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1.
Am J Case Rep ; 25: e943166, 2024 Mar 01.
Article in English | MEDLINE | ID: mdl-38425030

ABSTRACT

BACKGROUND Pneumatosis intestinalis (PI) is an uncommon condition that is not specific to any particular disease. Currently, there is no specific clinical guideline for treating and diagnosing PI. Furthermore, there are numerous causes of PI, which makes it difficult for clinicians - internal medicine physicians as well as surgeons - to take a clinical approach to diagnosis and treatment. CASE REPORT We present 3 clinical scenarios with PI. In the first patient there was a solitary image of PI, which was treated successfully with parenteral nutrition and intravenous antibiotics, and he was discharged after 5 days. The other 2 cases, which involve gas in the hepatic portal vein (HPVG), were handled in 2 distinct ways: surgically and conservatively. One needed diagnostic laparoscopy with necrotic segmentectomy and was discharged from the hospital on postoperative day 16. The last patient, received resuscitation treatment due to severe comorbidities and inability to tolerate surgery. After 3 days, abdominal CT scan revealed no signs of remaining PI. However, the patient was terminally discharged after 7 weeks of treatment due to septic shock caused by sacrococcygeal ulcer and urinary tract infection. By drawing comparisons among these 3 scenarios, we aim to highlight certain indicators for conservative treatment success. CONCLUSIONS PI with HPVG is a sign of severe prognosis, which often requires surgical intervention. However, the decision to manage conservatively or surgically depends on the patient's condition and other criteria such as peritonitis, free fluid in the abdominal cavity, and the presence of shock. Physicians should also weigh the benefits and risks of surgical intervention in critically ill patients.


Subject(s)
Abdominal Cavity , Laparoscopy , Male , Humans , Portal Vein , Necrosis , Tomography, X-Ray Computed/methods
3.
Quant Imaging Med Surg ; 9(8): 1429-1440, 2019 Aug.
Article in English | MEDLINE | ID: mdl-31559172

ABSTRACT

BACKGROUND: Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) that causes regions of ulceration within the interior of the colon. UC is estimated to afflict hundreds of thousands of people in the United States alone. In addition to traditional colonoscopy, ultrasonic techniques can detect colitis, but have limited spatial resolution, which frequently results in underdiagnoses. Nevertheless, clinical diagnosis of colitis is still generally performed via colonoscopy. Optical techniques such as confocal microscopy and optical coherence tomography (OCT) have been proposed to detect UC with higher resolution. However, UC can potentially alter tissue biomechanical properties, providing additional contrast for earlier and potentially more accurate detection. Although clinically available elastography techniques have been immensely useful, they do not have the resolution for imaging small tissues, such as in small mammalian disease models. However, OCT-based elastography, optical coherence elastography (OCE), is well-suited for imaging the biomechanical properties of small mammal colon tissue. METHODS: In this work, we induced elastic waves in ex vivo mouse colon tissue using a focused air-pulse. The elastic waves were detected using a phase-stabilized swept source OCE system, and the wave velocity was translated into stiffness. Measurements were taken at six positions for each sample to assess regional sample elasticity. Additional contrast between the control and diseased tissue was detected by analyzing the dispersion of the elastic wave and tissue optical properties obtained from the OCT structural image. RESULTS: The results show distinct differences (P<0.05) in the stiffness between control and colitis disease samples, with a Young's modulus of 11.8±8.0 and 5.1±1.5 kPa, respectively. The OCT signal standard deviations for control and diseased samples were 5.8±0.3 and 5.5±0.2 dB, respectively. The slope of the OCT signal spatial frequency decay in the control samples was 92.7±10.0 and 87.3±4.7 dB∙µm in the colitis samples. The slope of the linearly fitted dispersion curve in the control samples was 1.5 mm, and 0.8 mm in the colitis samples. CONCLUSIONS: Our results show that OCE can be utilized to distinguish tissue based on stiffness and optical properties. Our estimates of tissue stiffness suggest that the healthy colon tissue was stiffer than diseased tissue. Furthermore, structural analysis of the tissue indicates a distinct difference in tissue optical properties between the healthy and UC-like diseased tissue.

4.
IEEE Trans Image Process ; 19(8): 1978-86, 2010 Aug.
Article in English | MEDLINE | ID: mdl-20350842

ABSTRACT

Can images be decomposed into the sum of a geometric part and a textural part? In a theoretical breakthrough, [Y. Meyer, Oscillating Patterns in Image Processing and Nonlinear Evolution Equations. Providence, RI: American Mathematical Society, 2001] proposed variational models that force the geometric part into the space of functions with bounded variation, and the textural part into a space of oscillatory distributions. Meyer's models are simple minimization problems extending the famous total variation model. However, their numerical solution has proved challenging. It is the object of a literature rich in variants and numerical attempts. This paper starts with the linear model, which reduces to a low-pass/high-pass filter pair. A simple conversion of the linear filter pair into a nonlinear filter pair involving the total variation is introduced. This new-proposed nonlinear filter pair retains both the essential features of Meyer's models and the simplicity and rapidity of the linear model. It depends upon only one transparent parameter: the texture scale, measured in pixel mesh. Comparative experiments show a better and faster separation of cartoon from texture. One application is illustrated: edge detection.


Subject(s)
Algorithms , Cartoons as Topic , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Pattern Recognition, Automated/methods , Signal Processing, Computer-Assisted , Subtraction Technique , Data Mining/methods , Image Enhancement/methods , Reproducibility of Results , Sensitivity and Specificity
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