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Multidetector 64 slice ct scanner

Manufactured by GE Healthcare
Sourced in United States

The Multidetector 64-slice CT scanner is a medical imaging device manufactured by GE Healthcare. It is designed to capture high-resolution, three-dimensional images of the human body using advanced computed tomography (CT) technology. The scanner features 64 detector rows, enabling it to acquire multiple slices of data simultaneously for faster and more efficient image acquisition.

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2 protocols using multidetector 64 slice ct scanner

1

Cholecystectomy Specimen Diagnosis Protocol

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The final diagnosis was made either on the basis of histopathological evaluation of the cholecystectomy specimen or in cases of unresectable disease, on the basis of contrast-enhanced CT scan, performed using multidetector 64-slice CT scanner (General Electric Medical Systems, Milwaukee, WI, USA), as per the current optimized protocol. In the patients who were not subjected to surgical resection, the final diagnosis was confirmed by image-guided (CT or US) biopsy and subsequent histopathological evaluation.
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2

Coronary Artery Disease Prevalence and Outcomes

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This retrospective cohort study was performed on patients who were referred for CTCA to the multi-detector CT scan unit of Al-Zahra hospital, Isfahan, Iran, between March 2010 and March 2011. All CTCA studies were performed with a multi-detector 64-slice CT scanner (General Electric). About 527 patients with known or suspected CAD, who had undergone CTCA within last year were enrolled. Among them, data of 465 patients who had normal (no stenosis, n = 362) or non-significant CTCA findings (stenosis <50% of luminal narrowing, n = 103) were analyzed and prevalence of cardiac risk factors and major adverse cardiac events (MACE) were compared between these groups.15 (link) According to the number of involved coronary arteries, patients with non-significant coronary obstruction were subdivided to a single coronary vessel, two-coronary-vessel, and three-coronary-vessel involvement. Those who were not available for follow-up were excluded. In addition to the demographic information, data about patients’ symptoms and risk factors at the time of admission were extracted from their files.
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