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BSREM reconstruction for improved detection of in-transit metastases with digital FDG-PET/CT in patients with malignant melanoma.


Aljared, Arwa; Alharbi, Abdullah Awad; Huellner, Martin W (2018). BSREM reconstruction for improved detection of in-transit metastases with digital FDG-PET/CT in patients with malignant melanoma. Clinical Nuclear Medicine, 43(5):370-371.

Abstract

Block sequential regularized expectation maximization (BSREM) is a Bayesian penalized-likelihood reconstruction algorithm for PET, which reaches full convergence without the detriment of deteriorating the image quality by noise. Therefore, BSREM might have implications particularly for the detection of small lesions, which may be beneficial in melanoma patients. Our case of a 70-year-old man with metastasized malignant melanoma illustrates the impact of such a novel iterative PET reconstruction algorithm. Whereas the lymph node metastases are seen with the latest generation ordered subset expectation maximization reconstruction, the in-transit metastases are identified straightforward only with BSREM reconstruction.

Abstract

Block sequential regularized expectation maximization (BSREM) is a Bayesian penalized-likelihood reconstruction algorithm for PET, which reaches full convergence without the detriment of deteriorating the image quality by noise. Therefore, BSREM might have implications particularly for the detection of small lesions, which may be beneficial in melanoma patients. Our case of a 70-year-old man with metastasized malignant melanoma illustrates the impact of such a novel iterative PET reconstruction algorithm. Whereas the lymph node metastases are seen with the latest generation ordered subset expectation maximization reconstruction, the in-transit metastases are identified straightforward only with BSREM reconstruction.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Nuclear Medicine
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Radiology, Nuclear Medicine and Imaging
Language:English
Date:1 May 2018
Deposited On:21 Aug 2018 12:22
Last Modified:29 Jul 2020 07:31
Publisher:Lippincott Williams & Wilkins
ISSN:0363-9762
OA Status:Green
Publisher DOI:https://doi.org/10.1097/RLU.0000000000002024
PubMed ID:29485444

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