Functional Imaging in Musculoskeletal Disorders in Menopause

Filippi, Luca; Camedda, Riccardo; Frantellizzi, Viviana; Urbano, Nicoletta; De Vincentis, Giuseppe; Schillaci, Orazio

doi:10.1053/j.semnuclmed.2023.10.001

Cited by 5 publications

(4 citation statements)

References 92 publications

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“…For instance, CT enables consistent quantitative tissue measurements using specific datasets. However, these anatomical imaging modalities cannot evaluate the molecular activity of skeletal muscles [38,46]. In contrast, PET is sensitive to glucose and fatty acid metabolism, as well as blood flow, allowing the assessment of regions of interest and tissue activation levels.…”

Section: Discussionmentioning

confidence: 99%

Radiopharmaceuticals for Skeletal Muscle PET Imaging

Park,

Lee

et al. 2024

IJMS

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The skeletal muscles account for approximately 40% of the body weight and are crucial in movement, nutrient absorption, and energy metabolism. Muscle loss and decline in function cause a decrease in the quality of life of patients and the elderly, leading to complications that require early diagnosis. Positron emission tomography/computed tomography (PET/CT) offers non-invasive, high-resolution visualization of tissues. It has emerged as a promising alternative to invasive diagnostic methods and is attracting attention as a tool for assessing muscle function and imaging muscle diseases. Effective imaging of muscle function and pathology relies on appropriate radiopharmaceuticals that target key aspects of muscle metabolism, such as glucose uptake, adenosine triphosphate (ATP) production, and the oxidation of fat and carbohydrates. In this review, we describe how [18F]fluoro-2-deoxy-D-glucose ([18F]FDG), [18F]fluorocholine ([18F]FCH), [11C]acetate, and [15O]water ([15O]H2O) are suitable radiopharmaceuticals for diagnostic imaging of skeletal muscles.

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Section: Discussionmentioning

confidence: 99%

Radiopharmaceuticals for Skeletal Muscle PET Imaging

Park,

Lee

et al. 2024

IJMS

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“…Moreover, despite the larger availability of CT scans and a common use in the investigation of muscle disorders associated with cachexia or sarcopenia, the added value of qualitative MRI is unquestionable in this clinical setting [ 24 , 25 ]. Even more important is quantitative MRI, given the availability of multiparametric sequence able to capture the wide heterogeneity of NMDs features [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

Convolutional Neural Network-Based Automated Segmentation of Skeletal Muscle and Subcutaneous Adipose Tissue on Thigh MRI in Muscular Dystrophy Patients

Aringhieri,

Astrea,

Marfisi

et al. 2024

JFMK

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We aim to develop a deep learning-based algorithm for automated segmentation of thigh muscles and subcutaneous adipose tissue (SAT) from T1-weighted muscle MRIs from patients affected by muscular dystrophies (MDs). From March 2019 to February 2022, adult and pediatric patients affected by MDs were enrolled from Azienda Ospedaliera Universitaria Pisana, Pisa, Italy (Institution 1) and the IRCCS Stella Maris Foundation, Calambrone-Pisa, Italy (Institution 2), respectively. All patients underwent a bilateral thighs MRI including an axial T1 weighted in- and out-of-phase (dual-echo). Both muscles and SAT were manually and separately segmented on out-of-phase image sets by a radiologist with 6 years of experience in musculoskeletal imaging. A U-Net1 and U-Net3 were built to automatically segment the SAT, all the thigh muscles together and the three muscular compartments separately. The dataset was randomly split into the on train, validation, and test set. The segmentation performance was assessed through the Dice similarity coefficient (DSC). The final cohort included 23 patients. The estimated DSC for U-Net1 was 96.8%, 95.3%, and 95.6% on train, validation, and test set, respectively, while the estimated accuracy for U-Net3 was 94.1%, 92.9%, and 93.9%. Both of the U-Nets achieved a median DSC of 0.95 for SAT segmentation. The U-Net1 and the U-Net3 achieved an optimal agreement with manual segmentation for the automatic segmentation. The so-developed neural networks have the potential to automatically segment thigh muscles and SAT in patients affected by MDs.

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“…It is now accepted that the menopause is associated with the onset of bone and muscle diseases, such as osteoporosis and sarcopenia [1][2][3].…”

Section: Postmenopausal Osteoporosis and Sarcopeniamentioning

confidence: 99%

“…Primary osteoporosis is the most common form and includes postmenopausal osteoporosis and senile osteoporosis [1]. Decreased estrogen levels leads to increased apoptosis of osteoblasts, promoting at the same time osteoclast maturation and activity [4].…”

Section: Postmenopausal Osteoporosis and Sarcopeniamentioning

confidence: 99%

Irisin and Its Role in Postmenopausal Osteoporosis and Sarcopenia

Falsetti,

Palmini,

Donati

et al. 2024

Biomedicines

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Menopause, an extremely delicate phase in a woman’s life, is characterized by a drop in estrogen levels. This decrease has been associated with the onset of several diseases, including postmenopausal osteoporosis and sarcopenia, which often coexist in the same person, leading to an increased risk of fractures, morbidity, and mortality. To date, there are no approved pharmacological treatments for sarcopenia, while not all of those approved for postmenopausal osteoporosis are beneficial to muscles. In recent years, research has focused on the field of myokines, cytokines, or peptides secreted by skeletal muscle fibers following exercise. Among these, irisin has attracted great interest as it possesses myogenic properties but at the same time exerts anabolic effects on bone and could therefore represent the link between muscle and bone. Therefore, irisin could represent a new therapeutic strategy for the treatment of osteoporosis and also serve as a new biomarker of sarcopenia, thus facilitating diagnosis and pharmacological intervention. The purpose of this review is to provide an updated summary of what we know about the role of irisin in postmenopausal osteoporosis and sarcopenia.

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Functional Imaging in Musculoskeletal Disorders in Menopause

Cited by 5 publications

References 92 publications

Radiopharmaceuticals for Skeletal Muscle PET Imaging

Radiopharmaceuticals for Skeletal Muscle PET Imaging

Convolutional Neural Network-Based Automated Segmentation of Skeletal Muscle and Subcutaneous Adipose Tissue on Thigh MRI in Muscular Dystrophy Patients

Irisin and Its Role in Postmenopausal Osteoporosis and Sarcopenia

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