Non-contrast-enhanced Research Articles

Nasal and temporal intraconal orbital fat densities differ on computerized tomographic scans of normal orbits

AbstractBackground and AimThe anatomy and function of different areas within the intraconal fat remain poorly understood. A potential difference between nasal and temporal orbital fat densities in normal eyes may assist clinicians and radiologists in more accurately interpreting computerized tomographic (CT) scans and making more informed diagnostic and therapeutic decisions for patients with orbital pathologies.Patients and MethodsData from randomly selected patients who underwent orbital CT scans at Sheba Medical Center in 2022 were analyzed. Patients with abnormal imaging findings in either orbit were excluded. Intraconal orbital fat density was measured in six nasal and temporal sites by means of Hounsfield units (HU).ResultsThe study included 54 patients (mean age 45.3 ± 25.5 years, 29 [54%] females) who were scanned for ophthalmologic etiologies unrelated to the orbit. Non-contrast-enhanced (NCE)-CT scans were available for 36 patients (67%), CE-CT scans for 31 patients (57%), and both CE and NCE scans for 13 patients. HU values were significantly higher in the nasal orbit compared to the temporal orbit on both NCE-CT (−75.8 ± 7.5 nasal vs. −78.1 ± 8.4 temporal, P < 0.001) and CE-CT (−72.7 ± 6.7 nasal vs. −74.6 ± 8.6 temporal, P = 0.02). Age, sex, and laterality had no effect on the HU values.ConclusionsThe density of nasal intraconal fat is higher compared to temporal intraconal fat, as observed on both CE and NCE-CT scans of normal eyes.These results suggest the presence of anatomical differences between these compartments and could have significant clinical implications in the diagnosis of various orbital pathologies.

CSS-Net: A Collaborative Framework for Synthesis and Segmentation of Missing Contrast-enhanced Image with Error-Prediction Consistency

Abstract Automated tumor segmentation plays a critical role in facilitating the diagnosis and assessment of disease progression. Within the realm of tumor segmentation, Contrast-Enhanced (CE) scans are an effective imaging tool that allows for more intuitive observation of tumor characteristics and generally provide better segmentation results compared with Non-Contrast-Enhanced (NCE) scans alone. However, CE images are not available in most cases due to the time-consuming and costly need for contrast and repeat scans. To solve this issue, this paper proposes a Collaborative framework for the Synthesis and Segmentation of missing CE images in medical imaging with error-prediction consistency (CSS-Net). CSS-Net simultaneously addresses synthesis and segmentation tasks, generating both the synthesized CE images and coarse segmentation results. Subsequently, a multi-layer adaptive feature fusion strategy is utilized to effectively leverage the correlation between these tasks, resulting in refined segmentation results. Additionally, the proposed method incorporates a multi-layer feature fusion block, which adaptively selects features pertinent to segmentation. Furthermore, error-prediction consistency is also introduced between coarse and refined segmentation for regularization, leading to high-performance segmentation results. What’s more, we constructed a multimodal esophageal tumor segmentation dataset with 902 patients and validated it on this dataset and two publicly available multimodal brain tumor datasets. The results indicate that our method achieved Dice scores of 89.04% in esophageal tumor segmentation, 77.01% in whole glioma segmentation, and 91.14% in Vestibular Schwannoma segmentation. This performance surpasses that of segmentation using only available modalities and other image synthesis-based segmentation methods, demonstrating the superior robustness of CSS-Net.

Variable-density velocity-selective magnetization preparation for non-contrast-enhanced peripheral MR angiography.

Velocity-selective (VS) magnetization preparation has shown great promise for non-contrast-enhanced (NCE) magnetic resonance angiography (MRA) with the ability to generate positive angiographic contrast directly using a single 3D acquisition. However, existing VS-MRA methods have an issue of aliased saturation around a certain velocity, known as velocity field-of-view (vFOV), which can cause undesired signal loss in arteries. This study aimed to develop a new version of the VS preparation pulse sequence that overcomes the aliased saturation problem in conventional VS preparation. Utilizing the fact that an excitation profile is the Fourier transform of excitation k-space sampling, we sampled the k-space in a non-uniform fashion by scaling gradient pulses accordingly to have aliased excitation diffused over velocity. The variable density sampling function was numerically optimized to maximize the average of the velocity passband signal while minimizing its variance. The optimized variable density VS magnetization was validated through Bloch simulations and applied to peripheral NCE MRA in healthy subjects. The in-vivo experiments showed that the proposed variable density VS-MRA significantly lowered arterial signal loss observed in conventional VS-MRA, as evidenced by a higher arterial signal-to-noise ratio (58.50 ± 14.29 vs. 55.54 ± 12.32; p < 0.05) and improved artery-to-background contrast-to-noise ratio (22.75 ± 7.57 vs. 20.60 ± 6.51; p < 0.05).

DA-Tran: Multiphase liver tumor segmentation with a domain-adaptive transformer network

Accurate liver tumor segmentation from multiphase CT images is a prerequisite for data-driven tumor analysis. This study presents a domain-adaptive transformer (DA-Tran) network to segment liver tumors from each CT phase. First, a DA module is designed to produce domain-adapted feature maps from noncontrast-enhanced (NC)-phase, arterial (ART)-phase, portal venous (PV)-phase, and delay-phase (DP) images. Then, these domain-adapted feature maps are integrated using 3D transformer blocks to catch patch-structured similarity information and global context attention. Finally, the attention fusion decoder (AFD) integrates features from different branches to generate a more refined prediction. Extensive experimental results demonstrate that DA-Tran achieves state-of-the-art tumor segmentation results, i.e., a Dice similarity coefficient (DSC) of 87.00% and a 95% Hausdorff distance (HD95) of 5.10 mm on a clinical dataset (DB1). Additionally, DA-Tran consistently outperforms other cutting-edge methods on another multiphase liver tumor dataset (DB2). The DA module and transformer blocks can boost the co-segmentation performance and make DA-Tran an ideal solution for multiphase liver tumor segmentation.

CT imaging-based radiomics signatures improve prognosis prediction in postoperative colorectal cancer.

To investigate the use of non-contrast-enhanced (NCE) and contrast-enhanced (CE) CT radiomics signatures (Rad-scores) as prognostic factors to help improve the prediction of the overall survival (OS) of postoperative colorectal cancer (CRC) patients. A retrospective analysis was performed on 65 CRC patients who underwent surgical resection in our hospital as the training set, and 19 patient images retrieved from The Cancer Imaging Archive (TCIA) as the external validation set. In training, radiomics features were extracted from the preoperative NCE/CE-CT, then selected through 5-fold cross validation LASSO Cox method and used to construct Rad-scores. Models derived from Rad-scores and clinical factors were constructed and compared. Kaplan-Meier analyses were also used to compare the survival probability between the high- and low-risk Rad-score groups. Finally, a nomogram was developed to predict the OS. In training, a clinical model achieved a C-index of 0.796 (95% CI: 0.722-0.870), while clinical and two Rad-scores combined model performed the best, achieving a C-index of 0.821 (95% CI: 0.743-0.899). Furthermore, the models with the CE-CT Rad-score yielded slightly better performance than that of NCE-CT in training. For the combined model with CE-CT Rad-scores, a C-index of 0.818 (95% CI: 0.742-0.894) and 0.774 (95% CI: 0.556-0.992) were achieved in both the training and validation sets. Kaplan-Meier analysis demonstrated a significant difference in survival probability between the high- and low-risk groups. Finally, the areas under the receiver operating characteristics (ROC) curves for the model were 0.904, 0.777, and 0.843 for 1, 3, and 5-year survival, respectively. NCE-CT or CE-CT radiomics and clinical combined models can predict the OS for CRC patients, and both Rad-scores are recommended to be included when available.

The role of anatomical context in soft-tissue multi-organ segmentation of cadaveric non-contrast-enhanced whole body CT.

Cadaveric computed tomography (CT) image segmentation is a difficult task to solve, especially when applied to whole-body image volumes. Traditional algorithms require preprocessing using registration, or highly conserved organ morphologies. These requirements cannot be fulfilled by cadaveric specimens, so deep learning must be used to overcome this limitation. Further, the widespread use of 2D algorithms for volumetric data ignores the role of anatomical context. The use of 3D spatial context for volumetric segmentation of CT scans as well as the anatomical context required to optimize the segmentation has not been adequatelyexplored. To determine whether 2D slice-by-slice UNet algorithms or 3D volumetric UNet (VNet) algorithms provide a more effective method for segmenting 3D volumes, and to what extent anatomical context plays in the segmentation of soft-tissue organs in cadaveric, noncontrast-enhanced (NCE)CT. We tested five CT segmentation algorithms: 2D UNets with and without 3D data augmentation (3D rotations) as well as VNets with three levels of anatomical context (implemented via image downsampling at 1X, 2X, and 3X) for their performance via 3D Dice coefficients, and Hausdorff distance calculations. The classifiers were trained to segment the kidneys and liver and the performance was evaluated using Dice coefficient and Hausdorff distance on the segmentation versus the ground truthannotation. Our results demonstrate that VNet algorithms perform significantly better ( ) than 2D models. Among the VNet classifiers, those that use some level of image downsampling outperform (as calculated through Dice coefficients) the VNet without downsampling. Additionally, the optimal amount of downsampling depends on the targetorgan. Anatomical context is an important component of soft-tissue, multi-organ segmentation in cadaveric, NCE CT imaging of the whole body. Different amounts of anatomical contexts are optimal depending on the size, position, and surrounding tissue of theorgan.

Update on recent developments in imaging of inflammation in osteoarthritis: a narrative review.

Synovitis is an important component of the osteoarthritis (OA) disease process, particularly regarding the "inflammatory phenotype" of OA. Imaging plays an important role in the assessment of synovitis in OA with MRI and ultrasound being the most deployed imaging modalities. Contrast-enhanced (CE) MRI, particularly dynamic CEMRI (DCEMRI) is the ideal method for synovitis assessment, but for several reasons CEMRI is not commonly performed for OA imaging in general. Effusion-synovitis and Hoffa-synovitis are commonly used as surrogate markers of synovitis on non-contrast-enhanced (NCE) MRI and have been used in many epidemiological observational studies of knee OA. Several semiquantitative MRI scoring systems are available for the evaluation of synovitis in knee OA. Synovitis can be a target tissue for disease-modifying OA drug (DMOAD) clinical trials. Both MRI and ultrasound may be used to determine the eligibility and assess the therapeutic efficacy of DMOAD approaches. Ultrasound is mostly used for evaluation of synovitis in hand OA, while MRI is typically used for larger joints, namely knees and hips. The role of other modalities such as CT (including dual-energy CT) and nuclear medicine imaging (such as positron-emission tomography (PET) and its hybrid imaging) is limited in the context of synovitis assessment in OA. Despite research efforts to develop NCEMRI-based synovitis evaluation methods, these typically underestimate the severity of synovitis compared to CEMRI, and thus more research is needed before we can rely only on NCEMRI.

Patient size as a parameter for determining Diagnostic Reference Levels for paediatric Computed Tomography (CT) procedures

Introduction:The paediatric radiation dose has never been studied in Sri Lanka, nor has a national diagnostic reference level (NDRL) established. Therefore, the primary aim of this study was to propose diagnostic reference levels (DRL) and achievable dose (AD) values for paediatric CT examinations based on size. Methods:A total of 658 paediatric (0–15 years) non-contrast-enhanced (NC) studies of head, chest and abdomen regions performed during six months in two dedicated paediatric hospitals (out of the three such institutions in the country) were included. For head examinations, the dose indexes were analysed based on age, while for body examinations, both age and effective diameter (Deff) were used. The median and the third quartile of the pooled dose distribution were given as AD and NDRL, respectively. Results:The AD ranges for the head, chest and abdomen regions based on CTDIvol were 45.8–57.2 mGy, 2.9–10.0 mGy and 3.8–10.3 mGy. The corresponding NDRL ranges were 45.8–95.8 mGy, 3.5–14.1 mGy and 4.5–11.9 mGy. The AD ranges based on SSDEdeff and deff were 3.5–9.6 mGy and 4.1–10.3 mGy in chest and abdomen regions. The corresponding NDRL were 4.5–14.1 mGy and 6.1–10.6 mGy. Conclusion:Other institutions can use the present study DRLs as a reference dose for paediatric CT. The AD values can be used as a baseline for target dose optimisations, reducing doses up to 90%.

Evaluation of the Abdominal Aorta and External Iliac Arteries Using Three-Dimensional Time-of-Flight, Three Dimensional Electrocardiograph-Gated Fast Spin-Echo, and Contrast-Enhanced Magnetic Resonance Angiography in Clinically Healthy Cats.

Arterial thromboembolism is associated with high morbidity and mortality rates in cats. Definitive diagnosis requires advanced imaging modalities, such as computed tomography angiography (CTA) and contrast-enhanced (CE) magnetic resonance angiography (MRA). However, CTA involves exposure to a large amount of ionized radiation, and CE-MRA can cause systemic nephrogenic fibrosis. Non-contrast-enhanced (NE) MRA can help accurately diagnose vascular lesions without such limitations. In this study, we evaluated the ability of NE-MRA using three-dimensional electrocardiograph-gated fast spin-echo (3D ECG-FSE) and 3D time-of-flight (3D TOF) imaging to visualize the aorta and external iliac arteries in clinically healthy cats and compared the results with those obtained using CE-MRA. All 11 cats underwent 3D ECG-FSE, 3D TOF, and CE-MRA sequences. Relative signal intensity (rSI) for quantitative image analysis and image quality scores (IQS) for qualitative image analysis were assessed; the rSI values based on the 3D TOF evaluations were significantly lower than those obtained using 3D ECG-FSE (aorta 3D TOF: 0.57 ± 0.06, aorta 3D ECG-FSE: 0.83 ± 0.06, P < 0.001; external iliac arteries 3D TOF: 0.45 ± 0.06, external iliac arteries 3D ECG-FSE:0.80 ± 0.05, P < 0.001) and similar to those obtained using CE-MRA (aorta: 0.58 ± 0.05, external iliac arteries: 0.57 ± 0.03). Moreover, IQS obtained using 3D TOF were significantly higher than those obtained using 3D ECG-FSE (aorta 3D TOF: 3.95 ± 0.15, aorta 3D ECG-FSE: 2.32 ± 0.60, P < 0.001; external iliac arteries 3D ECG-FSE: 3.98 ± 0.08, external iliac arteries 3D ECG-FSE: 2.23 ± 0.56, P < 0.001) and similar to those obtained using CE-MRA (aorta: 3.61 ± 0.41, external iliac arteries: 3.57 ± 0.41). Thus, 3D TOF is more suitable and produces consistent image quality for visualizing the aorta and external iliac arteries in clinically healthy cats and this will be of great help in the diagnosis of FATE.

Evaluation of thyroid radiation dose during abdominal Computed Tomography procedures and dose reduction effectiveness of thyroid shielding

IntroductionDuring abdominal Computed Tomography (CT) studies, vicinity organs receive a dose from scatter radiation. The thyroid is considered an organ at greater risk due to high radiosensitivity. MethodsThe primary objective of this study was to determine the entrances surface dose (ESD) to the thyroid during abdominal CT studies and to evaluate the efficiency of dose reduction by lead shielding. The calibrated thermoluminescence dosimeter (TLD) chips were used to measure the ESD during 180 contrast-enhanced (CE) and non-contrast-enhanced (NC) abdominal CT studies in the presence and absence of lead shielding. ResultsThyroid shielding reduces the ESD by 72.3% (0.55 mGy), 86.5% (2.95 mGy) and 64.0% (2.24 mGy) during NC, 3–phase and 4–phase abdominal CT scans. Also, the patient height was identified as a parameter that inversely influenced the thyroid dose, proving that the taller patients receive less dose to the thyroid. Regardless, the scan parameters such as time and display field of view (DFOV) positively impact the thyroid dose. ConclusionLead shielding can prevent the external scatter reaching the thyroid region by 64%–87% during the non-vicinity scans such as abdomen CT. However, the actual dose saving lies between 0.2% and 0.4%, compared to the total effective dose of the whole CT procedure. Implications for practiceThe thyroid shield can effectively reduce external scatter radiation during abdominal CT procedures. However, the dose saving is insignificant compared to the total effective dose from the whole examination. Therefore, the use of thyroid shielding should be carefully evaluated during CT abdomen procedures.

Establishment of national diagnostic reference levels for computed tomography procedures in Sri Lanka: first nationwide dose survey

The main purpose of this study was to establish for the first time national diagnostic reference levels (NDRLs) for common computed tomography (CT) procedures in Sri Lanka. Patient morphometric data, exposure parameters and dose data such as volume CT dose index (CTDI) and dose–length product (DLP) were collected from 5666 patients who underwent 22 types of procedure. The extreme dose values were filtered before analysis to ensure that the data come from standard size patients. The median of the dose distribution was calculated for each institution, and the third quartile value of the median distribution was considered as the NDRL. Based on the inclusion and exclusion criteria, data from 4592 patients and 17 procedure types were considered for establishment of a NDRL, covering 41% of the country’s CT machines. The proposed NDRLs based on CTDI and DLP were: non-contrast-enhanced (NC) head, 82.2 mGy/1556 mGy cm; contrast-enhanced (CE) head, 82.2 mGy/1546 mGy cm; chest NC, 7.4 mGy/350 mGy cm; chest CE, 8.3 mGy/464 mGy cm; abdomen NC, 10.5 mGy/721 mGy cm; abdomen arterial (A) phase, 13.4 mGy/398 mGy cm; abdomen venous (V) phase, 10.8 mGy/460 mGy cm; abdomen delay (D) phase, 12.6 mGy/487 mGy cm; sinus NC, 30.2 mGy/452 mGy cm; lumbar spine NC, 24.1 mGy/1123 mGy cm; neck NC, 27.5 mGy/670 mGy cm; high-resolution CT of chest, 10.3 mGy/341 mGy cm; kidneys ureters and bladder NC, 19.4 mGy/929 mGy cm; chest to pelvis (CAP) NC, 10.8 mGy/801 mGy cm; CAP A, 10.4 mGy/384 mGy cm; CAP V, 10.5 mGy/534 mGy cm; CAP D, 16.8 mGy/652 mGy cm. Although the proposed NDRLs are comparable with those of other countries, the observed broad dose distributions between the CT machines within Sri Lanka indicate that dose optimisation strategies for the country should be implemented for most of the CT facilities.

Transfer Learning of the ResNet-18 and DenseNet-121 Model Used to Diagnose Intracranial Hemorrhage in CT Scanning.

The aim of the study was to verify the ability of the deep learning model to identify five subtypes and normal images in non-contrast enhancement CT of intracranial hemorrhage. A total of 351 patients (39 patients in the normal group, 312 patients in the intracranial hemorrhage group) who underwent intracranial hemorrhage noncontrast enhanced CT were selected, obtaining 2768 images in total (514 images for the normal group, 398 images for the epidural hemorrhage group, 501 images for the subdural hemorrhage group, 497 images for the intraventricular hemorrhage group, 415 images for the cerebral parenchymal hemorrhage group, and 443 images for the subarachnoid hemorrhage group). Based on the diagnostic reports of two radiologists with more than 10 years of experience, the ResNet-18 and DenseNet-121 deep learning models were selected. Transfer learning was used. 80% of the data was used for training models, 10% was used for validating model performance against overfitting, and the last 10% was used for the final evaluation of the model. Assessment indicators included accuracy, sensitivity, specificity, and AUC values. The overall accuracy of ResNet-18 and DenseNet-121 models was obtained as 89.64% and 82.5%, respectively. The sensitivity and specificity of identifying five subtypes and normal images were above 0.80. The sensitivity of the DenseNet-121 model to recognize intraventricular hemorrhage and cerebral parenchymal hemorrhage was lower than 0.80, 0.73, and 0.76, respectively. The AUC values of the two deep learning models were found to be above 0.9. The deep learning model can accurately identify the five subtypes of intracranial hemorrhage and normal images, and it can be used as a new tool for clinical diagnosis in the future.

A Combined-Radiomics Approach of CT Images to Predict Response to Anti-PD-1 Immunotherapy in NSCLC: A Retrospective Multicenter Study.

ObjectiveBased on non-contrast-enhanced (NCE)/contrast-enhanced (CE) computed tomography (CT) images, we try to identify a combined-radiomics model and evaluate its predictive capacity regarding response to anti-PD1 immunotherapy of patients with non-small-cell lung cancer (NSCLC).Methods131 patients with NSCLC undergoing anti-PD1 immunotherapy were retrospectively enrolled from 7 institutions. Using largest lesion (LL) and target lesions (TL) approaches, we performed a radiomics analysis based on pretreatment NCE-CT (NCE-radiomics) and CE-CT images (CE-radiomics), respectively. Meanwhile, a combined-radiomics model based on NCE-CT and CE-CT images was constructed. Finally, we developed their corresponding nomograms incorporating clinical factors. ROC was used to evaluate models’ predictive performance in the training and testing set, and a DeLong test was employed to compare the differences between different models.ResultsFor TL approach, both NCE-radiomics and CE-radiomics performed poorly in predicting response to immunotherapy. For LL approach, NCE-radiomics nomograms and CE-radiomics nomograms incorporating with clinical factor of distant metastasis all showed satisfactory results, reflected by the AUCs in the training (AUC=0.84, 95% CI: 0.75-0.92; AUC=0.77, 95% CI: 0.67-0.87) and test sets (AUC=0.78, 95% CI: 0.64-0.92, AUC=0.73, 95% CI: 0.57-0.88), respectively. Compared with the NCE-radiomics nomograms, the combined-radiomics nomogram showed incremental predictive capacity in the training set (AUC=0.85, 95% CI: 0.77-0.92) and test set (AUC=0.81, 95% CI: 0.67-0.94), respectively, but no statistical difference (P=0.86, P=0.79).ConclusionCompared with radiomics based on single NCE or CE-CT images, the combined-radiomics model has potential advantages to identify patients with NSCLC most likely to benefit from immunotherapy, and may effectively improve more precise and individualized decision support.

Association of Neurological Impairment on the Relative Benefit of Maximal Extent of Resection in Chemoradiation-Treated Newly Diagnosed Isocitrate Dehydrogenase Wild-Type Glioblastoma.

Increases in the extent of resection of both contrast-enhanced (CE) and non-contrast-enhanced (NCE) tissue are associated with substantial survival benefits in patients with isocitrate dehydrogenase wild-type glioblastoma. The fact, however, remains that these lesions exist within the framework of complex neural circuitry subserving cognition, movement, and behavior, all of which affect the ultimate survival outcome. The prognostic significance of the interplay between CE and NCE cytoreduction and neurological morbidity is poorly understood. To identify a clinically homogenous population of 228 patients with newly diagnosed isocitrate dehydrogenase wild-type glioblastoma, all of whom underwent maximal safe resection of CE and NCE tissue and adjuvant chemoradiation. We then set out to delineate the competing interactions between resection of CE and NCE tissue and postoperative neurological impairment with respect to overall survival. Nonparametric multivariate models of survival were generated via recursive partitioning to provide a clinically intuitive framework for the prognostication and surgical management of such patients. We demonstrated that the presence of a new postoperative neurological impairment was the key factor in predicting survival outcomes across the entire cohort. Patients older than 60 yr who suffered from at least one new impairment had the worst survival outcome regardless of extent of resection (median of 11.6 mo), whereas those who did not develop a new impairment had the best outcome (median of 28.4 mo) so long as all CE tissue was resected. Our data provide novel evidence for management strategies that prioritize safe and complete resection of CE tissue.

Potential increase in radiation-induced DNA double-strand breaks with higher doses of iodine contrast during coronary CT angiography.

PurposeTo investigate the contrast media iodine dose dependency of radiation‐induced DNA double‐strand breaks (DSBs) during a coronary computed tomography angiography (CCTA) scan.MethodsThis prospective patient study was approved by the ethical committee. Between November 2018 and July 2019, 50 patients (31 males and 19 females, mean age 64 years) were included in the study, 45 CCTA and five noncontrast‐enhanced (NCE) cardiac computed tomography (CT) patients. A single‐heartbeat scan protocol with a patient‐tailored contrast media injection protocol was used, administering a patient‐specific iodine dose. DNA double‐strand breaks were quantified using a γH2AX foci assay on peripheral blood lymphocytes. The net amount of γH2AX/cell was normalized to the individual patient CT dose by the size‐specific dose estimate (SSDE). Correlation between the administered and blood‐iodine dose and the SSDE normalized amount of DNA DSBs was investigated using a Pearson correlation test.ResultsCCTA patients were scanned with a mean CTDIvol of 10.6 ± 5.6 mGy, corresponding to a mean SSDE of 11.3 ± 5.3 mGy while the NCE cardiac CT patients were scanned with a mean CTDIvol of 6.00 ± 1.8 mGy, corresponding to a mean SSDE of 6.6 ± 2.7 mGy. The administered iodine dose ranged from 16.5 to 34.0 gI in the CCTA patients, resulting in a blood‐iodine dose range from 5.1 to 15.0 gI in the exposed blood volume. A significant linear relationship (r = 0.79, p‐value < 0.001) was observed between the blood iodine dose and SSDE normalized radiation‐induced DNA DSBs. A similar significant linear relationship (r = 0.62, p‐value < 0.001) was observed between the administered iodine dose and SSDE normalized radiation‐induced DNA DSBs.ConclusionsThis study shows that contrast media iodine dose increases the level of radiation‐induced DNA DSBs in peripheral blood lymphocytes in a linear dose‐dependent manner with CCTA. Importantly, the level of DNA DSBs can be reduced by lowering the administered iodine dose.

Combined high-resolution 3D CUBE T1-weighted imaging and non-contrast-enhanced magnetic resonance venography for evaluation of vein stenosis in May-Thurner syndrome.

To explore the feasibility of high-resolution MRI 3-dimensional (3D) CUBE T1-weighted magnetic resonance imaging (MRI) in combination with non-contrast-enhanced (NCE) magnetic resonance venography (MRV) for the assessment of lumen stenosis in May-Thurner syndrome. Twenty-nine patients underwent computed tomography venography (CTV) and high-resolution MRI-CUBE T1, and NCE MRV acquisitions. ANOVA and LSD tests were used to compare the stenosis rate and narrowest and distal diameters of the vessel lumen. There were no significant differences in the estimated stenosis rate between CTV, CUBE T1, and NCE MRV (p = 0.768). However, there were significant differences in the measured stenosis diameters of the left common iliac vein (LCIV), with CTV giving the largest mean diameter and CUBE had the smallest mean diameter (p < 0.05). The measured normal LCIV diameters did not significantly differ between MRV and CUBE (p = 0.075) but were significantly larger on CTV than on MRV and CUBE (p < 0.05). Compared with CTV, a combination of CUBE and MRV could provide an improved assessment of the degree of lumen stenosis in May-Thurner syndrome and demonstrate acute thrombosis. MRI underestimates the diameter of the vessel in comparison with CTV. MRI can be a substitute tool for Duplex ultrasound and CTV.

Most True Adrenal Incidentalomas Lack Proper Evaluation

Abstract Although the majority of true adrenal incidentalomas are benign and non-functional, appropriate workup is critical to rule out cancers as well as metabolic and cardiovascular diseases such as Cushing’s syndrome, primary aldosteronism (PA), and pheochromocytoma (PCC). The AACE/AAES and ENSAT guidelines recommend that all adrenal incidentalomas be evaluated for worrisome radiographic features and that all patients have initial biochemical work up to evaluate for hypercortisolism and pheochromocytoma as well as primary aldosteronism if hypertensive. Despite this, adrenal incidentalomas often are not evaluated properly leading to delayed diagnoses and potential complications from dysregulated hormone production. To determine if true adrenal incidentalomas are managed properly in our hospital system, we conducted a retrospective chart review. All CT scans (chest or abdomen) of adult patients conducted at the University of Colorado Hospital system between August 2011 and December 2016 were assessed (N=86,771). Of these, 305 scans identified true adrenal incidentalomas. CT scans done for patients with genetic conditions predisposing to adrenal nodules or done for an indication suggestive of adrenal disorder were excluded. From the 305 patient scans, 347 adrenal nodules were identified. Most patients (N=263, 86%) had one adrenal nodule; 42 (14%) had multiple nodules. Mean age of the cohort was 60±12.58 years old (range 21–88), and the majority were female (60.7%). The nodules had a mean size of 2.23±1.42 cm, range 0.5–11.2 cm. Most nodules were identified on CT scans with contrast (79%, N=241). Of the 64 scans (21%) done without contrast, 43% of the nodules had non-contrast enhanced (NCE) Hounsfield units (HU) less than 10, suggesting benign adenomas. Thirty-nine nodules (57%) had NCE HU greater than 10; eight of those were surgically removed (4 metastases from other primary cancers; 2 PCC; 2 lipid poor adrenal cortical adenomas). Most nodules were not biochemically evaluated. Only 64 of the 305 patients (21%) were tested for hypercortisolism (1mg ODST in 35; 24hr UFC in 29). Of those, three (0.1%) were diagnosed with Cushing’s syndrome. Only 82 patients (27%) were evaluated for PCC with plasma and/or 24hr urine metanephrines. Of these, 10 were diagnosed with PCC (3.3%). Only 24 patients (7.9%) were screened for PA with serum aldosterone and plasma renin activity, and four (1.3%) were positive. Taken together, of the 305 patients with adrenal incidentalomas, only 29 (9.5%) met guideline recommendations for biochemical work up for both hypercortisolism and PCC. Of those, 10 had a history of hypertension, yet only 5 were evaluated for PA. In summary, less than 10% of true adrenal incidentalomas had the proper biochemical evaluation. This suggests there are likely missed functional nodules leading to delayed or missed diagnosis possibly contributing to cardiovascular and metabolic consequences.

Threshold for calcium volume evaluation in patients with aortic valve stenosis: correlation with Agatston score.

The evaluation of aortic valve calcium burden is important when planning for transcatheter aortic valve implantation (TAVI). Although a robust golden standard methodology is available for calcium evaluation on noncontrast-enhanced (NCE) computed tomographic (CT) series, a standard reference for calcium assessment on contrast-enhanced CT series is currently lacking. Two hundred and forty-four preprocedural CT scans from patients who had received TAVI were analysed. We correlated the aortic calcium volumes obtained on CE series at three thresholds [450, 850, and 'probe + 100' Hounsfield Units (HU)] with the Agatston score obtained on NCE scans. A subgroup analysis was performed taking into account the contrast enhancement of the left ventricular outflow tract (LVOT), with a prespecified cut-off of 300 HU. The overall population analysis showed higher correlation with the Agatston score using the 850 HU threshold (r = 0.45, P < 0.0001); no correlation was found with the 450 HU threshold, whilst the 'probe + 100' HU threshold showed a weaker correlation (r = 0.30, P < 0.0001). In patients with LVOT enhancement less than 300 HU, 450 HU showed the highest accuracy in calcium identification (r = 0.70, P < 0.0001), whereas in patients with LVOT enhancement of at least 300 HU, the most accurate threshold was 850 HU (r = 0.46, P < 0.0001). The thresholds for correct calcium identification using the automatic 3Mensio software depend on the contrast enhancement of aortic and cardiac structures, which can be estimated by measuring the HU in the LVOT. In patients with LVOT HU of less than 300, the correct threshold to be set in the software is 450 HU, whereas in patients with LVOT HU of at least 300 the correct threshold is 850 HU.

SURG-22. PATTERN OF RECURRENCE ALONG EXTENT OF RESECTION IN PATIENTS WITH GLIOBLASTOMA, IDH-WILDTYPE: A RETROSPECTIVE STUDY

Abstract OBJECTIVE The concept for maximal resection of glioblastoma(GBM) is changing to resect not only contrast-enhanced (CE) tumor but non-contrast-enhanced (NCE) tumor. Although maximal resection is associated with longer survival, the pattern of recurrence in glioblastoma, isocitrate dehydrogenase (IDH)-wildtype patient is poorly understood. METHODS This retrospective, single-center study included 358 eligible patients through November 1, 2005 to December 31, 2018. Those patients were grouped along extent of resection (subtotal resection (STR, n=123), gross-total resection (GTR, n=194), and supratotal resection (SupTR, n=41)). The pattern of recurrence was classified based on the range of radiation treatment, into infield gross target volume (GTV), infield clinical target volume (CTV), marginal, outfield and CSF seeding. RESULTS Tumor recurrence was observed for each group as follows: STR group, 80.5%, GTR group, 75.3%, and SupTR group, 63.4%. Statistical differences in pattern of recurrence among each group were observed in infield GTV (STR group:75.8%, GTR group: 71.9%, and SupTR group: 42.3%, p=0.003) and Outfield (STR group:11.0%, GTR group: 21.2%, SupTR group: 34.6%, p=0.012) recurrence. The survival for SupTR group was significantly longer than that for the STR and GTR in terms of both overall survival (OS) and progression free survival (PFS) (OS, STR: 15.7m, GTR: 21.6m, SupTR: 44.7m, PFS, STR: 10.4m, GTR: 14.3m, SupTR: 35.5m) CONCLUSIONS As the extent of resection increased, local recurrence decreased and distant recurrence increased. During treatment of glioblastoma, expectation

The Association Between the Extent of Glioblastoma Resection and Survival in Light of MGMT Promoter Methylation in 326 Patients With Newly Diagnosed IDH-Wildtype Glioblastoma.

Background: The association between contrast enhanced (CE) and non-contrast enhanced (NCE) tumor resection and survival in patients with glioblastoma in relation to molecular subtypes is poorly understood. The aim of this study was to assess the association between CE and NCE tumor resection and survival in light of MGMT promoter methylation in newly diagnosed IDH-wildtype glioblastoma.Materials and methods: Patients with newly diagnosed IDH-wildtype glioblastoma who underwent surgery were eligible. CE and NCE tumor volumes were assessed on pre- and post-operative MRI scans and extent of resection was calculated. The association between CE and NCE tumor resection and survival was evaluated using multivariable Cox proportional hazards models and Kaplan Meier estimates.Results: Three hundred and twenty-six patients were included: 177 (54.3%) with and 149 (45.7%) without MGMT methylation. Multivariable Cox proportional hazards models stratified for MGMT methylation identified age ≤ 65y (HR 0.63; 95% CI, 0.49–0.81; p < 0.0001), chemoradiation (HR 0.13; 95% CI, 0.09–0.19; p < 0.0001), maximal CE tumor resection (HR 0.58; 95% CI, 0.39–0.87; p = 0.009), ≥ 30% NCE tumor resection (HR 0.71; 95% CI, 0.53–0.93; p = 0.014), and minimal residual CE tumor volume (HR 0.64; 95% CI, 0.46–0.88 p = 0.007) as being associated with longer overall survival. Kaplan Meier estimates showed that extensive surgery was more beneficial for patients with MGMT methylated glioblastoma.Conclusions: This study shows an association between maximal CE tumor resection, ≥30% NCE tumor resection, minimal residual CE tumor volume, and longer overall survival in patients with newly diagnosed IDH wildtype glioblastoma. Intraoperative imaging and stimulation mapping may be used to pursue safe and maximal resection. In future research, the safety aspect of maximizing tumor resection needs to be addressed.