No abstract

In recent decades, endovascular aneurysm repair or endovascular aortic repair (EVAR) has become an acceptable alternative to open surgery for the treatment of thoracic and abdominal aortic aneurysms and other aortic pathologies such as the acute aortic syndromes (e.g., penetrating aortic ulcer, intramural hematoma, dissection). Available data suggest that endovascular repair is associated with lower perioperative 30-day all-cause mortality as well as a significant reduction in perioperative morbidity when compared to open surgery. Additionally, EVAR leads to decreased blood loss, eliminates the need for cross-clamping the aorta and has shorter recovery periods than traditional surgery. It is currently the preferred mode of treatment of thoracic and abdominal aortic aneurysms in a subset of patients who meet certain anatomic criteria conducive to endovascular repair. The main disadvantage of EVAR procedures is the high rate of post-procedural complications that often require secondary re-intervention. As a result, most authorities recommend lifelong imaging surveillance following repair. Available surveillance modalities include conventional radiography, computed tomography, magnetic resonance angiography, ultrasonography, nuclear imaging and conventional angiography, with computed tomography currently considered to be the gold standard for surveillance by most experts. Following endovascular abdominal aortic aneurysm (AAA) repair, the rate of complications is estimated to range between 16% and 30%. The complication rate is higher following thoracic EVAR (TEVAR) and is estimated to be as high as 38%. Common complications include both those related to the endograft device and systemic complications. Device-related complications include endoleaks, endograft migration or collapse, kinking and/or stenosis of an endograft limb and graft infection. Post-procedural systemic complications include end-organ ischemia, cerebrovascular and cardiovascular events and post-implantation syndrome. Secondary re-interventions are required in approximately 19% to 24% of cases following endovascular abdominal and thoracic aortic aneurysm repair respectively. Typically, most secondary reinterventions involve the use of percutaneous techniques such as placement of cuff extension devices, additional endograft components or stents, enhancement of endograft fixation, treatment of certain endoleaks using various embolization techniques and embolic agents and thrombolysis of occluded endograft components. Less commonly, surgical conversion and/or open surgical modification are required. In this article, we provide an overview of the most common complications that may occur following endovascular repair of thoracic and AAAs. We also summarize the current surveillance recommendations for detecting and evaluating these complications and discuss various current secondary re-intervention approaches that may typically be employed for treatment.

Purpose To present a method for identifying intrinsic imaging phenotypes in breast cancer tumors and to investigate their association with prognostic gene expression profiles. Materials and Methods The authors retrospectively analyzed dynamic contrast material–enhanced (DCE) magnetic resonance (MR) images of the breast in 56 women (mean age, 55.6 years; age range, 37–74 years) diagnosed with estrogen receptor–positive breast cancer between 2005 and 2010. The study was approved by the institutional review board and compliant with HIPAA. The requirement to obtain informed consent was waived. Primary tumors were assayed with a validated gene expression assay that provides a score for the likelihood of recurrence. A multiparametric imaging phenotype vector was extracted for each tumor by using quantitative morphologic, kinetic, and spatial heterogeneity features. Multivariate linear regression was performed to test associations between DCE MR imaging features and recurrence likelihood. To identify intrinsic imaging phenotypes, hierarchical clustering was performed on the extracted feature vectors. Multivariate logistic regression was used to classify tumors at high versus low or medium risk of recurrence. To determine the additional value of intrinsic phenotypes, the phenotype category was tested as an additional variable. Receiver operating characteristic analysis and the area under the receiver operating characteristic curve (Az) were used to assess classification performance. Results There was a moderate correlation (r = 0.71, R2 = 0.50, P < .001) between DCE MR imaging features and the recurrence score. DCE MR imaging features were predictive of recurrence risk as determined by the surrogate assay, with an Az of 0.77 (P < .01). Four dominant imaging phenotypes were detected, with two including only low- and medium-risk tumors. When the phenotype category was used as an additional variable, the Az increased to 0.82 (P < .01). Conclusion Intrinsic imaging phenotypes exist for breast cancer tumors and correlate with recurrence likelihood as determined with gene expression profiling. These imaging biomarkers could ultimately help guide treatment decisions.

Optical spectroscopy can provide useful diagnostic information about the morphological and biochemical changes related to the progression of precancer in epithelial tissue. As precancerous lesions develop, the optical properties of both the superficial epithelium and underlying stroma are altered; measuring spectral data as a function of depth has the potential to improve diagnostic performance. We describe a clinical spectroscopy system with a depth-sensitive, ball lens coupled fiber-optic probe for noninvasive in vivo measurement of oral autofluorescence and diffuse reflectance spectra. We report results of spectroscopic measurements from oral sites in normal volunteers and in patients with neoplastic lesions of the oral mucosa; results indicate that the addition of depth selectivity can enhance the detection of optical changes associated with precancer.