilized to evaluate the anatomical accuracy of hydrogel PSR, developed using 3D printing and molding for pre-operative surgical rehearsals, of robotic-assisted partial nephrectomy (RAPN) and percutaneous nephrolithotomy (PCNL). Virtual computer-aided designs (CADs) of patient anatomy were created through segmentation of patient CT scan images. Ten patient-specific RAPN and PCNL hydrogel models were CT scanned and segmented to create a corresponding model CAD. The part compare tool (3-matic, Materialize), point-to-point measurements, and Dice similarity coefficient (DSC) analyzed surface geometry, alignment, and volumetric overlap of each model component. Geometries of the RAPN parenchyma, tumor, artery, vein, and pelvicalyceal system lay within an average deviation of 2.5mm (DSC = 0.70) of the original patient geometry and 5mm (DSC = 0.45) of the original patient alignment. Similarly, geometries of the PCNL pelvicalyceal system and stone lay within 2.5mm (DSC = 0.6) and within 15mm (16% deviation) in alignment. This process enabled the refinement of our modeling process to fabricate anatomically accurate RAPN and PCNL PSR. As 3D printing and modeling continues to have a greater impact on patient care, confirming anatomical accuracy should be introduced as a quality control measure prior to use for patient care.