Early Arterial Phase Research Articles

Can the second phase of contrast-enhanced MRA of the neck provide additional information in the acute stroke setting?

Double-concentration magnetic resonance imaging (MRI) contrast agents are frequently used in contrast-enhanced MR angiography (CE-MRA) of the head and neck. To avoid mistiming the peak concentration of intraluminal contrast (due to shorter duration of peak), a second acquisition is sometimes performed. To evaluate additional information from the second acquisition of CE-MRA and compare the collateral scoring to the hypoperfusion index obtained on MR perfusion, and to investigate presence of pseudo-occlusion using the second phase of CE-MRA. A retrospective study was conducted. CE-MRA of the brain/neck, dynamic susceptibility contrast (DSC) MR perfusion scan (in majority) and subsequent digital subtraction angiography (DSA) were evaluated in patients with previous acute internal carotid artery (ICA)/middle cerebral artery (MCA) occlusion. Evaluation of CE-MRA/MR perfusion and DSA was performed by three experienced neuroradiologists and one neurointerventionist, respectively. The site of ICA occlusion was seen to be distal to the site noted on early arterial phase (pseudo-occlusion of ICA) in 28.5% of patients. A significant negative correlation was seen between a higher HIR and collateral score. Evaluation of second phase CE-MRA can provide valuable information that may be otherwise lost if only the early arterial phase is evaluated.

Contrast-enhanced ultrasound appearance of adrenal hemorrhage after orthotopic liver transplantation: a retrospective study.

This study aimed to identify the incidence of adrenal hemorrhage (AH) after OLT and to summarize the ultrasound (US) and contrast-enhanced ultrasound (CEUS) characteristics. Patients with adrenal lesions after OLT at our hospital were retrospectively reviewed between January 2010 and November 2023. The reference diagnosis was defined on the basis of surgical data, computed tomography scans, and magnetic resonance imaging with at least 12 months of follow-up. The incidence of AH and the US and CEUS characteristics after OLT were analyzed and compared with those of adrenal metastases. A total of 23 patients (1.2%) with AH and 7 patients (0.35%) with suprarenal metastases were assessed. Compared with metastases, hematomas had more inhomogeneous echotextures (57% vs. 0.00%, P = 0.010), hypoechoic or mixed-echoic patterns (96% vs. 71%, P = 0.022), and anechoic areas (52% vs. 0.00%, P = 0.024), and their echotextures varied more over time (65% vs. 0.14%, P = 0.031). CEUS was performed on 12 patients with AH and 2 patients with metastases. A "jet-like" contrast superflux was observed in one actively bleeding hematoma, whereas no enhancement was observed in any static hematoma (100%). However, adrenal metastases had a contrast-enhanced appearance in the early arterial phase, followed by fast washout in the late phase (100%), and the difference was statistically significant (P < 0.001). The sonographic characteristics of AH after OLT vary over time. CEUS is recommended when adrenal lesions are detected, as CEUS can differentiate AH from metastases.

Prediction of microvascular invasion in hepatocellular carcinoma based on multi-phase dynamic enhanced CT radiomics feature and multi-classifier hierarchical fusion model

To predict microvascular invasion (MVI) in hepatocellular carcinoma (HCC) using a model based on multiphase dynamic-enhanced CT (DCE-CT) radiomics feature and hierarchical fusion of multiple classifiers. We retrospectively collected preoperative DCE-CT images from 111 patients with pathologically confirmed HCC in Guangzhou First People's Hospital between January, 2016 and April, 2020. The volume of interest was outlined in the early arterial phase, late arterial phase, portal venous phase and equilibrium phase, and radiomics features of these 4 phases were extracted. Seven classifiers based on different algorithms were trained using the filtered feature subsets to obtain multiple base classifiers under each phase. According to the hierarchical fusion strategy, a multi-criteria decision-making-based weight assignment algorithm was used for fusing each base classifier under the same phase with the model after extracting the phase information to obtain the prediction model. The proposed model was evaluated using a 5-fold cross-validation and assessed for area under the ROC curve (AUC), accuracy, sensitivity, and specificity. The prediction model was also compared with the fusion models using a single phase or multiple phases, models based on a single phase with a single classifier, models with different base classifier diversities, and 8 classifier models based on other ensemble methods. The experimental results showed that the performance of the proposed model for predicting HCCMVI was optimal after incorporating the 4 phases and 7 classifiers, with AUC, accuracy, sensitivity, and specificity of 0.828, 0.766, 0.877, and 0.648, respectively. Comparative experiments showed that this prediction model outperformed the models based on a single phase with a single classifier and other ensemble models. The proposed prediction model is effective for predicting MVI in HCC with superior performance to other models.

Fully Automated Versions of Clinically Validated Nephrometry Scores Demonstrate Superior Predictive Utility versus Human Scores.

To automate the generation of three validated nephrometry scoring systems on preoperative computerised tomography (CT) scans by developing artificial intelligence (AI)-based image processing methods. Subsequently, we aimed to evaluate the ability of these scores to predict meaningful pathological and perioperative outcomes. A total of 300 patients with preoperative CT with early arterial contrast phase were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer. A deep neural network approach was used to automatically segment kidneys and tumours, and then geometric algorithms were used to measure the components of the concordance index (C-Index), Preoperative Aspects and Dimensions Used for an Anatomical classification of renal tumours (PADUA), and tumour contact surface area (CSA) nephrometry scores. Human scores were independently calculated by medical personnel blinded to the AI scores. AI and human score agreement was assessed using linear regression and predictive abilities for meaningful outcomes were assessed using logistic regression and receiver operating characteristic curve analyses. The median (interquartile range) age was 60 (51-68) years, and 40% were female. The median tumour size was 4.2 cm and 91.3% had malignant tumours. In all, 27% of the tumours were high stage, 37% high grade, and 63% of the patients underwent partial nephrectomy. There was significant agreement between human and AI scores on linear regression analyses (R ranged from 0.574 to 0.828, all P < 0.001). The AI-generated scores were equivalent or superior to human-generated scores for all examined outcomes including high-grade histology, high-stage tumour, indolent tumour, pathological tumour necrosis, and radical nephrectomy (vs partial nephrectomy) surgical approach. Fully automated AI-generated C-Index, PADUA, and tumour CSA nephrometry scores are similar to human-generated scores and predict a wide variety of meaningful outcomes. Once validated, our results suggest that AI-generated nephrometry scores could be delivered automatically from a preoperative CT scan to a clinician and patient at the point of care to aid in decision making.

Color Mapping using Ultrasound System-integrated Perfusion Software for Evaluation of Focal Liver Lesions: A Possible First Step for More Independent Reading.

To assess the value of using integrated parametric ultrasound software for contrast-enhanced ultrasonography (CEUS) of liver tumors. 107 patients with liver tumors were studied. CEUS were performed to detect focal lesions. Parametric images were based on continuous CINE LOOPs, from the early-arterial phase (15 s) to the portal-venous phase (1 min) generated by perfusion software. The evaluations of the parametric images and their dignity for liver lesions were performed independently by an experienced and a less-experienced investigator. Computed tomography, magnetic resonance imaging scans or histological analysis were used as references. High parametric image quality were obtained in all patients. Among the patients, 44% lesions were benign, 56% were malignant. The experienced investigator correctly classified 46 of 47 (98%) as benign, and 60 of 60 (100%) as malignant tumors based on the parametric images. The less-experienced investigator correctly classified 39 of 47 (83%) as benign, and 49 of 60 (82%) malignant tumors, acheaving a high statistical accuracy of 98% with this type of diagnostic. Parametric imaging for grading the malignant degree of tumor may be a good complement to existing ultrasound techniques and was particularly helpful for improving the assessments of the less-experienced examiner.

Intrahepatic splenosis: Contrast enhanced ultrasound and magnetic resonance imaging findings.

To evaluate the contrast enhanced ultrasound (CEUS) and contrast enhanced magnetic resonance imaging (CEMRI) features of intrahepatic splenosis (IHS). Five patients (three males and two females, median age, 44 years; range,32-73 years) with seven IHSs were retrieved from the database of our hospital from March 2012 to October 2021. All IHSs were confirmed histologically by surgery. The CEUS and CEMRI characteristics of individual lesion were fully analyzed. All IHS patients were asymptomatic and four out of five patients had history of splenectomy. On CEUS, all IHSs were hyperenhancement in arterial phase. 71.4% (5/7) of IHSs manifested overall filling within few seconds, the other two lesions showed centripetal filling. Subcapsular vascular hyperenhancement and feeding artery was seen in 28.6% (2/7) and 42.9% (3/7) of IHSs, respectively. During portal venous phase, IHSs presented hyperenhancement (2/7) or isoenhancement (5/7). Moreover, rim-like hypoenhanced area was uniquely observed surrounding 85.7% (6/7) of IHSs. In late phase, seven IHSs remained continuous hyper- or isoenhancement. On CEMRI, five IHSs showed mosaic hyperintense in early arterial phase, the other two lesions showed homogeneous hyperintense. In portal venous phase, all IHSs revealed continuous hyper- (71.4%, 5/7) or iso-intense (28.6%, 2/7). During late phase, one IHS (14.3%, 1/7) became hypointense, the other lesions remained hyper- or isointense. Diagnosis of IHS can be based on typical CEUS and CEMRI features in patients with history of splenectomy.

Confirmed and presumed canine insulinomas and their presumed metastases are most conspicuous in the late arterial phase in a triple arterial phase CT protocol.

Arterial enhancement is the commonly described characteristic of canine insulinomas in contrast-enhanced computed tomography (CECT). However, this finding is also reported as inconsistent. The main aim of this single-center retrospective observational study was to describe the contrast enhancement (CE) pattern of canine presumed and confirmed insulinomas and presumed metastases in three consecutive (early, mid, and late) arterial phases. Included dogs had a medical-record-based clinical or cytological/histopathological diagnosis of insulinoma and quadruple-phase CECT.The arterial phases were identified according to published literature. The arterial enhancement of confirmed and presumed lesions was assessed using a visual grading score. Twelve dogs with a total of 17 pancreatic nodules were analyzed. Three dogs had multiple pancreatic nodules and nine had solitary findings. Four insulinomas were histopathologically confirmed. Late arterial phase (LAP) images demonstrated the largest number of pancreatic nodules reaching the highest enhancement scores (n=13, 76%). All analyzed dogs had CT evidence of arterially enhancing nodules in the liver (n=12), seven in the hepatic, splenic, or colic lymph nodes, and three in the spleen. Three out of five sampled livers and three lymph nodes were metastatic. All sampled spleens were benign. Avid arterial enhancement was the most dominant feature of canine presumed and confirmed insulinomas and presumed metastases in quadruple-phase CECT. The highest enhancement scores were observed primarily in LAP, followed by MAP. Authors, therefore, recommend including LAP in the standard CT protocol for dogs with suspected pancreatic insulinomas.

DCE-MRI-based radiomics in predicting angiopoietin-2 expression in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is the sixth most common cancer, and the third leading cause of cancer death worldwide. Studies have shown that increased angiopoietin-2 (Ang-2) expression relative to Ang-1 expression in tumors is associated with a poor prognosis.The purpose of this study was to investigate the efficacy of predicting Ang-2 expression in HCC by preoperative dynamic contrast‐enhanced magnetic resonance imaging (DCE-MRI)-based radiomics.MethodsThe data of 52 patients with HCC who underwent surgical resection in our hospital were retrospectively analyzed. Ang-2 expression in HCC was analyzed by immunohistochemistry. All patients underwent preoperative upper abdominal DCE-MRI and intravoxel incoherent motion diffusion-weighted imaging scans. Radiomics features were extracted from the early and late arterial and portal phases of axial DCE-MRI. Univariate analysis and least absolute shrinkage and selection operator (LASSO) was performed to select the optimal radiomics features for analysis. A logistic regression analysis was performed to establish a DCE-MRI radiomics model, clinic-radiologic (CR) model and combined model integrating the radiomics score with CR factors. The stability of each model was verified by 10-fold cross-validation. Receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA) were employed to evaluate these models.ResultsAmong the 52 HCC patients, high Ang-2 expression was found in 30, and low Ang-2 expression was found in 22. The areas under the ROC curve (AUCs) for the radiomics model, CR model and combined model for predicting Ang-2 expression were 0.800, 0.874, and 0.933, respectively. The DeLong test showed that there was no significant difference in the AUC between the radiomics model and the CR model (p > 0.05) but that the AUC for the combined model was significantly greater than those for the other 2 models (p < 0.05). The DCA results showed that the combined model outperformed the other 2 models and had the highest net benefit.ConclusionThe DCE-MRI-based radiomics model has the potential to predict Ang-2 expression in HCC patients; the combined model integrating the radiomics score with CR factors can further improve the prediction performance.Graphical abstract

Can expiratory or inspiratory contrast-enhanced computed tomography be more efficient for fast-track cannulation of the right adrenal vein in adrenal venous sampling?

This study compares the usefulness of expiratory arterial phase (EAP)-contrast-enhanced computed tomography (CT) (CECT) with that of inspiratory arterial phase (IAP)-CECT in adrenal venous sampling (AVS). Sixty-four patients who underwent AVS and CECT at the authors' hospital between April 2013 and June 2019 were included in this study. The patients were classified into the following two groups: EAP (32 patients) and IAP (32 patients) groups. The single arterial phase images were obtained at 40 seconds in the IAP group. The double arterial phase images were obtained at 40 seconds in the early arterial phase and 55 seconds in the late arterial phase in the EAP group. The authors then compared the right adrenal vein (RAV) visualization rate on the CECT, the difference between the CECT images and adrenal venograms in the localization of the RAV orifice, the cannulation time to the RAV, and the volume of contrast agent administered intraoperatively between the two groups. The rates of the RAV visualization in the EAP group were 84.4% in the early arterial phase, 93.8% in the late arterial phase, and 100% in the combined early and late arterial phases. The rate of the RAV visualization in the IAP group was 96.9%. There was no significant difference between the two groups in terms of the rate of the RAV visualization. However, there was a small difference in the location of the RAV orifice between the CECT images and adrenal venograms in the EAP group as compared with the IAP group (P < 0.001). The median time to the RAV catheterization was significantly shorter in the EAP group (27.5 minutes) than in the IAP group (35.5 minutes; P = 0.035). The rates of the RAV visualization in the EAP group were not significant between the early arterial phase, late arterial phase, and combined early and late arterial phases (P = 0.066). However, the mean volume CT dose index in the combined early and late arterial phases was significantly higher than in the early and late arterial phases (P < 0.001). The EAP-CECT is more useful for increasing the speed of the RAV cannulation due to the small difference in the localization of the RAV orifice compared to IAP-CECT. However, since EAP-CECT has double contrast arterial phases and increased radiation exposure compared to IAP-CECT, only the late arterial phase may be acceptable to reduce radiation exposure.

Prediction of Local Tumor Progression After Microwave Ablation in Colorectal Carcinoma Liver Metastases Patients by MRI Radiomics and Clinical Characteristics-Based Combined Model: Preliminary Results

To investigate the predictability of local tumor progression (LTP) after microwave ablation (MWA) in colorectal carcinoma liver metastases (CRLM) patients by magnetic resonance imaging (MRI) radiomics and clinical characteristics-based combined model. Forty-two consecutive CRLM patients (67 tumors) with post-MWA complete response at 1st month MRI were included in this retrospective study. One hundred and eleven radiomics features were extracted for each tumor and for each phase by manual segmentation from pre-treatment MRI T2 fat-suppressed (Phase 2) and early arterial phase T1 fat-suppressed sequences (Phase 1). A clinical model was constructed using clinical data, two combined models were created with feature reduction and machine learning by combining clinical data and Phase 2 and Phase 1 radiomics features. The predicting performance for LTP development was investigated. LTP developed in 7 patients (16.6%) and 11 tumors (16.4%). In the clinical model, the presence of extrahepatic metastases before MWA was associated with a high probability of LTP (p < 0.001). The pre-treatment levels of carbohydrate antigen 19-9 and carcinoembryonic antigen were higher in the LTP group (p = 0.010, p = 0.020, respectively). Patients with LTP had statistically significantly higher radiomics scores in both phases (p < 0.001 for Phase 2 and p = 0.001 for Phase 1). The classification performance of the combined model 2, created by using clinical data and Phase 2-based radiomics features, achieved the highest discriminative performance in predicting LTP (p = 0,014; the area under curve (AUC) value 0.981 (95% CI 0.948-0.990). The combined model 1, created using clinical data and Phase 1-based radiomics features (AUC value 0,927 (95% CI 0.860-0.993, p < 0.001)) and the clinical model alone [AUC value of 0.887 (95% CI 0.807-0.967, p < 0.001)] had similar performance. Combined models based on clinical data and radiomics features obtained from T2 fat-suppressed and early arterial-phase T1 fat-suppressed MRI are valuable markers in predicting LTP after MWA in CRLM patients. Large-scale studies with internal and external validations are needed to come to a firm conclusion on the predictability of radiomics models in CRLM patients.

PD08-06 FULLY AUTOMATED TUMOR CONTACT SURFACE AREA PREDICTS POSTOPERATIVE IPSILATERAL GFR PRESERVATION FOLLOWING PARTIAL NEPHRECTOMY

You have accessJournal of UrologyCME1 Apr 2023PD08-06 FULLY AUTOMATED TUMOR CONTACT SURFACE AREA PREDICTS POSTOPERATIVE IPSILATERAL GFR PRESERVATION FOLLOWING PARTIAL NEPHRECTOMY Andrew Wood, Nicholas Heller, Tarik Benidir, Nour Abdallah, Fabian Isensee, Resha Tejpaul, Chalairat Suk-Ouichai, Caleb Curry, Alex You, Erick Remer, Samuel Haywood, Robert Abouassaly, Steven Campbell, Nikolaos Papanikolopoulos, and Christopher Weight Andrew WoodAndrew Wood More articles by this author , Nicholas HellerNicholas Heller More articles by this author , Tarik BenidirTarik Benidir More articles by this author , Nour AbdallahNour Abdallah More articles by this author , Fabian IsenseeFabian Isensee More articles by this author , Resha TejpaulResha Tejpaul More articles by this author , Chalairat Suk-OuichaiChalairat Suk-Ouichai More articles by this author , Caleb CurryCaleb Curry More articles by this author , Alex YouAlex You More articles by this author , Erick RemerErick Remer More articles by this author , Samuel HaywoodSamuel Haywood More articles by this author , Robert AbouassalyRobert Abouassaly More articles by this author , Steven CampbellSteven Campbell More articles by this author , Nikolaos PapanikolopoulosNikolaos Papanikolopoulos More articles by this author , and Christopher WeightChristopher Weight More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003239.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Tumor Contact Surface Area (CSA) is an externally validated nephrometry scoring system that requires measurement of multiple dimensions of cross sectional imaging. Despite studies demonstrating its ability to predict glomerular filtration rate (GFR) following partial nephrectomy (PN), its implementation has been slowed by required time investment and interobserver variability. We sought to evaluate the utility of artificial intelligence (AI) generated CSA as compared to human-generated CSA in predicting post-PN GFR. METHODS: A total of 300 patients with preoperative computerized tomography with early arterial contrast phase were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer. A deep neural network approach was used to automatically segment kidneys and tumors, and then programed to generate the measurements and calculate tumor CSA. Human CSA scores were independently calculated by medical personnel blinded to AI-scores. Ipsilateral GFR before and after surgery was calculated from volumetric analyses of kidney parenchyma and pre and post-operative GFR values. AI-CSA and Human-CSA were then compared with regards to their ability to predict Ipsilateral GFR preservation. RESULTS: After removal of patients undergoing RN and those without requisite data for GFR calculation, a total of 150 patients were included in the analysis. There was significant agreement between Human CSA and AI-CSA on linear regression analysis (R2=0.74, p<0.0001). On univariate linear regression analysis, both AI- (r=0.217, p=0.0076) and Human generated (r=0.187, p=0.021) CSA similarly predicted ipsilateral GFR preservation. However, when incorporated into a MV model incorporating age, gender, body mass index, diabetes status, and ischemia time, only AI generated tumor CSA remained a significant predictor of ipsilateral GFR preservation (p=0.021). CONCLUSIONS: Fully automated tumor CSA calculations are not inferior, and may be superior, to human generated CSA calculations in predicting post-operative GFR after PN. Once validated, our results suggest that AI generated CSA could be delivered automatically from a preoperative CT scan to a clinician and patient at the point of care to aid in decision making. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e234 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Andrew Wood More articles by this author Nicholas Heller More articles by this author Tarik Benidir More articles by this author Nour Abdallah More articles by this author Fabian Isensee More articles by this author Resha Tejpaul More articles by this author Chalairat Suk-Ouichai More articles by this author Caleb Curry More articles by this author Alex You More articles by this author Erick Remer More articles by this author Samuel Haywood More articles by this author Robert Abouassaly More articles by this author Steven Campbell More articles by this author Nikolaos Papanikolopoulos More articles by this author Christopher Weight More articles by this author Expand All Advertisement PDF downloadLoading ...

. The moderated ct angiography of the heart scanning protocol for children with dilated cardiomyopathy

Purpose. To moderate computed tomography angiography (CTA) of the heart scanning protocol in children with dilated cardiomyopathy and low left ventricle ejection fraction (LVEF) for optimal visualization of the heart and its major vessels.Materials and methods. We examined 38 patients aged from 9 months to 17 years, undergoing treatment at the cardiology department in the of the Rehabilitation Clinic for Children of the Almazov National Medical Research Centre. Firstly, all patients were performed echocardiography (Echo). Echo data evaluated LVEF. The patients were selected based on the clinical diagnosis, the LVEF index, the patient’s height (or the length of the scan area). 2 groups of patients with DCM (with low LVEF) were formed - younger and older patients; for each group was formed a control group of patients with normal LVEF values. All patients underwent CTA on a 128-sliced computed tomograph Ingenuity Elite (Philips, Netherlands) after a bolus intravenous contrast medium injection.Results. There was revealed a relationship between the start time of the scan and the LVEF, the patient’s height. For patients with low LVEF were created study protocols, where scan start time offset was set as: for the group 1 in the early arterial phase +3c, in the late arterial phase +5c, in the venous phase +15c; for the group 2 in the early arterial phase +5c, in the late arterial phase +5c, in the venous phase +29c.Conclusion. The moderated scanning protocol presents good contrast enhancement by chambers of the heart and its major vessels. It is necessary for an assessment of the anatomy and pathological changes. The identified criteria (LVEF, patient height) should be considered for CTA of the heart in children with dilated cardiomyopathy.

Modified contrast-enhanced ultrasonography with the new high-resolution examination technique of high frame rate contrast-enhanced ultrasound (HiFR-CEUS) for characterization of liver lesions: First results.

To examine to what extent the high frame rate contrast-enhanced ultrasound (HiFR) diagnostic enables the conclusive diagnosis of liver changes with suspected malignancy. Ultrasound examinations were performed by an experienced examiner using a multifrequency probe (SC6-1) on a high-end ultrasound system (Resona 7, Mindray) to clarify liver changes that were unclear on the B-scan. A bolus of 1-2.4 ml of the Sulphur hexafluoride ultrasound microbubbles contrast agent SonoVue™ (Bracco SpA, Italy) was administered with DICOM storage of CEUS examinations from the early arterial phase (5-15 s) to the late phase (5-6 min). Based on the image files stored in the PACS, an independent reading was performed regarding image quality and finding-related diagnostic significance (0 not informative/non-diagnostic to 5 excellent image quality/confident diagnosis possible). References were clinical follow-up, if possible, comparison to promptly performed computed tomography or magnetic resonance imaging, in some cases also to histopathology. We examined 100 patients (42 women, 58 men, from 18 years to 90 years, mean 63±13 years) with different entities of focal and diffuse liver parenchymal changes, which could be detected in all cases with sufficient image quality with CEUS and with high image quality with HiFR-CEUS. Proportionally septate cysts were found in n = 19 cases, scars after hemihepatectomy with local reduced fat in n = 5 cases, scars after microwave ablation in n = 19 cases, hemangiomas in n = 9 cases, focal nodular hyperplasia in n = 8 cases, colorectal metastases in n = 15 cases, hepatocellular carcinoma (HCC) in n = 11 cases, Osler disease in n = 8 cases. The size of lesions ranged from 5 mm to 200 mm with a mean value of 33.1±27.8 mm. Conclusive diagnoses could be made by the experienced investigator in 97/100 cases with CEUS, confirmed by reference imaging, in parts by histopathology or follow-up. The image quality for HiFR CEUS was rated with a score of 3 to 5; 62 cases were assessed with an average of good (4 points), 27 cases with very good (5 points), and in 11 cases (3 points) still satisfactory despite aggravated acoustic conditions. The specificity of HIFR-CEUS was 97%, the sensitivity 97%, the positive predictive value 94%, the negative predictive value 99% and the accuracy 97%. HIFR-CEUS has demonstrated has demonstrated an improved image quality resulting in a high diagnostic accuracy. In the hands of an experienced investigator, HiFR-CEUS allows the assessment of focal and diffuse unclear liver parenchymal changes on B-scan and dynamic assessment of microcirculation in solid and vascular changes.

Predictive accuracy of computer-generated C-index nephrometry scores compared with human-generated scores in predicting oncologic and perioperative outcomes.

623 Background: The Centrality index (C-index) score is a validated nephrometry scoring system that requires precise measurements and mathematical calculations of cross sectional imaging. Like other nephrometry scores, its implementation has been slowed by required time investment and interobserver variability. We sought to automate this score on preoperative computerized tomography scans by developing an artificial intelligence-generated C-index score. We then aimed to evaluate its ability to predict meaningful oncologic and perioperative outcomes as compared to human-generated C-index nephrometry scores. Methods: 300 patients with preoperative computerized tomography with early arterial contrast phase were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer. A deep neural network approach was used to automatically segment kidneys and tumors, and then programed to generate the measurements and calculate C-index score. Human C-index scores were independently calculated by medical personnel blinded to AI-scores. AI- and Human score agreement was assessed using bivariate linear regression correlation and their predictive abilities for both oncologic and perioperative outcomes were assessed using logistic regression and compared with receiver operating characteristic (ROC) curve analyses with measurements of areas under the curve (AUC). Results: Median age was 60 years (IQE 51–68), and 40% were female. Median tumor size was 4.2 cm and 91.3% had malignant tumors. 27% were high stage, 37% high grade, and 63% underwent partial nephrectomy. There was significant agreement between Human scores and AI-scores on linear regression analysis (R2 = 0.738, p &lt;0.0001). Both AI- and Human generated C-index scores similarly predicted meaningful oncologic outcomes, with lower levels of either C-index score associated with increased risk of malignant histology (H-score p = 0.018, AI score p =0.014) high-grade disease (both p &lt;0.0001), and high stage disease (both p &lt;0.0001). Lower levels of either AI or human generated C-index scores also predicted a radical nephrectomy rather than partial nephrectomy surgical approach (both p &lt;0.0001). AUC measurements (Table) were similar but consistently superior for AI generated C-index scores. Conclusions: Fully automated AI-generated C-index scores are comparable to human-generated C-index scores and predict a wide variety of meaningful patient-centered outcomes. Once validated in additional populations, our results suggest that our AI generated C-index could be delivered automatically from a preoperative CT scan to a clinician and patient at the point of care to aid in decision making. [Table: see text]

Multiparametric Ultrasound of Cervical Lymph Node Metastases in Head and Neck Cancer for Planning Non-Surgical Therapy.

Background: We aimed to evaluate multiparametric ultrasound, to achieve a better understanding of the baseline characteristics of suspected cervical lymph node metastases in head and neck cancer before induction chemotherapy or chemoradiation. Methods: From February 2020 to April 2021, our complete ultrasound examination protocol was carried out on clinically evident malignant lymph nodes of histologically proven HNSCC in the pre-therapeutic setting. Results: A total of 13 patients were eligible for analysis. Using elastography, irregular clear hardening in areas in the center of the lymph node could be detected in all cases. Elastographic Q-analysis showed a significantly softer cortex compared to the center and surrounding tissue. The time–intensity curve analysis showed high values for the area under the curve and a short time-to-peak (fast wash-in) in all cases compared to the surrounding tissue. A parametric evaluation of contrast enhanced the ultrasound in the early arterial phase and showed an irregular enhancement from the margin in almost all investigated lymph nodes. These results show that the implementation of comprehensive, multiparametric ultrasound is suitable for classifying suspected lymph node metastasis more precisely than conventional ultrasound alone in the pre-therapeutic setting of HNSCC. Thus, these parameters may be used for improvements in the re-staging after chemoradiation or neoadjuvant therapy monitoring, respectively.

MP41-19 PHASE I NCT03738488. FEASIBLE 3D PRINTED MODELS OF RENAL CELL CARCINOMA WITH VENOUS THROMBUS EXTENSION FOR SURGICAL PLANNING AND SIMULATION

You have accessJournal of UrologyCME1 May 2022MP41-19 PHASE I NCT03738488. FEASIBLE 3D PRINTED MODELS OF RENAL CELL CARCINOMA WITH VENOUS THROMBUS EXTENSION FOR SURGICAL PLANNING AND SIMULATION Ines Rivero Belenchon, Carmen Belen Congregado Ruiz, Gorka Gomez Ciriza, Victoria Gomez Dos Santos, Cristina Asensio, Cristina Gonzalez Gordaliza, Ignacio Osman Garcia, Jose Manuel Conde Sanchez, Francisco Javier Burgos Revilla, and Rafael Antonio Medina Lopez Ines Rivero BelenchonInes Rivero Belenchon More articles by this author , Carmen Belen Congregado RuizCarmen Belen Congregado Ruiz More articles by this author , Gorka Gomez CirizaGorka Gomez Ciriza More articles by this author , Victoria Gomez Dos SantosVictoria Gomez Dos Santos More articles by this author , Cristina AsensioCristina Asensio More articles by this author , Cristina Gonzalez GordalizaCristina Gonzalez Gordaliza More articles by this author , Ignacio Osman GarciaIgnacio Osman Garcia More articles by this author , Jose Manuel Conde SanchezJose Manuel Conde Sanchez More articles by this author , Francisco Javier Burgos RevillaFrancisco Javier Burgos Revilla More articles by this author , and Rafael Antonio Medina LopezRafael Antonio Medina Lopez More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002607.19AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Renal Cell Cancer (RCC) accounts for 3-5% of all adults malignancies, and up to 10% are presented with venous thrombus extension (VTE). This worsens prognosis and represents a therapeutic challenge. 3D biomodels are printed copies of patients´ radiological images with visual and tactile components that enhance understanding of anatomy and may improve surgical planning, communication and training. This is a Multicenter Clinical Trial (NCT03738488), which aims to assess the efficacy and efficiency of surgery planning with 3D in RCC with VTE. The objective of the phase I is to obtain a feasible, affordable, accurate and suitable for surgical simulation 3D model. METHODS: A CT image in early arterial and nephrogenic phase was obtained. ITK-snap® and VirSSPA Software® were used for segmentation. The resulting 3D mesh was processed with MeshMixer®. Multiple models were printed using different 3D printers and materials. We evaluated: material, scale, thickness, accuracy, suitability for surgery, cost and printing time. 6 urologists completed a satisfaction questionnaire. RESULTS: 4 models were discarded (Table 1). The selected one was printed with BQ Witbox FDM printer in polyurethane filament with a 0.8 mm thickness and 100% scale. All anatomical structures could be correctly identified with a good accuracy compared to the CT (<5 mm deviation) and the surgery could be performed on it. Model cost was 15€ and whole processing and printing time 48 h. 100% of urologists thought that the obtained 3D model could be useful for surgery planning and simulation. CONCLUSIONS: A feasible and affordable 3D printed model of RCC with VTE was obtained. It was accurate compared to the CT and suitable for surgery simulation. Urologists thought it could be useful for surgery planning and simulation. Source of Funding: Funded by Pfizer © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e728 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ines Rivero Belenchon More articles by this author Carmen Belen Congregado Ruiz More articles by this author Gorka Gomez Ciriza More articles by this author Victoria Gomez Dos Santos More articles by this author Cristina Asensio More articles by this author Cristina Gonzalez Gordaliza More articles by this author Ignacio Osman Garcia More articles by this author Jose Manuel Conde Sanchez More articles by this author Francisco Javier Burgos Revilla More articles by this author Rafael Antonio Medina Lopez More articles by this author Expand All Advertisement PDF DownloadLoading ...

Contrast Media Reduction in Computed Tomography With Deep Learning Using a Generative Adversarial Network in an Experimental Animal Study.

This feasibility study aimed to use optimized virtual contrast enhancement through generative adversarial networks (GAN) to reduce the dose of iodine-based contrast medium (CM) during abdominal computed tomography (CT) in a large animal model. Multiphasic abdominal low-kilovolt CTs (90 kV) with low (low CM, 105 mgl/kg) and normal contrast media doses (normal CM, 350 mgl/kg) were performed with 20 healthy Göttingen minipigs on 3 separate occasions for a total of 120 examinations. These included an early arterial, late arterial, portal venous, and venous contrast phase. One animal had to be excluded because of incomplete examinations. Three of the 19 animals were randomly selected and withheld for validation (18 studies). Subsequently, the GAN was trained for image-to-image conversion from low CM to normal CM (virtual CM) with the remaining 16 animals (96 examinations). For validation, region of interest measurements were performed in the abdominal aorta, inferior vena cava, portal vein, liver parenchyma, and autochthonous back muscles, and the contrast-to-noise ratio (CNR) was calculated. In addition, the normal CM and virtual CM data were presented in a visual Turing test to 3 radiology consultants. On the one hand, they had to decide which images were derived from the normal CM examination. On the other hand, they had to evaluate whether both images are pathological consistent. Average vascular CNR (low CM 6.9 ± 7.0 vs virtual CM 28.7 ± 23.8, P < 0.0001) and parenchymal (low CM 1.5 ± 0.7 vs virtual CM 3.8 ± 2.0, P < 0.0001) CNR increased significantly by GAN-based contrast enhancement in all contrast phases and was not significantly different from normal CM examinations (vascular: virtual CM 28.7 ± 23.8 vs normal CM 34.2 ± 28.8; parenchymal: virtual CM 3.8 ± 2.0 vs normal CM 3.7 ± 2.6). During the visual Turing testing, the radiology consultants reported that images from normal CM and virtual CM were pathologically consistent in median in 96.5% of the examinations. Furthermore, it was possible for the examiners to identify the normal CM data as such in median in 91% of the cases. In this feasibility study, it could be demonstrated in an experimental setting with healthy Göttingen minipigs that the amount of CM for abdominal CT can be reduced by approximately 70% by GAN-based contrast enhancement with satisfactory image quality.

Anatomically and physiologically informed computational model of hepatic contrast perfusion for virtual imaging trials.

Virtual (in silico) imaging trials (VITs), involving computerized phantoms and models of the imaging process, provide a modern alternative to clinical imaging trials. VITs are faster, safer, and enable otherwise-impossible investigations. Current phantoms used in VITs are limited in their ability to model functional behavior such as contrast perfusion which is an important determinant of dose and image quality in CT imaging. In our prior work with the XCAT computational phantoms, we determined and modeled inter-organ (organ to organ) intravenous contrast concentration as a function of time from injection. However, intra-organ concentration, heterogeneous distribution within a given organ, was not pursued. We extend our methods in this work to model intra-organ concentration within the XCAT phantom with a specific focus on the liver. Intra-organ contrast perfusion depends on the organ's vessel network. We modeled the intricate vascular structures of the liver, informed by empirical and theoretical observations of anatomy and physiology. The developed vessel generation algorithm modeled a dual-input-single-output vascular network as a series of bifurcating surfaces to optimally deliver flow within the bounding surface of a given XCAT liver. Using this network, contrast perfusion was simulated within voxelized versions of the phantom by using knowledge of the blood velocities in each vascular structure, vessel diameters and length, and the time since the contrast entered the hepatic artery. The utility of the enhanced phantom was demonstrated through a simulation study with the phantom voxelized prior to CT simulation with the relevant liver vasculature prepared to represent blood and iodinated contrast media. The spatial extent of the blood-contrast mixture was compared to clinical data. The vascular structures of the liver were generated with size and orientation which resulted in minimal energy expenditure required to maintain blood flow. Intravenous contrast was simulated as having known concentration and known total volume in the liver as calibrated from time-concentration curves. Measurements of simulated CT ROIs were found to agree with clinically observed values of early arterial phase contrast enhancement of the parenchyma ( HU). Similarly, early enhancement in the hepatic artery was found to agree with average clinical enhancement HU). The computational methods presented here furthered the development of the XCAT phantoms allowing for multi-timepoint contrast perfusion simulations, enabling more anthropomorphic virtual clinical trials intended for optimization of current clinical imaging technologies and applications.

Diagnostic performance of MRI in detecting locally recurrent soft tissue sarcoma: systematic review and meta-analysis.

To systematically review the diagnostic criteria and performance of MRI in detecting locally recurrent soft tissue sarcoma. Medline and Embase were searched for original studies on the diagnostic performance of MRI detecting locally recurrent soft tissue sarcoma. Study quality was assessed using QUADAS-2. Sensitivity and specificity were pooled using a bivariate random-effects model. Ten studies were included. There was a high risk of bias with respect to patient selection in 2 studies and a high risk of bias with respect to flow and timing in 8 studies. The presence of a mass yielded a pooled sensitivity of 80.9% and a pooled specificity of 77.0%. Hyperintensity at T2-weighted imaging yielded a pooled sensitivity of 82.4% and a pooled specificity of 11.0%. Hypo- or isointensity at T1-weighted imaging yielded a pooled sensitivity of 82.0% and a pooled specificity of 14.3%. Contrast enhancement images yielded a pooled sensitivity of 95.9% and a pooled specificity of 12.3%. Low signal mass on the apparent diffusion coefficient (ADC) map yielded a pooled sensitivity of 67.5% and a pooled specificity of 95.3%. Early and rapid arterial phase enhancement at dynamic contrast-enhanced (DCE) MRI yielded a pooled sensitivity of 91.3% and a pooled specificity of 84.7%. The presence of a mass appears a useful criterion to diagnose locally recurrent soft tissue sarcoma. Signal characteristics at standard T2- and T1-weighted imaging and contrast enhancement seem less useful because they lack specificity. Functional MRI techniques, including DWI with ADC mapping and DCE, may help to make a correct diagnosis. • The presence of a mass at MRI appears useful to diagnose locally recurrent soft tissue sarcoma, because both sensitivity and specificity are fairly high. • Signal characteristics at standard T2- and T1-weighted sequences and contrast enhancement suffer from poor specificity. • DWI with ADC mapping and DCE may help to make a correct diagnosis, but further research is needed to better understand the value of these functional MRI techniques.

Focal Nodular Hyperplasia-Like Lesion in a Girl with Obesity and Fatty Liver.

Focal Nodular Hyperplasia-Like Lesion in a Girl with Obesity and Fatty Liver.