Mayo Clin Proc Innov Qual Outcomes
October 2023
Objective: To better understand the mortality and notable characteristics of patients initially denied intensive care unit (ICU) admission that are later admitted on reconsultation.
Patients And Methods: We collected data regarding all adult inpatients (n=3725) who received one or more ICU consults at an academic tertiary care hospital medical center between January 1, 2018 and October 1, 2021. We compared patients who were initially denied ICU admission and later admitted on reconsultation (C2A1, n=144) with those who were admitted after the first consultation (C1A1, n=2286) and those denied at first consult and never later admitted (C1A0, n=1295).
Background: Rapid response teams (RRTs) have impacted the management of decompensating patients, potentially improving mortality. Few studies address the significance of RRT timing relative to hospital admission. We aimed to identify outcomes of adult patients who trigger immediate RRT activation, defined as within 4 hours of admission and compare with RRT later in admission or do not require RRT activation, and identify risk factors that predispose toward immediate RRT activation.
View Article and Find Full Text PDFBackground: A small proportion of non-small cell lung cancers (NSCLCs) have been observed to spread to distant lymph nodes (N3) or metastasize (M1) or both, while the primary tumor is small (≤3 cm, T1). These small aggressive NSCLCs (SA-NSLSC) are important as they are clinically significant, may identify unique biologic pathways, and warrant aggressive follow-up and treatment. This study identifies factors associated with SA-NSCLC and attempts to validate a previous finding that women with a family history of lung cancer are at particularly elevated risk of SA-NSCLC.
View Article and Find Full Text PDFObjective: The purpose of this study is to evaluate radiologists' performance in detecting actionable nodules on chest CT when aided by a pulmonary vessel image-suppressed function and a computer-aided detection (CADe) system.
Materials And Methods: A novel computerized pulmonary vessel image-suppressed function with a built-in CADe (VIS/CADe) system was developed to assist radiologists in interpreting thoracic CT images. Twelve radiologists participated in a comparative study without and with the VIS/CADe using 324 cases (involving 95 cancers and 83 benign nodules).
The utilization of unnatural amino acids (UAAs) in bioconjugations is ideal due to their ability to confer a degree of bioorthogonality and specificity. In order to elucidate optimal conditions for the preparation of bioconjugates with UAAs, we synthesized 9 UAAs with variable methylene tethers (2-4) and either an azide, alkyne, or halide functional group. All 9 UAAs were then incorporated into green fluorescent protein (GFP) using a promiscuous aminoacyl-tRNA synthetase.
View Article and Find Full Text PDFComputer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. Computer-aided detection systems mark regions of an image that may reveal specific abnormalities and are used to alert clinicians to these regions during image interpretation. Computer-aided diagnosis systems provide an assessment of a disease using image-based information alone or in combination with other relevant diagnostic data and are used by clinicians as a decision support in developing their diagnoses.
View Article and Find Full Text PDFComputer-aided detection/diagnosis (CAD) is increasingly used for decision support by clinicians for detection and interpretation of diseases. However, there are no quality assurance (QA) requirements for CAD in clinical use at present. QA of CAD is important so that end users can be made aware of changes in CAD performance both due to intentional or unintentional causes.
View Article and Find Full Text PDFPurpose: To demonstrate possible superiority in the performance of a radiologist who is tasked with detecting actionable nodules and aided by the bone suppression and soft-tissue visualization algorithm of a new software program that produces a modified image by suppressing the ribs and clavicles, filtering noise, and equalizing the contrast in the area of the lungs.
Materials And Methods: The study and use of anonymized and deidentified data received approval from the MedStar-Georgetown University Oncology Institutional Review Board. Informed consent was obtained from 15 study radiologists.
Purpose: A learning-based approach integrating the use of pixel-level statistical modeling and spiculation detection is presented for the segmentation of mammographic masses with ill-defined margins and spiculations.
Methods: The algorithm involves a multiphase pixel-level classification, using a comprehensive group of features computed from regional intensity, shape, and textures, to generate a mass-conditional probability map (PM). Then, the mass candidate, along with the background clutters consisting of breast fibroglandular and other nonmass tissues, is extracted from the PM by integrating the prior knowledge of shape and location of masses.
Front Biosci (Elite Ed)
January 2010
In this paper, we introduce a C-scan ultrasound prototype and three imaging modalities for the detection of foreign objects inserted in porcine soft tissue. The object materials include bamboo, plastics, glass and aluminum alloys. The images of foreign objects were acquired using the C-scan ultrasound, a portable B-scan ultrasound, film-based radiography, and computerized radiography.
View Article and Find Full Text PDFIntroduction: Chest radiographs are routinely employed in clinical practice. Radiographic findings that are abnormal suspicious (AS) for lung cancer occur commonly. The majority of AS radiographic abnormalities are not cancer.
View Article and Find Full Text PDFAcad Radiol
February 2008
Rationale And Objectives: To demonstrate the value of a new data visualization and exploration method for mutlireader-multicase receiver operating characteristic (MRMC-ROC) experiments of computer-aided detection (CAD) algorithms that uses three-dimensional (3D) heat maps tool adapted from gene expression array analysis.
Materials And Methods: We are using data from a clinical trial of a commercial CAD system for lung cancer detection (RapidScreen RS-2000, Riverain Medical Group, Miamisburg, OH, and Rockville, MD). 3D heat maps, originally developed for displaying changes in gene expression after cancer chemotherapy in MATLAB, were modified to display the radiologists confidence levels as they interpreted chest radiographs and used to visualize the radiologists confidence levels before and after the provision of a CAD system.
Cancer Epidemiol Biomarkers Prev
October 2007
Background: Some non-small cell lung cancers (NSCLC) progress to distant lymph nodes or metastasize while relatively small. Such small aggressive NSCLCs (SA-NSCLC) are no longer resectable with curative intent, carry a grave prognosis, and may involve unique biological pathways. This is a study of factors associated with SA-NSCLC.
View Article and Find Full Text PDFInt J Biomed Imaging
November 2012
Image-based change quantitation has been recognized as a promising tool for accurate assessment of tumor's early response to chemoprevention in cancer research. For example, various changes on breast density and vascularity in glandular tissue are the indicators of early response to treatment. Accurate extraction of glandular tissue from pre- and postcontrast magnetic resonance (MR) images requires a nonrigid registration of sequential MR images embedded with local deformations.
View Article and Find Full Text PDFOur purpose in this work was to develop an automatic boundary detection method for mammographic masses and to rigorously test this method via statistical analysis. The segmentation method utilized a steepest change analysis technique for determining the mass boundaries based on a composed probability density cost function. Previous investigators have shown that this function can be utilized to determine the border of the mass body.
View Article and Find Full Text PDFIEEE Trans Med Imaging
September 2003
A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images.
View Article and Find Full Text PDFIEEE Trans Med Imaging
February 2002
A multiple circular path convolution neural network (MCPCNN) architecture specifically designed for the analysis of tumor and tumor-like structures has been constructed. We first divided each suspected tumor area into sectors and computed the defined mass features for each sector independently. These sector features were used on the input layer and were coordinated by convolution kernels of different sizes that propagated signals to the second layer in the neural network system.
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