A 14-year-old female with no significant medical history presented with hypertensive urgency, in the setting of 4 to 6 weeks of diarrhea, abdominal pain, headaches, anemia, weight loss, and high blood pressures. Her evaluation revealed signs of a systemic inflammatory process that was most suspicious for inflammatory bowel disease. However, when her hypertension was evaluated with a renal Doppler ultrasound, there were signs of narrowing, stenosis, and hypoplasia that led to a diagnostic angiogram of the abdominal aorta. Full body positron emission tomography scan revealed multiple areas of stenosis and aortic thickening with enhancement compatible with Takayasu arteritis. She received prednisone, methotrexate, and infliximab with marked improvement in her clinical symptoms and inflammatory markers.
by
Ellen S. Regalado;
Lauren Mellor-Crummey;
Julie De Backer;
Alan C. Braverman;
Lesley Ades;
Susan Benedict;
Timothy J. Bradley;
M. Elizabeth Brickner;
Kathryn C. Chatfield;
Anne Child;
Cori Feist;
Kathryn W. Holmes;
Glen Joseph Iannucci;
Birgit Lorenz;
Paul Mark;
Takayuki Morisaki;
Hiroko Morisaki;
Shaine A. Morris;
Anna L. Mitchell;
John R. Ostergaard;
Julie Richer;
Denver Sallee;
Sherene Shalhub;
Mustafa Tekin;
Anthony Estrera;
Patricia Musolino;
Anji Yetman;
Reed Pyeritz;
Dianna M. Milewicz
PurposeSmooth muscle dysfunction syndrome (SMDS) due to heterozygous ACTA2 arginine 179 alterations is characterized by patent ductus arteriosus, vasculopathy (aneurysm and occlusive lesions), pulmonary arterial hypertension, and other complications in smooth muscle-dependent organs. We sought to define the clinical history of SMDS to develop recommendations for evaluation and management.MethodsMedical records of 33 patients with SMDS (median age 12 years) were abstracted and analyzed.ResultsAll patients had congenital mydriasis and related pupillary abnormalities at birth and presented in infancy with a patent ductus arteriosus or aortopulmonary window. Patients had cerebrovascular disease characterized by small vessel disease (hyperintense periventricular white matter lesions; 95%), intracranial artery stenosis (77%), ischemic strokes (27%), and seizures (18%). Twelve (36%) patients had thoracic aortic aneurysm repair or dissection at median age of 14 years and aortic disease was fully penetrant by the age of 25 years. Three (9%) patients had axillary artery aneurysms complicated by thromboembolic episodes. Nine patients died between the ages of 0.5 and 32 years due to aortic, pulmonary, or stroke complications, or unknown causes.ConclusionBased on these data, recommendations are provided for the surveillance and management of SMDS to help prevent early-onset life-threatening complications.
Accurate identification of in vivo nonlinear, anisotropic mechanical properties of the aortic wall of individual patients remains to be one of the critical challenges in the field of cardiovascular biomechanics. Since only the physiologically loaded states of the aorta are given from in vivo clinical images, inverse approaches, which take into account of the unloaded configuration, are needed for in vivo material parameter identification. Existing inverse methods are computationally expensive, which take days to weeks to complete for a single patient, inhibiting fast feedback for clinicians. Moreover, the current inverse methods have only been evaluated using synthetic data. In this study, we improved our recently developed multi-resolution direct search (MRDS) approach and the computation time cost was reduced to 1~2 hours. Using the improved MRDS approach, we estimated in vivo aortic tissue elastic properties of two ascending thoracic aortic aneurysm (ATAA) patients from pre-operative gated CT scans. For comparison, corresponding surgically-resected aortic wall tissue samples were obtained and subjected to planar biaxial tests. Relatively close matches were achieved for the in vivo-identified and ex vivo-fitted stress-stretch responses. It is hoped that further development of this inverse approach can enable an accurate identification of the in vivo material parameters from in vivo image data.