Publications by authors named "Eide Sterling"

Objective: There is surging interest in using dual-energy computed tomography (DECT) to identify cardiovascular monosodium urate (MSU) deposits in patients with gout. We sought to examine the prevalence and characterization of cardiovascular DECT artifacts using non-electrocardiogram (EKG)-gated DECT pulmonary angiograms.

Methods: We retrospectively reviewed non-EKG-gated DECT pulmonary angiograms performed on patients with and without gout at a single academic center.

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Introduction: Metastatic spinal cord compression (MSCC) is a disastrous complication of advanced malignancy. A deep learning (DL) algorithm for MSCC classification on CT could expedite timely diagnosis. In this study, we externally test a DL algorithm for MSCC classification on CT and compare with radiologist assessment.

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Purpose: To develop a deep learning (DL) model for epidural spinal cord compression (ESCC) on CT, which will aid earlier ESCC diagnosis for less experienced clinicians.

Methods: We retrospectively collected CT and MRI data from adult patients with suspected ESCC at a tertiary referral institute from 2007 till 2020. A total of 183 patients were used for training/validation of the DL model.

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Background: Metastatic epidural spinal cord compression (MESCC) is a disastrous complication of advanced malignancy. Deep learning (DL) models for automatic MESCC classification on staging CT were developed to aid earlier diagnosis. Methods: This retrospective study included 444 CT staging studies from 185 patients with suspected MESCC who underwent MRI spine studies within 60 days of the CT studies.

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Objective: To evaluate the impact of pre-operative contrast-enhanced mammography (CEM) in breast cancer patients with dense breasts.

Methods: We conducted a retrospective review of 232 histologically proven breast cancers in 200 women (mean age: 53.4 years ± 10.

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Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetitive and time consuming. Deep learning (DL) could provide faster and more consistent interpretation.

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Article Synopsis
  • The study aims to improve the efficiency and reliability of diagnosing lumbar spinal stenosis using a deep learning (DL) model that automates detection and classification based on MRI scans.
  • The research involved analyzing 446 lumbar spine MRI studies, with a focus on training and validating the model using various grading scales, and comparing its performance against experienced radiologists.
  • Results showed that the DL model achieved high detection accuracy for the central canal but had lower recall for neural foramina compared to radiologists, indicating potential areas for further refinement in the model's performance.
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Purpose: To determine the accuracy of a handheld ultrasound-guided optoacoustic tomography (US-OT) probe developed for human deep-tissue imaging in ex vivo assessment of tumor margins postlumpectomy.

Methods: A custom-built two-dimensional (2D) US-OT-handheld probe was used to scan 15 lumpectomy breast specimens. Optoacoustic signals acquired at multiple wavelengths between 700 and 1100 nm were reconstructed using model linear algorithm, followed by spectral unmixing for lipid and deoxyhemoglobin (Hb).

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Osteoblastoma is a rare, benign primary tumor of bone, accounting for < 1% of all bone tumors. We report the case of a 27-year-old female who developed pain and swelling five and a half years after a clavicular fracture and was subsequently found to have an osteoblastoma arising at the fracture site. This is the first reported case of an osteoblastoma developing after a fracture, although osteoid osteomas, which are histologically indistinguishable from osteoblastomas, have been reported at prior fracture sites.

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Background And Purpose: We assessed the feasibility of obtaining diagnostic quality images of the heart and thoracic aorta by extending the axis coverage of a non-ECG-gated computed tomographic angiogram performed in the primary evaluation of acute stroke without increasing the contrast dose.

Methods: Twenty consecutive patients with acute ischemic stroke within the 4.5 hours of symptom onset were prospectively recruited.

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Gout is a common entity; yet it is such a great mimicker in its imaging features that it can confuse clinicians and radiologists alike, sometimes leading to unnecessary investigations and treatment. We present a case of a 52 year old male renal transplant patient who presented with a slow growing mass in his left shin. The initial radiograph demonstrated a non-aggressive looking calcified lesion.

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