Dynamic Elevation of Aromatic Amino Acids in Hepatitis C Virus-Induced Cirrhosis After a Standard Meal.

INTRODUCTION: Perturbations in aromatic (AAAs) and branched-chain amino acids (BCAAs) are seen in decompensated liver disease. The aim of this study was to evaluate the dynamic, postprandial relationship between hepatitis C virus-induced liver disease and amino acid concentrations in patients with compensated liver disease. METHODS: Patients infected with hepatitis C virus underwent a baseline liver biopsy to determine Ishak Fibrosis Score and evaluate the liver transcriptome. Patients ate a standard meal and underwent peripheral vein sampling at defined intervals. Quantitative analysis of amino acids was performed using liquid chromatography-tandem mass spectrometry. RESULTS: At baseline, there was no difference in AAA and BCAA concentrations between patients with cirrhosis and non-cirrhotic patients. After a standard meal, AAAs, but not BCAAs, were elevated in patients with cirrhosis compared with non-cirrhotic patients at every time point. The HepQuant SHUNT fraction was significantly higher in patients with cirrhosis and positively correlated with AAA concentration at all time points, but not BCAA. Analysis of the hepatic transcriptome demonstrated greater downregulation of the AAA degradation pathways than the BCAA degradation pathways. DISCUSSION: At baseline, cirrhotic patients with compensated liver disease have adequate reserve liver function to metabolize AAAs and BCAAs. When faced with a metabolic stressor, such as a standard meal, patients with cirrhosis are less able to metabolize the increased load of AAAs. This impairment correlates with portosystemic shunting. Further evaluation of AAA levels in compensated liver disease might further the understanding of the liver-muscle axis and the role it may play in the development of sarcopenia in liver disease.

CT Evaluation of Lymph Nodes That Merge or Split during the Course of a Clinical Trial: Limitations of RECIST 1.1.

Purpose To compare Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 with volumetric measurement in the setting of target lymph nodes that split into two or more nodes or merge into one conglomerate node. Materials and Methods In this retrospective study, target lymph nodes were evaluated on CT scans from 166 patients with different types of cancer; 158 of the scans came from The Cancer Imaging Archive. Each target node was measured using RECIST 1.1 criteria before and after merging or splitting, followed by volumetric segmentation. To compare RECIST 1.1 with volume, a single-dimension hypothetical diameter (HD) was determined from the nodal volume. The nodes were divided into three groups: (a) one-target merged (one target node merged with other nodes); (b) two-target merged (two neighboring target nodes merged); and (c) split node (a conglomerate node cleaved into smaller fragments). Bland-Altman analysis and t test were applied to compare RECIST 1.1 with HD. On the basis of the RECIST 1.1 concept, we compared response category changes between RECIST 1.1 and HD. Results The data set consisted of 30 merged nodes (19 one-target merged and 11 two-target merged) and 20 split nodes (mean age for all 50 included patients, 50 years ± 7 [standard deviation]; 38 men). RECIST 1.1, volumetric, and HD measurements indicated an increase in size in all one-target merged nodes. While volume and HD indicated an increase in size for nodes in the two-target merged group, RECIST 1.1 showed a decrease in size in all two-target merged nodes. Although volume and HD demonstrated a decrease in size of all split nodes, RECIST 1.1 indicated an increase in size in 60% (12 of 20) of the nodes. Discrepancy of the response categories between RECIST 1.1 and HD was observed in 5% (one of 19) in one-target merged, 82% (nine of 11) in two-target merged, and 55% (11 of 20) in split nodes. Conclusion RECIST 1.1 does not optimally reflect size changes when lymph nodes merge or split. Keywords: CT, Lymphatic, Tumor Response Supplemental material is available for this article. © RSNA, 2021.

Automated abnormality classification of chest radiographs using deep convolutional neural networks.

As one of the most ubiquitous diagnostic imaging tests in medical practice, chest radiography requires timely reporting of potential findings and diagnosis of diseases in the images. Automated, fast, and reliable detection of diseases based on chest radiography is a critical step in radiology workflow. In this work, we developed and evaluated various deep convolutional neural networks (CNN) for differentiating between normal and abnormal frontal chest radiographs, in order to help alert radiologists and clinicians of potential abnormal findings as a means of work list triaging and reporting prioritization. A CNN-based model achieved an AUC of 0.9824 ± 0.0043 (with an accuracy of 94.64 ± 0.45%, a sensitivity of 96.50 ± 0.36% and a specificity of 92.86 ± 0.48%) for normal versus abnormal chest radiograph classification. The CNN model obtained an AUC of 0.9804 ± 0.0032 (with an accuracy of 94.71 ± 0.32%, a sensitivity of 92.20 ± 0.34% and a specificity of 96.34 ± 0.31%) for normal versus lung opacity classification. Classification performance on the external dataset showed that the CNN model is likely to be highly generalizable, with an AUC of 0.9444 ± 0.0029. The CNN model pre-trained on cohorts of adult patients and fine-tuned on pediatric patients achieved an AUC of 0.9851 ± 0.0046 for normal versus pneumonia classification. Pretraining with natural images demonstrates benefit for a moderate-sized training image set of about 8500 images. The remarkable performance in diagnostic accuracy observed in this study shows that deep CNNs can accurately and effectively differentiate normal and abnormal chest radiographs, thereby providing potential benefits to radiology workflow and patient care.

Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data.

Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment management and surgical planning. Recent advances of convolutional networks (ConvNets) have demonstrated higher accuracy than traditional mathematical models can be achieved in predicting future tumor volumes. This indicates that deep learning based data-driven techniques may have great potentials on addressing such problem. However, current 2D image patch based modeling approaches can not make full use of the spatio-temporal imaging context of the tumor's longitudinal 4D (3D + time) patient data. Moreover, they are incapable to predict clinically-relevant tumor properties, other than the tumor volumes. In this paper, we exploit to formulate the tumor growth process through convolutional Long Short-Term Memory (ConvLSTM) that extract tumor's static imaging appearances and simultaneously capture its temporal dynamic changes within a single network. We extend ConvLSTM into the spatio-temporal domain (ST-ConvLSTM) by jointly learning the inter-slice 3D contexts and the longitudinal or temporal dynamics from multiple patient studies. Our approach can incorporate other non-imaging patient information in an end-to-end trainable manner. Experiments are conducted on the largest 4D longitudinal tumor dataset of 33 patients to date. Results validate that the proposed ST-ConvLSTM model produces a Dice score of 83.2%±5.1% and a RVD of 11.2%±10.8%, both statistically significantly outperforming (p < 0.05) other compared methods of traditional linear model, ConvLSTM, and generative adversarial network (GAN) under the metric of predicting future tumor volumes. Additionally, our new method enables the prediction of both cell density and CT intensity numbers. Last, we demonstrate the generalizability of ST-ConvLSTM by employing it in 4D medical image segmentation task, which achieves an averaged Dice score of 86.3%±1.2% for left-ventricle segmentation in 4D ultrasound with 3 seconds per patient case.

Eligibility and Radiologic Assessment for Adjuvant Clinical Trials in Kidney Cancer.

PURPOSE: To harmonize the eligibility criteria and radiologic disease assessment definitions in clinical trials of adjuvant therapy for renal cell carcinoma (RCC). METHOD: On November 28, 2017, US-based experts in RCC clinical trials, including medical oncologists, urologic oncologists, regulators, biostatisticians, radiologists, and patient advocates, convened at a public workshop to discuss eligibility for trial entry and radiologic criteria for assessing disease recurrence in adjuvant trials in RCC. Multiple virtual meetings were conducted to address the issues identified at the workshop. RESULTS: The key workshop conclusions for adjuvant RCC therapy clinical trials were as follows. First, patients with non-clear cell RCC could be routinely included, preferably in an independent cohort. Second, patients with T3-4, N+M0, and microscopic R1 RCC tumors may gain the greatest advantages from adjuvant therapy. Third, trials of agents not excreted by the kidney should not exclude patients with severe renal insufficiency. Fourth, therapy can begin 4 to 16 weeks after the surgical procedure. Fifth, patients undergoing radical or partial nephrectomy should be equally eligible. Sixth, patients with microscopically positive soft tissue or vascular margins without gross residual or radiologic disease may be included in trials. Seventh, all suspicious regional lymph nodes should be fully resected. Eighth, computed tomography should be performed within 4 weeks before trial enrollment; for patients with renal insufficiency who cannot undergo computed tomography with contrast, noncontrast chest computed tomography and magnetic resonance imaging of the abdomen and pelvis with gadolinium should be performed. Ninth, when feasible, biopsy should be undertaken to identify any malignant disease. Tenth, when biopsy is not feasible, a uniform approach should be used to evaluate indeterminate radiologic findings to identify what constitutes no evidence of disease at trial entry and what constitutes radiologic evidence of disease. Eleventh, a uniform approach for establishing the date of recurrence should be included in any trial design. Twelfth, patient perspectives on the use of placebo, conditions for unblinding, and research biopsies should be considered carefully during the conduct of an adjuvant trial. CONCLUSIONS AND RELEVANCE: The discussions suggested that a uniform approach to eligibility criteria and radiologic disease assessment will lead to more consistently interpretable trial results in the adjuvant RCC therapy setting.

Eligibility and Radiologic Assessment in Adjuvant Clinical Trials in Bladder Cancer.

Objective: To harmonize eligibility criteria and radiographic disease assessments in clinical trials of adjuvant therapy for muscle-invasive bladder cancer (MIBC). Methods: National experts in bladder cancer clinical trial research, including medical and urologic oncologists, radiologists, biostatisticians, and patient advocates, convened at a public workshop on November 28, 2017, to discuss eligibility, radiographic entry criteria, and assessment of disease recurrence in adjuvant clinical trials in patients with MIBC. Results: The key workshop conclusions for adjuvant MIBC clinical trials included the following points: (1) patients with urothelial carcinoma with divergent histologic differentiation should be allowed to enroll; (2) neoadjuvant chemotherapy is defined as at least 3 cycles of neoadjuvant cisplatin-based combination chemotherapy; (3) patients with muscle-invasive, upper-tract urothelial carcinoma should be included in adjuvant trials of MIBC; (4) patients with severe renal insufficiency can enroll into trials using agents that are not renally excreted; (5) patients with microscopic surgical margins can be included; (6) patients should undergo a standard bilateral lymph node dissection prior to enrollment; (7) computed tomographic (CT) imaging should be performed within 4 weeks prior to enrollment. For patients with renal insufficiency who cannot undergo CT imaging with contrast, noncontrast chest CT and magnetic resonance imaging of the abdomen and pelvis with gadolinium should be done; (8) biopsy of indeterminate lesions to evaluate for malignant disease should be done when feasible; (9) a uniform approach to evaluate indeterminate radiographic lesions when biopsy is not feasible should be included in any trial design; (10) a uniform approach to determining the date of recurrence is important in interpreting adjuvant trial results; and (11) new high-grade, upper-tract primary tumors and new MIBC tumors should be considered recurrence events. Conclusions and Relevance: A uniform approach to eligibility criteria, definitions of no evidence of disease, and definitions of disease recurrence may lead to more consistent interpretations of adjuvant trial results in MIBC.

Evaluation of incidental pelvic fluid in relation to physiological changes in healthy pubescent children using pelvic magnetic resonance imaging.

BACKGROUND: Peritoneal free fluid can indicate an underlying disease process; however detection of minimal peritoneal free fluid in healthy children is not uncommon. OBJECTIVE: To assess the significance of incidental peritoneal free fluid within healthy children by MRI and its relation to physiological changes during puberty. MATERIALS AND METHODS: This prospective study was performed on 32 healthy volunteers (20 boys) between the ages of 8 years and 13 years, with consecutive follow-ups every 8-10 months for an average of 3 years. Body mass index (BMI) z-score, pubertal status, C-reactive protein and sex hormone concentrations were assessed prior to MRI studies. We reviewed a total of 120 pelvic MRI studies (61 boys) and measured the quantity of peritoneal free fluid. For statistical analysis we used linear mixed-model accounting for within-patient correlations. RESULTS: The mean ± standard deviation volume of peritoneal free fluid was 4.7±5.7 mL in girls and 1.9±3.1 mL in boys, with a maximum volume of 25 mL and 17 mL, respectively. The prevalence of peritoneal free fluid was significantly higher in girls (91%) compared to boys (67%; P=0.0035). In 15% of the girls and 3% of the boys the fluid was greater than 10 mL. The mean volume of peritoneal free fluid in the fourth stage of puberty was higher and significantly different from the mean volume in the first stage of puberty (P=0.01). CONCLUSION: Among healthy pubescent children, the prevalence of peritoneal free fluid is significantly higher in girls. The volume of peritoneal free fluid can reach volumes greater than 10 mL during normal puberty, especially in the fourth stage, and can be assumed normal in the absence of active disease.

Pharmacodynamic Study of Miransertib in Individuals with Proteus Syndrome.

Proteus syndrome is a life-threatening segmental overgrowth syndrome caused by a mosaic gain-of-function AKT1 variant. There are no effective treatments for Proteus syndrome. Miransertib is an AKT1 inhibitor that, prior to this study, has been evaluated only in adult oncology trials. We designed a non-randomized, phase 0/1 pilot study of miransertib in adults and children with Proteus syndrome to identify an appropriate dosage starting point for a future efficacy trial using a pharmacodynamic endpoint. The primary endpoint was a 50% reduction in the tissue levels of AKT phosphorylation from biopsies in affected individuals. We also evaluated secondary efficacy endpoints. We found that a dose of 5 mg/m2/day (1/7 the typical dose used in oncology) led to a 50% reduction in phosphorylated AKT (pAKT) in affected tissues from five of six individuals. This dose was well tolerated. Two of the six efficacy endpoints (secondary objectives) suggested that this agent may be efficacious. We observed a decrease in a cerebriform connective tissue nevus and a reduction in pain in children. We conclude that 5 mg/m2/day of miransertib is an appropriate starting point for future efficacy trials and that this agent shows promise of therapeutic efficacy in children with Proteus syndrome.

Vascular calcification in patients with large-vessel vasculitis compared to patients with hyperlipidemia.

OBJECTIVE: Calcification of the coronary arteries, aorta, and branch vessels can occur in both large-vessel vasculitis (LVV) and atherosclerosis. The study objective was to determine the location and amount of vascular calcification in patients with LVV versus hyperlipidemia (HLD) and to identify risk factors associated with vascular calcification in LVV. METHODS: Patients with giant cell arteritis (GCA), Takayasu's arteritis (TAK), and HLD underwent non-contrast computed tomography of the aorta and branch vessels. Vascular calcification in 14 specific arterial territories (4 segments of the aorta, 9 branch arteries, and the coronary arteries) was quantified throughout the large arteries by a cumulative Agatston score. Multivariate linear regression analyses were used to identify associations between traditional and disease-specific risk factors and total Agatston score. RESULTS: A total of 88 subjects, including GCA (n = 29); TAK (n = 22); and HLD (n = 37), participated. Prevalence of vascular calcification in the aorta and branch vessels significantly differed in the coronary arteries (HLD = 67%, GCA = 35%, TAK = 9%, p < 0.01). Total Agatston scores were higher in GCA (median 3260, range 25-18,138) versus HLD (460, 19-17,215) (p < 0.01) but did not significantly differ between GCA and TAK (1944, 52-47,520) (p = 0.53). In multivariable regression analysis, age, type of vasculitis, and prednisone use was associated with vascular calcification in LVV. CONCLUSION: The prevalence of coronary artery calcification is lower in LVV compared to HLD, but the amount of total vascular calcification throughout the large arteries is greater in LVV. Both traditional and disease-specific risk factors are associated with vascular calcification in LVV.

NegBio: a high-performance tool for negation and uncertainty detection in radiology reports.

Negative and uncertain medical findings are frequent in radiology reports, but discriminating them from positive findings remains challenging for information extraction. Here, we propose a new algorithm, NegBio, to detect negative and uncertain findings in radiology reports. Unlike previous rule-based methods, NegBio utilizes patterns on universal dependencies to identify the scope of triggers that are indicative of negation or uncertainty. We evaluated NegBio on four datasets, including two public benchmarking corpora of radiology reports, a new radiology corpus that we annotated for this work, and a public corpus of general clinical texts. Evaluation on these datasets demonstrates that NegBio is highly accurate for detecting negative and uncertain findings and compares favorably to a widely-used state-of-the-art system NegEx (an average of 9.5% improvement in precision and 5.1% in F1-score). AVAILABILITY: https://github.com/ncbi-nlp/NegBio.

Photon-Counting Computed Tomography for Vascular Imaging of the Head and Neck: First In Vivo Human Results.

PURPOSE: The purpose of this study was to evaluate image quality of a spectral photon-counting detector (PCD) computed tomography (CT) system for evaluation of major arteries of the head and neck compared with conventional single-energy CT scans using energy-integrating detectors (EIDs). METHODS: In this institutional review board-approved study, 16 asymptomatic subjects (7 men) provided informed consent and received both PCD and EID contrast-enhanced CT scans of the head and neck (mean age, 58 years; range, 46-75 years). Tube settings were (EID: 120 kVp/160 mA vs PCD: 140 kVp/108 mA) for all volunteers. Quantitative analysis included measurements of mean attenuation, image noise, and contrast-to-noise ratio (CNR). Spectral PCD data were used to reconstruct virtual monoenergetic images and iodine maps. A head phantom was used to validate iodine concentration measurements in PCD images only. Two radiologists blinded to detector type independently scored the image quality of different segments of the arteries, as well as diagnostic acceptability, image noise, and severity of artifacts of the PCD and EID images. Reproducibility was assessed with intraclass correlation coefficient. Linear mixed models that account for within-subject correlation of analyzed arterial segments were used. Linear regression and Bland-Altman analysis with 95% limits of agreement were used to calculate the accuracy of material decomposition. RESULTS: Photon-counting detector image quality scores were significantly higher compared with EID image quality scores with lower image noise (P < 0.01) and less image artifacts (P < 0.001). Photon-counting detector image noise was 9.1% lower than EID image noise (8.0 ± 1.3 HU vs 8.8 ± 1.5 HU, respectively, P < 0.001). Arterial segments showed artifacts on EID images due to beam hardening that were not present on PCD images. On PCD images of the head phantom, there was excellent correlation (R = 0.998) between actual and calculated iodine concentrations without significant bias (bias: -0.4 mg/mL [95% limits of agreements: -1.1 to 0.4 mg/mL]). Iodine maps had 20.7% higher CNR compared with nonspectral PCD (65.2 ± 9.0 vs 54.0 ± 4.5, P = 0.01), and virtual monoenergetic image at 70 keV showed similar CNR to nonspectral images (52.6 ± 4.2 vs 54.0 ± 4.5, P = 0.39). CONCLUSIONS: Photon-counting CT has the potential to improve the image quality of carotid and intracranial CT angiography compared with single-energy EID CT.

Comparison of findings of spontaneous splenorenal shunt in color Doppler sonography with multislice CT scan (64 slices) in liver transplant candidates.

BACKGROUND: Liver transplantation is the only definite treatment for end stage liver disease and it has high costs for the medical system so decreasing its complication and increasing its effectiveness is crucial. One of the factors that affect liver transplantation is the presence of spontaneous splenorenal shunt. Its diagnosis is mainly overlooked in pre-liver transplant patients. Main modality for its diagnosis is multislice CT scan however this is more expensive than sonography. Also, it exposes the patients to ionizing radiation. Considering the advantages of color Doppler ultrasound, studies to determine the sensitivity and specificity for detection of spontaneous splenorenal shunt is essential. MATERIALS AND METHODS: In our study 70 cirrhotic patients who were referred by liver transplant surgeons for evaluation of abdomen by CT and sonograhy were assessed for presence of spontaneous splenorenal shunt, left adrenal varix and left renal vein diameter and velocity and sensitivity and specificity of both modalities were checked. Patients in whom left renal vein could not evaluated by sonography and patients with splenectomy and nutcracker syndrome were excluded. RESULTS: In the point of 10 mm diameter of left renal vein in CT scan there was 78.6% sensitivity and 67.9% specificity for the presence of spontaneous splenorenal shunt. Left adrenal varix in CT had sensitivity of 71.4%, specificity of 100%, and positive predictive value of 100% and negative predictive value of 70% and varix below spleen in CT had sensitivity of 54.8%, specificity of 96.4%, and positive predictive value of 95.8% and negative predictive value of 58.7% for the presence of spontaneous splenorenal shunt. In the point of 8 mm diameter of left renal vein in sonography there was 66.7% sensitivity and 85.7% specificity for the presence of spontaneous splenorenal shunt. For the velocity of more than 35 cm/s of left renal vein in sonography there was 61.9% sensitivity and 82.1% specificity for the presence of spontaneous splenorenal shunt. Left adrenal varix in sonography had sensitivity of 45.2%, specificity of 96.4%, positive predictive value of 95% and negative predictive value of 54% for the presence of spontaneous splenorenal shunt. CONCLUSION: There was moderate agreement between CT scan and sonography for detection of spontaneous splenorenal shunt. CT scan is choice for detection of SSRS but sonography is somehow useful. It means that if sonograhy is positive it is sufficient, if negative, then CT should be performed. This is due to low sensitivity of sonography.

Levodopa-carbidopa may improve vision loss in indirect traumatic optic neuropathy.

To compare the effect of levodopa-carbidopa on the visual outcome of patients with indirect traumatic optic neuropathy (ITON), this randomized, double-blind, placebo-controlled study was conducted on 32 patients with ITON within 6 days after trauma. Patients underwent a complete ocular examination, pattern visual evoked potential (PVEP) testing, and high-resolution orbital computed tomography (CT) scanning. All patients received high-dose intravenous methylprednisolone, and levodopa was also administered to the levodopa group. The main outcome measures were best corrected visual acuity and PVEP results at the last-completed examination. The study was completed on 16 patients in the levodopa group and 10 patients in the placebo group because the others were lost to follow-up. There were no statistically significant differences for age, sex, involved eye, ocular and CT scan findings, pretreatment visual acuity, frequency of recordable PVEPs, and follow-up. In the levodopa group the visual acuity improved significantly after treatment (p = 0.009), but not in the placebo group (p = 0.34). After treatment the visual acuity in the levodopa group was 2.1 ± 2.1, and in the placebo group was 3.9 ± 1.2 (p = 0.008). In those who had visual acuity less than or equal to figure count, significant improvement in visual acuity was observed in the levodopa group (p = 0.03), but not in the placebo group (p = 0.34). However, the final visual acuity in these patients was comparable after treatment (p = 0.21). Nine patients (56.2%) in the levodopa group, and 1 (10%) in the placebo group, experienced improvement in visual acuity (p = 0.02). The frequency of unrecordable PVEPs were comparable in both groups (p = 0.09). Patients treated with levodopa within 6 days of onset of ITON were more likely to experience improvement in visual acuity than those in the placebo group.