Clifford Yang

Posterolateral Corner Reconstruction of the Knee: Evaluation of a Technique With Clinical Outcomes and Stress Radiography

Background: Injuries to the posterolateral corner of the knee remain a challenging problem and have been cited frequently as a reason for failure of anterior and posterior cruciate ligament reconstructions. Although several reconstructive techniques currently exist, there are relatively few clinical outcomes data after reconstruction of the posterolateral corner. Purpose: The study was undertaken to examine the clinical outcomes and provide objective data using arthrometry and stress radiography of a posterolateral corner reconstruction technique. Study Design: Case series; Level of evidence, 4. Methods: A retrospective cohort study of a consecutive series of patients who underwent posterolateral corner reconstruction of the knee was evaluated. The surgery featured dual femoral tunnels, a transfibular tunnel, and a free graft to reconstruct the posterolateral corner of the knee. All patients had concomitant reconstruction of one or both cruciate ligaments. Outcomes were assessed using the Short Form–12, Lysholm, and Tegner knee scores. A clinical examination, KT-2000 arthrometry measurements, single-legged hop quotient, and varus and posterior Telos stress radiographs were obtained and compared with results for the contralateral, uninjured knees. Results: Twenty-four (83%) of 29 consecutive patients were evaluated at a mean 39 months postoperatively (range, 24-81 months). The mean Lysholm and Tegner knee scores were 83 and 6, respectively. The mean difference (± standard deviation) in total anterior-posterior side-to-side KT arthrometry measurements was 1.4 ± 1.3 mm. The varus stress radiographic mean side-to-side difference measured at 20° of flexion was 0.2 ± 1.9 mm. The mean radiographic posterior tibial displacement with a 15-kg stress at 90° of flexion was 3.2 ± 4.5 mm in patients undergoing posterior cruciate ligament reconstruction. Conclusion: This reconstruction of the posterolateral corner of the knee with concomitant cruciate ligament reconstruction restores varus and rotational stability at a minimum of 2 years postoperatively.

Neuroimaging findings and brain-behavioral correlates in a former boxer with chronic traumatic brain injury

Chronic traumatic brain injury (CTBI) is associated with contact sports such as boxing. CTBI results from repetitive blows to the head rather than from a single impact. CTBI individuals present with motor symptoms (incoordination, spasticity, parkinsonism), cognitive impairment (executive dysfunction, memory deficits) and neuropsychiatric symptoms (irritability, affective disturbances). The structural and functional neuroimaging findings and clinical presentation of a CTBI case are described. We propose hypotheses about the pathophysiology of the observed neuroimaging findings and their relationship to the neuropsychiatric symptoms of the patients.

Alcohol Dementia and Thermal Dysregulation: A Case Report and Review of the Literature

Wernickes encephalopathy and Korsakoffs psychosis in alcoholics are thought to be due to thiamine deficiency. When the process goes untreated, patients may develop alcohol-induced persisting dementia. We review the literature on thermal dysregulation and the place of thiamine treatment in Wernickes encephalopathy, Korsakoffs psychosis, and alcohol-induced persisting dementia. We describe a patient with alcohol-induced persisting dementia who showed thermal dysregulation which responded to parenteral but not oral thiamine. Subsequently, he developed aspiration pneumonia with associated fever reaction and expired. We describe the neuroimaging findings—diffuse cortical atrophy, ventricular dilatation, atrophy of the corpus callosum, hypothalamus, and medulla, and a probable arachnoid cyst in the left temporal tip. We conclude that thermal dysregulation was likely related to dysfunction of temperature regulatory brain centers, that thermal dysregulation was stabilized with parenteral but not oral thiamine, and that parenteral thiamine may have a role even in chronic cases of alcohol-induced persisting dementia.

Breast cancer screening using convolutional neural network and follow-up digital mammography

We propose a computer-aided detection (CAD) method for breast cancer screening using convolutional neural network (CNN) and follow-up scans. First, mammographic images are examined by three cascading object detectors to detect suspicious cancerous regions. Then all regional images are fed to a trained CNN (based on the pre-trained VGG-19 model) to filter out false positives. Three cascading detectors are trained with Haar features, local binary pattern (LBP) and histograms of oriented gradient (HOG) separately via an AdaBoost approach. The bounding boxes (BBs) from three featured detectors are merged to generate a region proposal. Each regional image, consisting of three channels, current scan (red channel), registered prior scan (green channel) and their difference (blue channel), is scaled to 224×224×3 for CNN classification. We tested the proposed method using our digital mammographic database including 69 cancerous subjects of mass, architecture distortion, and 27 healthy subjects, each of which includes two scans, current (cancerous or healthy), prior scan (healthy 1 year before). On average 165 BBs are created by three cascading classifiers on each mammogram, but only 3 BBs remained per image after the CNN classification. The overall performance is described as follows: sensitivity = 0.928, specificity = 0.991, FNR = 0.072, and FPI (false positives per image) = 0.004. Considering the early-stage cancerous status (1-year ago was normal), the performance of the proposed CAD method is very promising.

Survey on deep convolutional neural networks in mammography

The limitations of traditional Computer Aided Detection (CAD) systems for mammography, the extreme importance of early detection of breast cancer and the high impact of the false diagnosis of patients lead to investigating Deep Learning methods (DL) for mammograms. Deep Learning, in particular, Convolutional Neural Networks (CNNs) have been recently used for object localization and detection, risk assessment, and classification tasks in mammogram images. CNNs help radiologists provide more accurate diagnosis by delivering precise quantitative analysis of suspicious lesions in short time. This survey reviews the strengths and limitations of major CNNs applications in analyzing mammogram images. It summarizes 51 contributions on applying CNNs on various tasks in mammography. Moreover, it discusses the best practices done using CNN methods and suggesting directions for further improvement in medical images and in particular mammogram images.

Central Core Laboratory versus Site Interpretation of Coronary CT Angiography: Agreement and Association with Cardiovascular Events in the PROMISE Trial

Purpose To assess concordance and relative prognostic utility between central core laboratory and local site interpretation for significant coronary artery disease (CAD) and cardiovascular events. Materials and Methods In the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial, readers at 193 North American sites interpreted coronary computed tomographic (CT) angiography as part of the clinical evaluation of stable chest pain. Readers at a central core laboratory also interpreted CT angiography blinded to clinical data, site interpretation, and outcomes. Significant CAD was defined as stenosis greater than or equal to 50%; cardiovascular events were defined as a composite of cardiovascular death or myocardial infarction. Results In 4347 patients (51.8% women; mean age ± standard deviation, 60.4 years ± 8.2), core laboratory and site interpretations were discordant in 16% (683 of 4347), most commonly because of a finding of significant CAD by site but not by core laboratory interpretation (80%, 544 of 683). Overall, core laboratory interpretation resulted in 41% fewer patients being reported as having significant CAD (14%, 595 of 4347 vs 23%, 1000 of 4347; P < .001). Over a median follow-up period of 25 months, 1.3% (57 of 4347) sustained myocardial infarction or cardiovascular death. The C statistic for future myocardial infarction or cardiovascular death was 0.61 (95% confidence interval [CI]: 0.54, 0.68) for the core laboratory and 0.63 (95% CI: 0.56, 0.70) for the sites. Conclusion Compared with interpretation by readers at 193 North American sites, standardized core laboratory interpretation classified 41% fewer patients as having significant CAD.

Effect of Adjuvant Chemotherapy on Left Ventricular Remodeling in Women with Newly Diagnosed Primary Breast Cancer: A Pilot Prospective Longitudinal Cardiac Magnetic Resonance Imaging Study

Purpose: The aim of this study was to assess the left ventricular (LV) remodeling response to chemotherapy in low–cardiac-risk women with newly diagnosed nonmetastatic breast cancer. Cardiotoxic effects of chemotherapy are an increasing concern. To effectively interpret cardiac imaging studies performed for screening purposes in patients undergoing cancer therapy it is necessary to understand the normal changes in structure and function that may occur. Methods: Twenty women without preexisting cardiovascular disease, of a mean age of 50 years, newly diagnosed with nonmetastatic breast cancer and treated with anthracycline or trastuzumab, were prospectively enrolled and evaluated at four time points (at baseline, during chemotherapy, 2 weeks after chemotherapy, and 6 months after chemotherapy) using cardiac magnetic resonance imaging, blood samples, and a clinical questionnaire. Results: Over a 6-month period, the left ventricular ejection fraction (%) decreased (64.15±5.30 to 60.41±5.77, P<0.002) and the LV end-diastolic (mm) and end-systolic (mm) volumes increased (124.73±20.25 to 132.21±19.33, P<0.04 and 45.16±11.88 to 52.57±11.65, P<0.00, respectively). The LV mass (g) did not change (73.06±11.51 to 69.21±15.3, P=0.08), but the LV mass to LVEDV ratio (g/mm) decreased (0.594±0.098 to 0.530±0.124, P<0.04). Conclusions: In low–cardiac-risk women with nonmetastatic breast cancer, the increased LV volume and a mildly decreased left ventricular ejection fraction during and after chemotherapy do not seem to be associated with laboratory or clinical evidence of increased risk for heart failure.

Early breast cancer detection with digital mammograms using Haar-like features and AdaBoost algorithm

The current computer-aided detection (CAD) methods are not sufficiently accurate in detecting masses, especially in dense breasts and/or small masses (typically at their early stages). A small mass may not be perceived when it is small and/or homogeneous with surrounding tissues. Possible reasons for the limited performance of existing CAD methods are lack of multiscale analysis and unification of variant masses. The speed of CAD analysis is important for field applications. We propose a new CAD model for mass detection, which extracts simple Haar-like features for fast detection, uses AdaBoost approach for feature selection and classifier training, applies cascading classifiers for reduction of false positives, and utilizes multiscale detection for variant sizes of masses. In addition to Haar features, local binary pattern (LBP) and histograms of oriented gradient (HOG) are extracted and applied to mass detection. The performance of a CAD system can be measured with true positive rate (TPR) and false positives per image (FPI). We are collecting our own digital mammograms for the proposed research. The proposed CAD model will be initially demonstrated with mass detection including architecture distortion.

OT1-02-12: Early Detection of Cardiotoxicity by Advanced Cardiac Imaging and a Novel Biomarker in Breast Cancer Patients Undergoing Chemotherapy.

Background The survival rate of breast cancer patients has increased due to improvements in cancer treatment. However, many survivors develop irreversible or reversible cardiotoxicity associated with anthracycline or trastuzumab therapy, respectively. To detect cardiac damage, the currently accepted method is to measure left ventricular ejection fraction (LVEF) by echocardiography, which lacks the sensitivity to predict early cardiac dysfunction. Early identification of cardiotoxicity is essential to cancer survivors, as development of cardiomyopathy carries a worse outcome independent of cancer prognosis. Currently, there are no accepted guidelines for the early detection of myocardial injury. The use of cardiac biomarkers and more sensitive echocardiographic techniques have expanded options for monitoring, but have yet to reach a consensus. Hence, our study will evaluate the potential predictive value of novel cardiac biomarkers and advanced echocardiographic and cardiac magnetic resonance imaging (CMR) techniques to detect subclinical myocardial damage. Our findings may be applicable for monitoring new antineoplastic agents during food and drug administration (FDA) clinical trials. Trial Design Prospective cohort study with internal control of 20 patients newly diagnosed with breast cancer. The trial will assess endpoints at baseline, 2 weeks after initiation of therapy, and 2 weeks and 6 months after chemotherapy completion. 1. Primary Endpoint a. Decline in left ventricular ejection fraction assessed by CMR and 3D-echo not detected by conventional methods b. Presence of either myocardial fibrosis or edema detected by CMR c. Changes in myocardial deformation detected by echo or CMR strain d. Increase in cardiac biomarkers (Serum caspase-3 p17 peptide, Troponin I, B-type natriuretic peptide) and possible correlation with imaging parameters 2. Secondary Endpoint a. Development New York Heart Association class 1 to 4 symptoms b. Decrease in LVEF of ≥5% to ≤50% with or without symptoms Eligibility Criteria Inclusion Criteria: 1. Newly diagnosed stage I, II, or III breast cancer 2. Age between 18 and 75 years old. 3. Treatment with trastuzumab or anthracycline-based chemotherapy Exclusion Criteria: 1. History of cardiovascular disease 2. Pacemaker 3. History of mediastinal radiotherapy 4. Creatinine clearance 5. Serum bilirubin >2.0 mg/dl, ALT and AST > 100 U/1) 6. Hypertension, uncontrolled >140/90 7. LVEF 8. Claustrophobia Specific Aims 1. Detect early myocardial injury. 2. Evaluate early predictors of left ventricular dysfunction. 3. Evaluate timing of monitoring during or post treatment Statistical Method This is a pilot study and 20 patients are required to reach statistical significance with 85% power. All values will be analyzed as mean±SD or n (%). Categorical indicators will be analyzed using nonparametric statistics such as Cochran9s Q. Changes in imaging and biomarker parameters will be assessed using analysis of variance, while correlation between the two will be assessed using mixed models appropriate for binary outcome. Significance will be accepted at p ≤0.05 for all tests. Present accrual and target accrual Nine subjects are enrolled with a goal of 20. Contact for people interested in trial: 1. Dr. Erick Avelar, eavelar@uchc.edu 2. Dr. Susan Tannenbaum, stannenbaum@uchc.edu Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr OT1-02-12.