CT Scans Of Patients Research Articles

Comparison of Image Quality and Radiation Dose in Pediatric Temporal Bone CT Using Photon-Counting Detector CT and Energy-Integrating Detector CT.

Currently, there is a lack of research directly comparing photon-counting detector CT (PCD-CT) and energy-integrating detector CT (EID-CT) in pediatric temporal bone CT imaging. The purpose of this study was to compare the image quality and radiation dose of temporal bone CT scans in pediatric patients acquired with PCD-CT and EID-CT. The retrospective study included a total of 110 pediatric temporal bone CT scans (PCD-CT, n = 52; EID-CT, n = 58). Two independent readers evaluated the spatial resolution of 4 anatomic structures (tympanic membrane, incudostapedial joint, stapedial crura, and cochlear modiolus) and overall image quality by using a 4-point scale. Interreader agreement was assessed. Dose-length product for each CT was compared, and subgroup analyses were performed based on age (younger than 3 years, 3-5 years, 6-11 years, and 12 years and above). PCD-CT demonstrated statistically significantly higher scores than EID-CT for all items (tympanic membrane, 2.9 versus 2.4; incudostapedial joint, 3.6 versus 2.6; stapedial crura, 3.2 versus 2.4; cochlear modiolus, 3.4 versus 2.8; overall image quality, 3.6 versus 2.8; P < .05). Interreader agreement ranged from good to excellent (interclass correlation coefficients, 0.6-0.81). PCD-CT exhibited a 43% dose reduction compared with EID-CT, with a particularly substantial reduction of over 70% in the subgroups of children younger than 6 years. PCD temporal bone CT achieves significantly superior imaging quality at a lower radiation dose compared with EID-CT.

Reliability of the transverse acetabular ligament as a landmark for functional cup anteversion in total hip arthroplasty.

The transverse acetabular ligament (TAL) can be a useful and reproducible landmark in the orientation of the acetabular cup in total hip arthroplasty (THA). Its role in guiding cup orientation when aiming to implant in a functional anteversion orientation is unclear. The aim of this study was to assess the relationship between the TAL and the planned acetabular cup anteversion when implanted in a function orientation. In a retrospective study the anteversion of the TAL in the contralateral un-replaced hip was measured in CT scans of patients undergoing THA and compared to the functional cup anteversion using the patient-specific spinopelvic parameters. Comparative measurements of the native acetabular version were made from the superior rim to the inferior rim and at 10 mm intervals between the 2, all in reference to the anterior pelvic plane. 96 hips were measured. The mean TAL anteversion angle was 17.2° ± 4.5°. The mean planned acetabular cup anteversion angle was 26.3° ± 4.7°. Pearson's correlation coefficient of this measurement with the TAL was -0.03 (p = 0.769). There was a significant difference between the planned acetabular cup anteversion and the measurement of the TAL (p < 0.0001). If cups are implanted parallel to the TAL, almost 80% will be >5° different to targeted functional cup version. It should be aimed to implant cups with more anteversion than the TAL indicates.

Synthesizing High-Resolution Dual-Energy Radiographs from Coronary Artery Calcium CT Images.

Generating realistic radiographs from CT is mainly limited by the native spatial resolution of the latter. Here we present a general approach for synthesizing high-resolution digitally reconstructed radiographs (DRRs) from an arbitrary resolution CT volume. Our approach is based on an upsampling framework where tissues of interest are first segmented from the original CT volume and then upsampled individually to the desired voxelization (here ~1 mm → 0.2 mm). Next, we create high-resolution 2D tissue maps by cone-beam projection of individual tissues in the desired radiography direction. We demonstrate this approach on a coronary artery calcium (CAC) patient CT scan and show that our approach preserves individual tissue volumes, yet enhances the tissue interfaces, creating a sharper DRR without introducing artificial features. Lastly, we model a dual-layer detector to synthesize high-resolution dual-energy (DE) anteroposterior and lateral radiographs from the patient CT to visualize the CAC in 2D through material decomposition. On a general level, we envision that this approach is valuable for creating libraries of synthetic yet realistic radiographs from corresponding large CT datasets.

Potential of photon counting computed tomography derived spectral reconstructions to reduce beam-hardening artifacts in chest CT

PurposeAim of the recent study is to point out a method to optimize quality of CT scans in oncological patients with port systems. This study investigates the potential of photon counting computed tomography (PCCT) for reduction of beam hardening artifacts caused by port-implants in chest imaging by means of spectral reconstructions. MethodIn this retrospective single-center study, 8 ROIs for 19 spectral reconstructions (polyenergetic imaging, monoenergetic reconstructions from 40 to 190 keV as well as iodine maps and virtual non contrast (VNC)) of 49 patients with pectoral port systems undergoing PCCT of the chest for staging of oncologic disease were measured. Mean values and standard deviation (SD) Hounsfield unit measurements of port-chamber associated hypo- and hyperdense artifacts, bilateral muscles and vessels has been carried out. Also, a structured assessment of artifacts and imaging findings was performed by two radiologists. ResultsA significant association of keV with iodine contrast as well as artifact intensity was noted (all p < 0.001). In qualitative assessment, utilization of 120 keV monoenergetic reconstructions could reduce severe and pronounced artifacts completely, as compared to lower keV reconstructions (p < 0.001). Regarding imaging findings, no significant difference between monoenergetic reconstructions was noted (all p > 0.05). In cases with very high iodine concentrations in the subclavian vein, image distortions were noted at 40 keV images (p < 0.01). ConclusionsThe present study demonstrates that PCCT derived spectral reconstructions can be used in oncological imaging of the thorax to reduce port-derived beam-hardening artefacts. When evaluating image data sets within a staging, it can be particularly helpful to consider the 120 keV VMIs, in which the artefacts are comparatively low.

The Association Between Craniofacial Fracture Patterns and Traumatic Optic Neuropathy.

Traumatic optic neuropathy (TON) is a rare but potentially devastating complication of craniofacial trauma. Approximately half of patients with TON sustain permanent vision loss. In this study, we sought to identify the most common fracture patterns associated with TON. We performed a retrospective review of craniomaxillofacial CT scans of trauma patients who presented to the R Adams Cowley Shock Trauma Center from 2015 to 2017. Included were adult patients who had orbital fractures with or without other facial fractures. Patients diagnosed with TON by a formal ophthalmologic examination were analyzed. Craniofacial fracture patterns were identified. Bivariate analysis and multivariate logistic regression were performed to identify craniofacial fracture patterns most commonly associated with TON. A total of 574 patients with orbital fractures who met inclusion criteria [15 (2.6%)] were diagnosed with TON. The median [interquartile range (IQR)] age was 44 (28-59) years. Patients with optic canal fractures and sphenoid sinus fractures had greater odds of TON compared with patients who did not have these fracture types [adjusted odds ratio (aOR) 95% confidence interval (CI) 31.8 (2.6->100), 8.1 (2.7-24.4), respectively]. Patients who sustain optic canal and sphenoid sinus fractures in the setting of blunt facial trauma are at increased odds of having a TON. Surgeons and other physicians involved in the care of these patients should be aware of this association.

Association between thoracic density and area with COVID-19 outcomes

BackgroundThe relationship between sarcopenia and the consequences of COVID-19 is not yet fully understood. It is noteworthy that information about muscle status can be easily retrieved by segmenting specific regions of skeletal muscles on CT scans. Our aim in this study was to investigate the relationship between sarcopenia and the consequences of COVID-19.MethodsIn this analytical cross-sectional study, 338 patients with COVID-19 who had a positive PCR test for COVID-19 and underwent chest CT scan in Loghman-e-Hakim Hospital from July to September 2021 were evaluated. Age, sex, background diseases, mechanical ventilation, duration of hospitalization, as well as lab tests, ICU admission and mortality were extracted from patient records. The severity of COVID-19 disease and the area and density of paraspinal muscles at the level of T5 and T12 vertebrae were evaluated through chest CT scans.ResultsLength of stay had significant relationship with T5 density (1.15 (< 0.001)) and T12 density (1.24 (< 0.001). The mean of T12 area (3.35 (P = 0.005) and T12 density 4.59 (P = 0.012) were significantly lower in ICU admitted. There was a significant relationship between mortality and age, cardiovascular disorders, COPD, underlying disease, length of stay, WBC and lymphocyte levels, as well as the severity of the disease.ConclusionsBased on the results of this study, we can infer that the use of CT scan in patients with COVID-19 and the determination of muscle area and density can predict the consequences of COVID-19, such as a longer duration of hospitalization, the need for admission to the ICU, and mortality.

Just give the contrast? Appraisal of guidelines on intravenous iodinated contrast media use in patients with kidney disease

ObjectiveTo appraise the quality of guidelines on intravenous iodinated contrast media (ICM) use in patients with kidney disease, and to compare the recommendations among them.MethodsWe searched four literature databases, eight guideline libraries, and ten homepages of radiological societies to identify English and Chinese guidelines on intravenous ICM use in patients with kidney disease published between January 2018 and June 2023. The quality of the guidelines was assessed with the Scientific, Transparent, and Applicable Rankings (STAR) tool.ResultsTen guidelines were included, with a median STAR score of 46.0 (range 28.5–61.5). The guidelines performed well in “Recommendations” domain (31/40, 78%), while poor in “Registry” (0/20, 0%) and “Protocol” domains (0/20, 0%). Nine guidelines recommended estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73 m2 as the cutoff for referring patients to discuss the risk-benefit balance of ICM administration. Three guidelines further suggested that patients with an eGFR < 45 mL/min/1.73 m2 and high-risk factors also need referring. Variable recommendations were seen in the acceptable time interval between renal function test and ICM administration, and that between scan and repeated scan. Nine guidelines recommended to use iso-osmolar or low-osmolar ICM, while no consensus has been reached for the dosing of ICM. Nine guidelines supported hydration after ICM use, but their protocols varied. Drugs or blood purification therapy were not recommended as preventative means.ConclusionGuidelines on intravenous ICM use in patients with kidney disease have heterogeneous quality. The scientific societies may consider joint statements on controversial recommendations for variable timing and protocols.Critical relevance statementThe heterogeneous quality of guidelines, and their controversial recommendations, leave gaps in workflow timing, dosing, and post-administration hydration protocols of contrast-enhanced CT scans for patients with kidney diseases, calling for more evidence to establish a safer and more practicable workflow.Key points• Guidelines concerning iodinated contrast media use in kidney disease patients vary.• Controversy remains in workflow timing, contrast dosing, and post-administration hydration protocols.• Investigations are encouraged to establish a safer iodinated contrast media use workflow.Graphical

Repair of Inferior Alveolar Nerve in Orthognathic Surgery Simulator (RIANOS): A Novel, Open-Source, Combined 3D Printed, and Ex-Vivo Chicken Sciatic Nerve Training Model

Study Design Face and content validation of a surgical simulation model. Objective Accidental transection of the inferior alveolar nerve (IAN) during bilateral sagittal split osteotomies (BSSO) has a reported incidence of up to 7%, determining important sensory disturbances in patients. Proper repair demands the need of microsurgical anastomosis skills. No previous training models have been described to simulate this. Therefore, we present a validated simulation model for intraoral repair of transected IAN. Methods A CT scan of an orthognathic surgery patient was modified and a 3D model of a mandible with BSSO was printed. Chicken thigh anatomy was reviewed, and 2.5 mm sciatic nerves were dissected and mounted in the model. In order to simulate intraoral work depth, it was put inside a dental phantom or medical glove box. The model was tested by a group of experts (n = 12), simulating a transected IAN repair inside the mouth with both loupes and a double visor surgical training microscope. A survey was conducted to assess Face and Content validity. Results The model was named RIANOS after Repair of Inferior Alveolar Nerve in Orthognathic Surgery Simulator. The printing cost of each model was approximately US$3 and the design file is open-source and available for download. All experts “Strongly Agreed” that the model was useful for training inferior alveolar nerve microsurgical repair and would consider implementing it with their residents. Conclusions We developed a low cost, reproducible, open-source simulator for IAN injury repair training during BSSO. Face and Content validity was achieved through evaluation by a group of experts.

The Relationship Between Intra-articular Fracture Energy and a Patient's Inflammatory Response.

Prior studies have demonstrated elevated inflammatory cytokine concentrations in the synovial fluid of articular fracture patients postinjury. Similarly, CT-based fracture energy measurements have been correlated with posttraumatic osteoarthritis risk after pilon fracture. The purpose of this study was to determine the associations between synovial fluid cytokine levels, fracture energy, and overall trauma to the body in articular fracture patients. Acute tibial plateau, tibial plafond, and rotational ankle fracture patients were prospectively enrolled from December 2011 through January 1, 2019. Synovial fluid concentrations of interleukin-1 beta, interleukin-1 receptor antagonist, IL-6, IL-8, IL-10, matrix metallopeptidase-1, MMP-3, and MMP-13 were quantified. Patient CT scans were used to calculate fracture energy. The Injury Severity Score (ISS) was used to relate cytokine levels to whole-body injury severity. Spearman rho correlation coefficients were calculated to assess the relationship between injury severity metrics and synovial fluid cytokine, chemokine, and matrix metallopeptidase concentrations. Eighty-seven patients were enrolled with 42 had a tibial plateau fractures (OTA/AO 41B1-2, 41B2-14, 41B3-3, 41C1-3, 41C2-4, 41C3-16), 24 patients had a tibial plafond fracture (OTA/AO 43B1-2, 43B2-4, 43B3-5, 43C1-2, 43C2-3, 43C3-8), and 21 had a rotational ankle fracture (OTA/AO 44B1-3, 44B2-3, 44B3-6, 44C1-4, 44C2-5). Fracture energy significantly differed between fracture patterns, with ankle fractures involving substantially less fracture energy (median = 2.92 J) than plafond (10.85 J, P < 0.001) and plateau fractures (13.05 J, P < 0.001). After adjustment for multiple comparisons, MMP-3 was significantly correlated with transformed fracture energy (r = 0.41, 95% confidence interval [CI], 0.22-0.58, P < 0.001), while IL-1β was significantly correlated with the Injury Severity Score (Spearman ρ = 0.31, 95% CI, 0.08-0.49, P = 0.004). Synovial fluid MMP-3 concentration was significantly correlated with CT-quantified fracture energy in intra-articular fracture patients. Given that in clinical practice fracture energy tends to correlate with posttraumatic osteoarthritis risk, MMP-3 may warrant further investigation for its role in posttraumatic osteoarthritis development after articular fracture. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Blood flow and emboli transport patterns during venoarterial extracorporeal membrane oxygenation: A computational fluid dynamics study

ProblemDespite advances in Venoarterial Extracorporeal Membrane Oxygenation (VA-ECMO), a significant mortality rate persists due to complications. The non-physiological blood flow dynamics of VA-ECMO may lead to neurological complications and organ ischemia. Continuous retrograde high-flow oxygenated blood enters through a return cannula placed in the femoral artery which opposes the pulsatile deoxygenated blood ejected by the left ventricle (LV), which impacts upper body oxygenation and subsequent hyperoxemia. The complications underscore the critical need to comprehend the impact of VA-ECMO support level and return cannula size, as mortality remains a significant concern. AimThe aim of this study is to predict and provide insights into the complications associated with VA-ECMO using computational fluid dynamics (CFD) simulations. These complications will be assessed by characterising blood flow and emboli transport patterns through a comprehensive analysis of the influence of VA-ECMO support levels and arterial return cannula sizes. MethodsPatient-specific 3D aortic and major branch models, derived from a male patient's CT scan during VA-ECMO undergoing respiratory dysfunction, were analyzed using CFD. The investigation employed species transport and discrete particle tracking models to study ECMO blood (oxygenated) mixing with LV blood (deoxygenated) and to trace emboli transport patterns from potential sources (circuit, LV, and aorta wall). Two cannula sizes (15 Fr and 19 Fr) were tested alongside varying ECMO pump flow rates (50%, 70%, and 90% of the total cardiac output). ResultsCannula size did not significantly affect oxygen transport. At 90% VA-ECMO support, all arteries distal to the aortic arch achieved 100% oxygen saturation. As support level decreased, oxygen transport to the upper body also decreased to a minimum saturation of 73%. Emboli transport varied substantially between emboli origin and VAECMO support level, with the highest risk of cerebral emboli coming from the LV with a 15 Fr cannula at 90% support. ConclusionArterial return cannula sizing minimally impacted blood oxygen distribution; however, it did influence the distribution of emboli released from the circuit and aortic wall. Notably, it was the support level alone that significantly affected the mixing zone of VA-ECMO and cardiac blood, subsequently influencing the risk of embolization of the cardiogenic source and oxygenation levels across various arterial branches.

The paediatric polytrauma CT-indication (PePCI)-score–Development of a prognostic model to reduce unnecessary CT scans in paediatric trauma patients

BackgroundWhole-Body CT (WBCT) is frequently used in emergency situations for promptly diagnosing paediatric polytrauma patients, given the challenges associated with obtaining precise details about the mechanism and progression of trauma. However, WBCT does not lead to reduced mortality in paediatric patients, but is associated with high radiation exposure. We therefore wanted to develop a screening tool for CT demand-driven emergency room (ER)-trauma diagnostic to reduce radiation exposure in paediatric patients. MethodsA retrospective study in a Level I trauma centre in Germany was performed. Data from 344 paediatric emergency patients with critical mechanism of injury who were pre-announced by the ambulance for the trauma room were collected. Patients’ symptoms, clinical examination, extended Focused Assessment with Sonography for Trauma (eFAST), routinely, laboratory tests and blood gas and - when obtained - WBCT images were analysed. To identify potential predictors of severe injuries (ISS > 23), 300 of the 344 cases with complete data were subjected to regression analyses model. ResultsMultiple regression analysis identified cGCS, base excess (BE), medically abnormal results from eFAST screening, initial unconsciousness, and injuries involving three or more body regions as significant predictors for a screening tool for decision-making to perform WBCT or selective CT. The developed Paediatric polytrauma CT-Indication (PePCI)-Score was divided into three risk categories and achieved a sensitivity of 87 % and a specificity of 71 % when comparing the low and medium risk groups with the high risk group. Comparing only the low-risk group with the high-risk group for the decision to perform WBCT, 32/35 (91 %) of patients with an ISS >23 were correctly identified, as were 124/137 (91 %) with lower ISS scores. ConclusionWith the newly developed PePCI-Score, the frequency of WBCT in a paediatric emergency patients collective can be significantly reduced according to our data. After prospective validation, the initial assessment of paediatric trauma patients in the future could be made not only by the mechanism of injury, but also by the new PePCI-Score, deriving on clinical findings after thorough clinical assessment and the discretion of the trauma team.

Improving the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm using DenseNet

IntroductionThinner slices are more susceptible in detecting small lesions but suffer from higher statistical fluctuation. This work aimed to reduce image noise in multiphase contrast-enhanced CT reconstructed with slice thickness thinner than the clinical setting (i.e., 5 mm) using convolutional neural network (CNN) for enabling better detection of hypo-vascular liver metastasis. MethodsA DenseNet model was used to generate noise map for multiphase CT reconstructed with slice thickness of 2.5 mm and 1.25 mm. Image denoising was conducted by subtracting the CNN-generated noise map from CT images with reduced photon flux due to thinner slice thickness. The performance of DenseNet was evaluated on CT scans of electron density phantoms and patients with hypovascular liver metastases less than 1.5 cm in terms of Hounsfield Unit (HU) variation, statistical fluctuation, and contrast-to-noise ratio (CNR). ResultsThe phantom study demonstrated that the CNN-based denoising method was able to reduce statistical fluctuation in CT images reconstructed with slice thickness of 2.5 mm and 1.25 mm without causing significant edge blurring or variation in HU values. With regards to patient study, it was found that the denoised 2.5-mm and 1.25-mm slices had higher CNR than the conventional 5-mm slices for hypo-vascular liver metastases in all 4 phases of multiphase CT. ConclusionOur results demonstrated that the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm could be improved by using the CNN-based denoising method. Implications for practiceReconstruction slice thickness has a strong influence on the image quality of CT imaging. A CNN-based denoising method was used in this work to reduce the image noise in multiphase contrast-enhanced CT reconstructed with slice thickness less than 5 mm.

Exploring the Diagnostic Dilemma of Indeterminate Pulmonary Nodules in Patients with Primary Sarcoma of Bone.

Bone sarcomas are known to have a predilection for pulmonary metastasis. Surveillance protocols are thus focused on periodic chest imaging, typically with CT scan. Pulmonary nodules can be easily identified with this modality, but smaller nodules are not readily biopsied and may not represent metastatic disease. These are called indeterminate. The natural history of indeterminate nodules in a bone sarcoma population and factors associated with progression to true metastatic disease are not clearly defined. All bone sarcoma patients treated at a single institution from 2010 to 2020 were eligible for inclusion. We treated 327 patients over this period; 119 were excluded for age less than 16 years, 31 were excluded for evident metastatic disease at presentation, and 60 were excluded for incomplete clinical follow-up or CT chest imaging either at staging or in surveillance. We assessed chest CT images for presence of pulmonary nodules and selected variables both at the staging and on surveillance images. Nodules were considered metastatic if proven histologically with a biopsy or by clinical interpretation by the multidisciplinary sarcoma team. Clinical and imaging factors were assessed for the association of indeterminate nodule progression to true metastatic disease. Seventy three of the 117 patients had indeterminate nodules on their staging CT scan; 41.1% of those patients progressed to metastatic disease compared to 43.2% of the patients that did not have indeterminate nodules on staging CT. Fifty eight of the 117 patients developed indeterminate nodules on surveillance chest CT, and 55.2% of those patients progressed to metastatic disease. There were no clinical or imaging factors that predicted the development of metastatic disease in the group that had indeterminate nodules at presentation; however, the number and size of nodules did correlate with progression to metastasis in those that developed indeterminate nodules on surveillance. Indeterminate pulmonary nodules are common on staging CT scans in patients with a bone sarcoma. The presence or absence of these indeterminate nodules was not predictive of progression to true metastatic disease in this cohort. However, the development of indeterminate nodules on surveillance imaging was associated with progression to metastatic disease with the size and number of nodules being important factors.

Familial pancreatic cancer: a long fruitful journey.

In the early years of my GI fellowship, a healthy 40-year-old man came to my clinic and announced that he was going to die of pancreatic cancer. His brothers, father and uncles had all died of the disease; he felt his fate was inescapable. I asked whether his family members had seen doctors or had any tests. His answer was yes to both. Even so, doctors could not diagnose the pancreatic cancer at early stages. CT scans were always negative. I thought to myself, in order to help this patient-CT scans may not be reliable for early detection. Perhaps other methods of imaging the pancreas might be of more benefit. This patient opened a door that led to a 30-year journey of trying to detect pancreatic cancer at earlier stages when it is curable.

Clinical evaluation of pulmonary quantitative computed tomography parameters for diagnosing eosinophilic chronic obstructive pulmonary disease: Characteristics and diagnostic performance.

To investigate the characteristics and diagnostic performance of quantitativecomputed tomography (QCT) parameters in eosinophilic chronic obstructive pulmonary disease (COPD) patients. High-resolution CT scans of COPD patients were retrospectively analyzed, and various emphysematous parenchyma measurements, including lung volume (LC), lung mean density (LMD), lung standard deviation (LSD), full-width half maximum (FWHM), and lung relative voxel number (LRVN) were performed. The QCT parameters were compared between eosinophilic and noneosinophilic COPD patients, using a definition of eosinophilic COPD as blood eosinophil values ≥ 300 cells·µL-1 on at least three times. Receiver operating characteristic curves and area under the curve (ROC-AUC) and python were used to evaluate discriminative efficacy of QCT. Noneosinophilic COPD patients had a significantly lower TLMD (-846.3 ± 47.9 Hounsfield Unit[HU]) and TFWHM(162.5 ± 30.6 HU) compared to eosinophilic COPD patients (-817.8 ± 54.4, 177.3 ± 33.1 HU, respectively) (p = 0.018, 0.03, respectively). Moreover, the total LC (TLC) and TLSD were significantly lower in eosinophilic COPD group (3234.4 ± 1145.8, 183.8 ± 33.9 HU, respectively) than the noneosinophilic COPD group (5600.2 ± 1248.4, 203.5 ± 20.4 HU, respectively) (p = 0.009, 0.002, respectively). The ROC-AUC values for TLC, TLMD, TLSD, and TFWHM were 0.91 (95% confidence interval [CI], 0.828-0.936), 0.66 (95% CI, 0.546-0.761), 0.64 (95% CI, 0.524-0.742), and 0.63 (95% CI, 0.511-0.731), respectively. When the TLC value was 4110 mL, the sensitivity was 90.7% (95% CI, 79.7-96.9), specificity was 77.8% (95% CI, 57.7-91.4) and accuracy was 86.4%. Notably, TLC demonstrated the highest discriminative efficiency with an F1 Score of 0.79, diagnostic Odds Ratio of 34.3 and Matthews Correlation Coefficient of 0.69, surpassing TLMD (0.55, 3.66, 0.25), TLSD (0.56, 3.95, 0.26), and TFWHM (0.56, 4.16, 0.33). Eosinophilic COPD patients exhibit lower levels of emphysema and a more uniform density distribution throughout the lungs compared to noneosinophilic COPD patients. Furthermore, TLC demonstrated the highest diagnostic efficiency and may serve as a valuable diagnostic marker for distinguishing between the two groups.

Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM)

PurposeFrequent CT scans to quantify lung involvement in cystic lung disease increases radiation exposure. Beam shaping energy filters can optimize imaging properties at lower radiation dosages. The aim of this study is to investigate whether use of SilverBeam filter and deep learning reconstruction algorithm allows for reduced radiation dose chest CT scanning in patients with lymphangioleiomyomatosis (LAM).Material and methodsIn a single-center prospective study, 60 consecutive patients with LAM underwent chest CT at standard and ultra-low radiation doses. Standard dose scan was performed with standard copper filter and ultra-low dose scan was performed with SilverBeam filter. Scans were reconstructed using a soft tissue kernel with deep learning reconstruction (AiCE) technique and using a soft tissue kernel with hybrid iterative reconstruction (AIDR3D). Cyst scores were quantified by semi-automated software. Signal-to-noise ratio (SNR) was calculated for each reconstruction. Data were analyzed by linear correlation, paired t-test, and Bland–Altman plots.ResultsPatients averaged 49.4 years and 100% were female with mean BMI 26.6 ± 6.1 kg/m2. Cyst score measured by AiCE reconstruction with SilverBeam filter correlated well with that of AIDR3D reconstruction with standard filter, with a 1.5% difference, and allowed for an 85.5% median radiation dosage reduction (0.33 mSv vs. 2.27 mSv, respectively, p < 0.001). Compared to standard filter with AIDR3D, SNR for SilverBeam AiCE images was slightly lower (3.2 vs. 3.1, respectively, p = 0.005).ConclusionSilverBeam filter with deep learning reconstruction reduces radiation dosage of chest CT, while maintaining accuracy of cyst quantification as well as image quality in cystic lung disease.Clinical relevance statementRadiation dosage from chest CT can be significantly reduced without sacrificing image quality by using silver filter in combination with a deep learning reconstructive algorithm.Key Points• Deep learning reconstruction in chest CT had no significant effect on cyst quantification when compared to conventional hybrid iterative reconstruction.• SilverBeam filter reduced radiation dosage by 85.5% compared to standard dose chest CT.• SilverBeam filter in coordination with deep learning reconstruction maintained image quality and diagnostic accuracy for cyst quantification when compared to standard dose CT with hybrid iterative reconstruction.Graphical abstract

Deep learning-enabled detection of hypoxic-ischemic encephalopathy after cardiac arrest in CT scans: a comparative study of 2D and 3D approaches.

To establish a deep learning model for the detection of hypoxic-ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format. 168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.6%) without signs of HIE. These images were randomly divided into a training and a test set, and five deep learning models based on based on Densely Connected Convolutional Networks (DenseNet121) were trained and validated using different image input formats (2D and 3D images). All optimized stacked 2D and 3D networks could detect signs of HIE. The networks based on the data as 2D image data stacks provided the best results (S100: AUC: 94%, ACC: 79%, S50: AUC: 93%, ACC: 79%). We provide visual explainability data for the decision making of our AI model using Gradient-weighted Class Activation Mapping. Our proof-of-concept deep learning model can accurately identify signs of HIE on CT images. Comparing different 2D- and 3D-based approaches, most promising results were achieved by 2D image stack models. After further clinical validation, a deep learning model of HIE detection based on CT images could be implemented in clinical routine and thus aid clinicians in characterizing imaging data and predicting outcome.

Development and Validation of Deep Learning-Based Automated Detection of Cervical Lymphadenopathy in Patients with Lymphoma for Treatment Response Assessment: A Bi-institutional Feasibility Study.

The purpose is to train and evaluate a deep learning (DL) model for the accurate detection and segmentation of abnormal cervical lymph nodes (LN) on head and neck contrast-enhanced CT scans in patients diagnosed with lymphoma and evaluate the clinical utility of the DL model in response assessment. This retrospective study included patients who underwent CT for abnormal cervical LN and lymphoma assessment between January 2021 and July 2022. Patients were grouped into the development (n = 76), internal test 1 (n = 27), internal test 2 (n = 87), and external test (n = 26) cohorts. A 3D SegResNet model was used to train the CT images. The volume change rates of cervical LN across longitudinal CT scans were compared among patients with different treatment outcomes (stable, response, and progression). Dice similarity coefficient (DSC) and the Bland-Altman plot were used to assess the model's segmentation performance and reliability, respectively. No significant differences in baseline clinical characteristics were found across cohorts (age, P = 0.55; sex, P = 0.13; diagnoses, P = 0.06). The mean DSC was 0.39 ± 0.2 with a precision and recall of 60.9% and 57.0%, respectively. Most LN volumes were within the limits of agreement on the Bland-Altman plot. The volume change rates among the three groups differed significantly (progression (n = 74), 342.2%; response (n = 8), - 79.2%; stable (n = 5), - 8.1%; all P < 0.01). Our proposed DL segmentation model showed modest performance in quantifying the cervical LN burden on CT in patients with lymphoma. Longitudinal changes in cervical LN volume, as predicted by the DL model, were useful for treatment response assessment.

Radiomics in differential diagnosis of Wilms tumor and neuroblastoma with adrenal location in children.

Machine learning methods can be applied successfully to various medical imaging tasks. Our aim with this study was to build a robust classifier using radiomics and clinical data for preoperative diagnosis of Wilms tumor (WT) or neuroblastoma (NB) in pediatric abdominal CT. This is a single-center retrospective study approved by the Institutional Ethical Board. CT scans of consecutive patients diagnosed with WT or NB admitted to our hospital from January 2005 to December 2021 were evaluated. Three distinct datasets based on clinical centers and CT machines were curated. Robust, non-redundant, high variance, and relevant radiomics features were selected using data science methods. Clinically relevant variables were integrated into the final model. Dice score for similarity of tumor ROI, Cohen's kappa for interobserver agreement among observers, and AUC for model selection were used. A total of 147 patients, including 90 WT (mean age 34.78 SD: 22.06months; 43 male) and 57 NB (mean age 23.77 SD:22.56months; 31 male), were analyzed. After binarization at 24months cut-off, there was no statistically significant difference between the two groups for age (p = .07) and gender (p = .54). CT clinic radiomics combined model achieved an F1 score of 0.94, 0.93 accuracy, and an AUC 0.96. In conclusion, the CT-based clinic-radiologic-radiomics combined model could noninvasively predict WT or NB preoperatively. Notably, that model correctly predicted two patients, which none of the radiologists could correctly predict. This model may serve as a noninvasive preoperative predictor of NB/WT differentiation in CT, which should be further validated in large prospective models. CT-based clinic-radiologic-radiomics combined model could noninvasively predict Wilms tumor or neuroblastoma preoperatively. • CT radiomics features can predict Wilms tumor or neuroblastoma from abdominal CT preoperatively. • Integrating clinic variables may further improve the performance of the model. • The performance of the combined model is equal to or greater than human readers, depending on the lesion size.

Abstract WP67: Utilization and Impact of Large Vessel Occlusion Stroke Screening Practices and Selected Target Stroke III Strategies in the Get-with-the-Guidelines Registry Hospitals

Background: The utilization and impact of pre-hospital and in-hospital large vessel occlusion (LVO) stroke screening protocols and Target: Stroke phase III (TS III) best-practice strategies on time metrics for endovascular treatment at a national level, have not been studied. Methods: We sent an online survey in July 2022 to hospital representatives of 2528 hospitals participating in the GWTG registry about their EMS systems, clinical and imaging protocols, and utilization of selected TS III best-practice strategies (multiple choice, 0-100 scale, and yes/no questions). We obtained Individual patient-level data from the GWTG-Stroke Registry from January 2017 to March 2022. Multivariable linear regression models were performed to investigate the associations of these strategies with door-to-puncture (DTP) in endovascular (EVT) patients. Results: Out of 2455 sites that met our inclusion criteria, 1455 sites completed the survey, with a response rate of 59.3%. Hospital-level baseline characteristics, utilization of selected LVO screening practices, and site-reported strategies associated with shorter DTP times are shown (Table 1). Strategies associated with shorter DTP were the performance of simultaneous vascular imaging along with non-contrast CT scan on all stroke patients within 24 hours, and the use of newer technologies for LVO detection in the field leading to a 7.1 min (CI -12.8, -1.5) decrease and a 10 min (CI -18.6, -1.3) decrease in DTP with every 25% increase in the utilization of these strategies, respectively (Table 1). Conclusion: The simultaneous performance of vascular imaging with non-contrast CT scan in all stroke patients presenting within 24 hours and the use of newer technologies for LVO detection in the field could lead to shorter DTP times.