Jae Ho Sohn

Comparison of Existing Response Criteria in Patients with Hepatocellular Carcinoma Treated with Transarterial Chemoembolization Using a 3D Quantitative Approach

PURPOSE To compare currently available non-three-dimensional methods (Response Evaluation Criteria in Solid Tumors [RECIST], European Association for Study of the Liver [EASL], modified RECIST [mRECIST[) with three-dimensional (3D) quantitative methods of the index tumor as early response markers in predicting patient survival after initial transcatheter arterial chemoembolization (TACE). MATERIALS AND METHODS This was a retrospective single-institution HIPAA-compliant and institutional review board-approved study. From November 2001 to November 2008, 491 consecutive patients underwent intraarterial therapy for liver cancer with either conventional TACE or TACE with drug-eluting beads. A diagnosis of hepatocellular carcinoma (HCC) was made in 290 of these patients. The response of the index tumor on pre- and post-TACE magnetic resonance images was assessed retrospectively in 78 treatment-naïve patients with HCC (63 male; mean age, 63 years ± 11 [standard deviation]). Each response assessment method (RECIST, mRECIST, EASL, and 3D methods of volumetric RECIST [vRECIST] and quantitative EASL [qEASL]) was used to classify patients as responders or nonresponders by following standard guidelines for the uni- and bidimensional measurements and by using the formula for a sphere for the 3D measurements. The Kaplan-Meier method with the log-rank test was performed for each method to evaluate its ability to help predict survival of responders and nonresponders. Uni- and multivariate Cox proportional hazard ratio models were used to identify covariates that had significant association with survival. RESULTS The uni- and bidimensional measurements of RECIST (hazard ratio, 0.6; 95% confidence interval [CI]: 0.3, 1.0; P = .09), mRECIST (hazard ratio, 0.6; 95% CI: 0.6, 1.0; P = .05), and EASL (hazard ratio, 1.1; 95% CI: 0.6, 2.2; P = .75) did not show a significant difference in survival between responders and nonresponders, whereas vRECIST (hazard ratio, 0.6; 95% CI: 0.3, 1.0; P = .04), qEASL (Vol) (hazard ratio, 0.5; 95% CI: 0.3, 0.9; P = .02), and qEASL (%) (hazard ratio, 0.3; 95% CI: 0.15, 0.60; P < .001) did show a significant difference between these groups. CONCLUSION The 3D-based imaging biomarkers qEASL and vRECIST were tumor response criteria that could be used to predict patient survival early after initial TACE and enabled clear identification of nonresponders.

Class 3 semaphorin mediates dendrite growth in adult newborn neurons through Cdk5/FAK pathway.

Class 3 semaphorins are well-known axonal guidance cues during the embryonic development of mammalian nervous system. However, their activity on postnatally differentiated neurons in neurogenic regions of adult brains has not been characterized. We found that silencing of semaphorin receptors neuropilins (NRP) 1 or 2 in neural progenitors at the adult mouse dentate gyrus resulted in newly differentiated neurons with shorter dendrites and simpler branching in vivo. Tyrosine phosphorylation (Tyr 397) and serine phosphorylation (Ser 732) of FAK were essential for these effects. Semaphorin 3A and 3F mediate serine phosphorylation of FAK through the activation of Cdk5. Silencing of either Cdk5 or FAK in newborn neurons phenocopied the defects in dendritic development seen upon silencing of NRP1 or NRP2. Furthermore, in vivo overexpression of Cdk5 or FAK rescued the dendritic phenotypes seen in NRP1 and NRP2 deficient neurons. These results point to a novel role for class 3 semaphorins in promoting dendritic growth and branching during adult hippocampal neurogenesis through the activation of Cdk5-FAK signaling pathway.

Quality Initiatives: Statistical Control Charts: Simplifying the Analysis of Data for Quality Improvement

Quality improvement (QI) projects are an integral part of todays radiology practice, helping identify opportunities for improving outcomes by refining work processes. QI projects are typically driven by outcome measures, but the data can be difficult to interpret: The numbers tend to fluctuate even before a process is altered, and after a QI intervention takes place, it may be even more difficult to determine the cause of such vacillations. Control chart analysis helps the QI project team identify variations that should be targeted for intervention and avoid tampering in processes in which variation is random or harmless. Statistical control charts make it possible to distinguish among random variation or noise in the data, outlying tendencies that should be targeted for future intervention, and changes that signify the success of previous intervention. The data on control charts are plotted over time and integrated with various graphic devices that represent statistical reasoning (eg, control limits) to allow visualization of the intensity and overall effect-negative or positive-of variability. Even when variability has no substantial negative effect, appropriate intervention based on the results of control chart analysis can help increase the efficiency of a process by optimizing the central tendency of the outcome measure. Different types of control charts may be used to analyze the same outcome dataset: For example, paired charts of individual values (x) and the moving range (mR) allow robust and reliable analyses of most types of data from radiology QI projects. Many spreadsheet programs and templates are available for use in creating x-mR charts and other types of control charts.

Multimodality Imaging of Ethiodized Oil–loaded Radiopaque Microspheres during Transarterial Embolization of Rabbits with VX2 Liver Tumors

Purpose To assess the visibility of radiopaque microspheres during transarterial embolization (TAE) in the VX2 rabbit liver tumor model by using multimodality imaging, including single-snapshot radiography, cone-beam computed tomography (CT), multidetector CT, and micro-CT. Materials and Methods The study was approved by the institutional animal care and use committee. Fifteen VX2-tumor-bearing rabbits were assigned to three groups depending on the type of embolic agent injected: 70-150-μm radiopaque microspheres in saline (radiopaque microsphere group), 70-150-μm radiopaque microspheres in contrast material (radiopaque microsphere plus contrast material group), and 70-150-μm radiolucent microspheres in contrast material (nonradiopaque microsphere plus contrast material group). Rabbits were imaged with single-snapshot radiography, cone-beam CT, and multidetector CT. Three to 5 weeks after sacrifice, excised livers were imaged with micro-CT and histologic analysis was performed. The visibility of the embolic agent was assessed with all modalities before and after embolization by using a qualitative three-point scale score reading study and a quantitative assessment of the signal-to-noise ratio (SNR) change in various regions of interest, including the tumor and its feeding arteries. The Kruskal-Wallis test was used to compare the rabbit characteristics across groups, and the Wilcoxon signed rank test was used to compare SNR measurements before and after embolization. Results Radiopaque microspheres were qualitatively visualized within tumor feeding arteries and targeted tissue with all imaging modalities (P < .05), and their presence was confirmed with histologic examination. SNRs of radiopaque microsphere deposition increased after TAE on multidetector CT, cone-beam CT, and micro-CT images (P < .05). Similar results were obtained when contrast material was added to radiopaque microspheres, except for additional image attenuation due to tumor enhancement. For the group with nonradiopaque microspheres and contrast material, retained tumoral contrast remained qualitatively visible with all modalities except for micro-CT, which demonstrated soluble contrast material washout over time. Conclusion Radiopaque microspheres were visible with all imaging modalities and helped increase conspicuity of the tumor as well as its feeding arteries after TAE in a rabbit VX2 liver tumor model. (©) RSNA, 2015.

Validation of the Hong Kong Liver Cancer Staging System in Determining Prognosis of the North American Patients Following Intra-arterial Therapy

Background & Aims There is debate over the best way to stage hepatocellular carcinoma (HCC). We attempted to validate the prognostic and clinical utility of the recently developed Hong Kong Liver Cancer (HKLC) staging system, a hepatitis B–based model, and compared data with that from the Barcelona Clinic Liver Cancer (BCLC) staging system in a North American population that underwent intra‐arterial therapy (IAT). Methods We performed a retrospective analysis of data from 1009 patients with HCC who underwent IAT from 2000 through 2014. Most patients had hepatitis C or unresectable tumors; all patients underwent IAT, with or without resection, transplantation, and/or systemic chemotherapy. We calculated HCC stage for each patient using 5‐stage HKLC (HKLC‐5) and 9‐stage HKLC (HKLC‐9) system classifications, and the BCLC system. Survival information was collected up until the end of 2014 at which point living or unconfirmed patients were censored. We compared performance of the BCLC, HKLC‐5, and HKLC‐9 systems in predicting patient outcomes using Kaplan‐Meier estimates, calibration plots, C statistic, Akaike information criterion, and the likelihood ratio test. Results Median overall survival time, calculated from first IAT until date of death or censorship, for the entire cohort (all stages) was 9.8 months. The BCLC and HKLC staging systems predicted patient survival times with significance (P < .001). HKLC‐5 and HKLC‐9 each demonstrated good calibration. The HKLC‐5 system outperformed the BCLC system in predicting patient survival times (HKLC C = 0.71, Akaike information criterion = 6242; BCLC C = 0.64, Akaike information criterion = 6320), reducing error in predicting survival time (HKLC reduced error by 14%, BCLC reduced error by 12%), and homogeneity (HKLC chi‐square = 201, P < .001; BCLC chi‐square = 119, P < .001) and monotonicity (HKLC linear trend chi‐square = 193, P < .001; BCLC linear trend chi‐square = 111, P < .001). Small proportions of patients with HCC of stages IV or V, according to the HKLC system, survived for 6 months and 4 months, respectively. Conclusions In a retrospective analysis of patients who underwent IAT for unresectable HCC, we found the HKLC‐5 staging system to have the best combination of performances in survival separation, calibration, and discrimination; it consistently outperformed the BCLC system in predicting survival times of patients. The HKLC system identified patients with HCC of stages IV and V who are unlikely to benefit from IAT.

Feasibility of a Modified Cone-Beam CT Rotation Trajectory to Improve Liver Periphery Visualization during Transarterial Chemoembolization

PURPOSE To compare liver coverage and tumor detectability by using preprocedural magnetic resonance (MR) images as a reference, as well as radiation exposure of cone-beam computed tomography (CT) with different rotational trajectories. MATERIALS AND METHODS Fifteen patients (nine men and six women; mean age ± standard deviation, 65 years ± 5) with primary or secondary liver cancer were retrospectively included in this institutional review board-approved study. A modified cone-beam CT protocol was used in which the C-arm rotates from +55° to -185° (open arc cone-beam CT) instead of -120° to +120° (closed arc cone-beam CT). Each patient underwent two sessions of transarterial chemoembolization between February 2013 and March 2014 with closed arc and open arc cone-beam CT (during the first and second transarterial chemoembolization sessions, respectively, as part of the institutional transarterial chemoembolization protocol). For each cone-beam CT examination, liver volume and tumor detectability were assessed by using MR images as the reference. Radiation exposure was compared by means of a phantom study. For statistical analysis, paired t tests and a Wilcoxon signed rank test were performed. RESULTS Mean liver volume imaged was 1695 cm(3) ± 542 and 1857 cm(3) ± 571 at closed arc and open arc cone-beam CT, respectively. The coverage of open arc cone-beam CT was significantly higher compared with closed arc cone-beam CT (97% vs 86% of the MR imaging liver volume, P = .002). In eight patients (53%), tumors were partially or completely outside the closed arc cone-beam CT field of view. All tumors were within the open arc cone-beam CT field of view. The open arc cone-beam CT radiation exposure by means of weighted CT index was slightly lower compared with that of closed arc cone-beam CT (-5.1%). CONCLUSION Open arc cone-beam CT allowed for a significantly improved intraprocedural depiction of peripheral hepatic tumors while achieving a slight radiation exposure reduction.

Imaging Biomarkers of Tumor Response in Neuroendocrine Liver Metastases Treated with Transarterial Chemoembolization: Can Enhancing Tumor Burden of the Whole Liver Help Predict Patient Survival?

Purpose To investigate whether whole-liver enhancing tumor burden [ETB] can serve as an imaging biomarker and help predict survival better than World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), modified RECIST (mRECIST), and European Association for the Study of the Liver (EASL) methods in patients with multifocal, bilobar neuroendocrine liver metastases (NELM) after the first transarterial chemoembolization (TACE) procedure. Materials and Methods This HIPAA-compliant, institutional review board-approved retrospective study included 51 patients (mean age, 57.8 years ± 13.2; range, 13.5-85.8 years) with multifocal, bilobar NELM treated with TACE. The largest area (WHO), longest diameter (RECIST), longest enhancing diameter (mRECIST), largest enhancing area (EASL), and largest enhancing volume (ETB) were measured at baseline and after the first TACE on contrast material-enhanced magnetic resonance images. With three-dimensional software, ETB was measured as more than 2 standard deviations the signal intensity of a region of interest in normal liver. Response was assessed with WHO, RECIST, mRECIST, and EASL methods according to their respective criteria. For ETB response, a decrease in enhancement of at least 30%, 50%, and 65% was analyzed by using the Akaike information criterion. Survival analysis included Kaplan-Meier curves and Cox regressions. Results Treatment response occurred in 5.9% (WHO criteria), 2.0% (RECIST), 25.5% (mRECIST), and 23.5% (EASL criteria) of patients. With 30%, 50%, and 65% cutoffs, ETB response was seen in 60.8%, 39.2%, and 21.6% of patients, respectively, and was the only biomarker associated with a survival difference between responders and nonresponders (45.0 months vs 10.0 months, 84.3 months vs 16.7 months, and 85.2 months vs 21.2 months, respectively; P < .01 for all). The 50% cutoff provided the best survival model (hazard ratio [HR]: 0.2; 95% confidence interval [CI]: 0.1, 0.4). At multivariate analysis, ETB response was an independent predictor of survival (HR: 0.2; 95% CI: 0.1, 0.6). Conclusion Volumetric ETB is an early treatment response biomarker and surrogate for survival in patients with multifocal, bilobar NELM after the first TACE procedure.

Renal Cell Carcinoma Metastatic to the Liver: Early Response Assessment after Intraarterial Therapy Using 3D Quantitative Tumor Enhancement Analysis

PURPOSE Liver metastases from renal cell carcinoma (RCC) are not uncommon in the course of disease. However, data about tumor response to intraarterial therapy (IAT) are scarce. This study assessed whether changes of enhancing tumor volume using quantitative European Association for the Study of the Liver (qEASL) on magnetic resonance imaging (MRI) and computed tomography (CT) can evaluate tumor response and predict overall survival (OS) early after therapy. METHODS AND MATERIALS Fourteen patients with liver metastatic RCC treated with IAT (transarterial chemoembolization: n= 9 and yttrium-90: n= 5) were retrospectively included. All patients underwent contrast-enhanced imaging (MRI: n= 10 and CT: n= 4) 3 to 4 weeks pre- and posttreatment. Response to treatment was evaluated on the arterial phase using Response Evaluation Criteria in Solid Tumors (RECIST), World Health Organization, modified RECIST, EASL, tumor volume, and qEASL. Paired t test was used to compare measurements pre- and post-IAT. Patients were stratified into responders (≥65% decrease in qEASL) and nonresponders (<65% decrease in qEASL). OS was evaluated using Kaplan-Meier curves with log-rank test and the Cox proportional hazard model. RESULTS Mean qEASL (cm3) decreased from 93.5 to 67.2 cm3 (P= .004) and mean qEASL (%) from 63.1% to 35.6% (P= .001). No significant changes were observed using other response criteria. qEASL was the only significant predictor of OS when used to stratify patients into responders and nonresponders with median OS of 31.9 versus 11.1 months (hazard ratio [HR], 0.43; 95% confidence interval [CI], 0.19-0.97; P= .042) for qEASL (cm3) and 29.9 versus 10.2 months (HR, 0.09; 95% CI, 0.01-0.74; P= .025) for qEASL (%). CONCLUSION Three-dimensional (3D) quantitative tumor analysis is a reliable predictor of OS when assessing treatment response after IAT in patients with RCC metastatic to the liver. qEASL outperforms conventional non-3D methods and can be used as a surrogate marker for OS early after therapy.

Large Scale Semi-Automated Labeling of Routine Free-Text Clinical Records for Deep Learning

Breast cancer is a leading cause of cancer death among women in the USA. Screening mammography is effective in reducing mortality, but has a high rate of unnecessary recalls and biopsies. While deep learning can be applied to mammography, large-scale labeled datasets, which are difficult to obtain, are required. We aim to remove many barriers of dataset development by automatically harvesting data from existing clinical records using a hybrid framework combining traditional NLP and IBM Watson. An expert reviewer manually annotated 3521 breast pathology reports with one of four outcomes: left positive, right positive, bilateral positive, negative. Traditional NLP techniques using seven different machine learning classifiers were compared to IBM Watson’s automated natural language classifier. Techniques were evaluated using precision, recall, and F-measure. Logistic regression outperformed all other traditional machine learning classifiers and was used for subsequent comparisons. Both traditional NLP and Watson’s NLC performed well for cases under 1024 characters with weighted average F-measures above 0.96 across all classes. Performance of traditional NLP was lower for cases over 1024 characters with an F-measure of 0.83. We demonstrate a hybrid framework using traditional NLP techniques combined with IBM Watson to annotate over 10,000 breast pathology reports for development of a large-scale database to be used for deep learning in mammography. Our work shows that traditional NLP and IBM Watson perform extremely well for cases under 1024 characters and can accelerate the rate of data annotation.

Prospective Comparison of Diagnostic Accuracy Between Point-of-Care and Conventional Ultrasound in a General Diagnostic Department: Implications for Resource-Limited Settings

To compare the diagnostic accuracy of hand‐held point‐of‐care (POC) versus conventional sonography in a general diagnostic setting with the intention to inform medical providers or clinicians on the rational use of POC ultrasound in resource limited settings.