scholarly journals Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care

Author(s):  
Lorenzo Grassi ◽  
Sami P. Väänänen ◽  
Hanna Isaksson

Abstract Purpose of Review Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation. Recent Findings Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. Summary All the reviewed application areas made considerable steps forward in the past 5–6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i12-i42
Author(s):  
S Brook ◽  
G Todorov ◽  
A N Comninos

Abstract Introduction Falls are a major risk factor for fragility fractures and patients should be appropriately assessed to reduce future fragility fracture risk. National guidelines provide recommendations on assessing fracture risk using calculators to guide therapy initiation. FRAX and QFracture are the two main calculators used, however they differ considerably in their inputs. The aim of this study was to compare the risk estimation and performance between these two frequently used calculators to help determine their appropriate utility. Methods Data from patients aged ≥70 years admitted with a fall to the Acute Medical Units at Charing Cross Hospital between 1st Dec 2018–31st March 2019 were retrospectively collected, covering all inputs required for the two risk calculators. The 10-year major osteoporotic and hip fracture risks were calculated using FRAX and QFracture and compared. The one-year major osteoporotic and hip fracture risks from QFracture were assessed against actual one-year fracture rates. Results Conclusions Risk calculators are effective tools to aid the decision of bone therapy initiation. Here we demonstrate that there is a strong correlation between the two commonly used calculators. However, in terms of absolute risk values there is a mean 8.9% difference with QFracture providing higher risks in this “fallers” group. As absolute treatment thresholds are frequently used to guide bone therapy initiation, opposing recommendations may result. Therefore, there is a need to further explore calculator performance and determine which would more accurately serve different patient groups.


2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Delia Ciardo ◽  
Francesco Conversano ◽  
Paola Pisani ◽  
Sergio Casciaro

Abstract Introduction Fragility bone fractures impact patient’s quality of life and worldwide healthcare systems: accurate technologies and device are required in order to early diagnose and monitor the effect of osteoporosis on a mass-population basis. Several studied have analysed the pros and cons of the numerous technologies available nowadays for the diagnosis and monitoring of bone health, highlighting the need of further tools able to better define and estimate bone strength and to predict the risk of fracture [1]. Objectives The aim is to assess the state of the art about Radiofrequency Echographic Multi-Spectrometry (REMS). Methods A review of the available literature was performed, considering full papers, reviews and abstracts on REMS published before January 31th 2020. Results REMS has been recently presented by an ESCEO consensus paper as a valuable technology for osteoporosis diagnosis and fracture risk estimation [1]. It is based on the automatic processing of the raw unfiltered signals obtained with an ultrasound scan, thus overcoming the main drawback of dual-energy X-ray absorptiometry (DXA) and computed tomography (CT)-based technologies [2]. Moreover, REMS scans are performed at axial skeleton reference sites, i.e. lumbar spine [3] and femoral neck [4], differently from quantitative ultrasound (QUS) technology, which is usually applied to peripheral sites [3]. Clinical performance has been confirmed by a multicentre clinical trial enrolling over 1900 Caucasian women, demonstrating a high correlation between bone mineral density (BMD) estimated by REMS and DXA. In addition, high performance in terms of precision and intra- and inter-operator repeatability of REMS have been assessed [6]. Prospective studies have demonstrated the predictive ability of incident fragility fractures [7] and the high concordance with DXA in terms of measured BMD in patients with rheumatoid arthritis and pre/post-menopause [8, 9]. Conclusions REMS is an innovative approach for the early diagnosis, short-term monitoring of osteoporosis and risk fracture prediction. The available data envisaged for further applications in paediatric patients, pregnant women and patients at risk of secondary osteoporosis (e.g., diabetic, nephropathic, oncological patients). The EchoS system, a device implementing the REMS technology, has recently received the approval from the U.S. Food and Drug Administration (FDA). References 1. Diez-Perez et al. Aging Clin Exp Res 2019;31(10):1375–89 2. Iwaszkiewicz & Leszczyński. Forum Reumatol 2019;5(2):81–8 3. Hans & Baim. J Clin Densitom 2017;20(3):322-3 4. Conversano et al. Ultrasound Med Biol 2015;41:281–300 5. Casciaro et al. Ultrasound Med Biol 2016;42:1337–56 6. Di Paola et al. Osteoporos Int 2018;30:391–402 7. Adami et al. Ann Rheum Dis, vol.78, supp.2, 2019, p.A928 8. Bojincă et al. Exp Ther Med 2019;18(3):1661-68 9. Kirilova et al. Clin Cases Miner Bone Metab 2019; 16(1):14-17


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Shijun Yang ◽  
Bin Wang ◽  
Xiong Han

AbstractAlthough antiepileptic drugs (AEDs) are the most effective treatment for epilepsy, 30–40% of patients with epilepsy would develop drug-refractory epilepsy. An accurate, preliminary prediction of the efficacy of AEDs has great clinical significance for patient treatment and prognosis. Some studies have developed statistical models and machine-learning algorithms (MLAs) to predict the efficacy of AEDs treatment and the progression of disease after treatment withdrawal, in order to provide assistance for making clinical decisions in the aim of precise, personalized treatment. The field of prediction models with statistical models and MLAs is attracting growing interest and is developing rapidly. What’s more, more and more studies focus on the external validation of the existing model. In this review, we will give a brief overview of recent developments in this discipline.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 294.2-294
Author(s):  
D. Ciardo ◽  
P. Pisani ◽  
F. A. Lombardi ◽  
R. Franchini ◽  
F. Conversano ◽  
...  

Background:The main consequence of osteoporosis is the occurrence of fractures due to bone fragility, with important sequelae in terms of disability and mortality. It has been already demonstrated that the information about bone mass density (BMD) alone is not sufficient to predict the risk of fragility fractures, since several fractures occur in patients with normal BMD [1].The Fragility Score is a parameter that allows to estimate skeletal fragility thanks to a trans-abdominal ultrasound scan performed with Radiofrequency Echographic Multi Spectrometry (REMS) technology. It is calculated by comparing the results of the spectral analysis of the patient’s raw ultrasound signals with reference models representative of fragile and non-fragile bones [2]. It is a dimensionless parameter, which can vary from 0 to 100, in proportion to the degree of fragility, independently from BMD.Objectives:This study aims to evaluate the effectiveness of Fragility Score, measured during a bone densitometry exam performed with REMS technology at lumbar spine, in identifying patients at risk of incident osteoporotic fractures at a follow-up period of 5 years.Methods:Caucasian women with age between 30 and 90 were scanned with spinal REMS and DXA. The incidence of osteoporotic fractures was assessed during a follow-up period of 5 years. The ability of the Fragility Score to discriminate between patients with and without incident fragility fractures was subsequently evaluated and compared with the discriminatory ability of the T-score calculated with DXA and with REMS.Results:Overall, 533 women (median age: 60 years; interquartile range [IQR]: 54-66 years) completed the follow-up (median 42 months; IQR: 35-56 months), during which 73 patients had sustained an incident fracture.Both median REMS and DXA measured T-score values were significantly lower in fractured patients than for non-fractured ones, conversely, REMS Fragility Score was significantly higher (Table 1).Table 1.Analysis of T-score values calculated with REMS and DXA and Fragility Score calculated with REMS. Median values and interquartile ranges (IQR) are reported. The p-value is derived from the Mann-Whitney test.Patients without incident fragility fracturePatients with incident fragility fracturep-valueT-score DXA[median (IQR)]-1.9 (-2.7 to -1.0)-2.6 (-3.3 to -1.7)0.0001T-score REMS[median (IQR)]-2.0 (-2.8 to -1.1)-2.7 (-3.5 to -1.9)<0.0001Fragility Score[median (IQR)]29.9 (25.7 to 36.2)53.0 (34.2 to 62.5)<0.0001By evaluating the capability to discriminate patients with/without fragility fractures, the Fragility Score obtained a value of the ROC area under the curve (AUC) of 0.80, higher than the AUC of the REMS T-score (0.66) and of the T-score DXA (0.64), and the difference was statistically significant (Figure 1).Figure 1.ROC curve comparison of Fragility Score, REMS and DXA T-score values in the classification of patients with incident fragility fractures.Furthermore, the correlation between the Fragility Score and the T-score values was low, with Pearson correlation coefficient r=-0.19 between Fragility Score and DXA T-score and -0.18 between the Fragility Score and the REMS T-score.Conclusion:The Fragility Score was found to be an effective tool for the prediction of fracture risk in a population of Caucasian women, with performances superior to those of the T-score values. Therefore, this tool presents a high potential as an effective diagnostic tool for the early identification and subsequent early treatment of bone fragility.References:[1]Diez Perez A et al. Aging Clin Exp Res 2019; 31(10):1375-1389.[2]Pisani P et al. Measurement 2017; 101:243–249.Disclosure of Interests:None declared


2014 ◽  
Vol 33 (2-3) ◽  
pp. 641-655 ◽  
Author(s):  
Michael T. Schweizer ◽  
Charles G. Drake

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i12-i42
Author(s):  
C M Orton ◽  
N E Sinson ◽  
R Blythe ◽  
J Hogan ◽  
N A Vethanayagam ◽  
...  

Abstract Introduction NICE and the National Osteoporosis Guidance Group (NOGG) advise on evaluation of fracture risk and osteoporosis treatment1,2, with evidence suggesting that screening and treatment reduces the risk of fragility fractures 3,4,5. However, it is often overlooked in the management of older patients within secondary care. Audit data from Sheffield Frailty Unit (SFU) in 2018 showed that national guidance was not routinely followed. Fracture Risk Assessment Tool (FRAX®) scores were not calculated and bone health was poorly managed. Therefore, we undertook a quality improvement project aiming to optimise bone health in patients presenting to SFU. Method & Intervention In January 2019 we collaborated with Sheffield Metabolic Bone Centre (MBC) to develop a pathway aiming to improve bone health assessment and management in patients presenting to SFU with a fall or fragility fracture. This included a user-friendly flow chart with accompanying guidelines, alongside education for staff. Performance was re-evaluated in May 2019, following which a tick box prompt was added to post take ward round documentation. A re-audit was performed in March 2020. Results In March 2018 0% of patients presenting with a fall had a FRAX® score calculated and only 40% of those with a new fragility fracture were managed according to guidelines. In May 2019, this had improved to 18% and 100% respectively. In March 2020 86% of patients had a FRAX® score calculated appropriately and 100% of fragility fractures were managed according to guidelines. In both re-audits 100% of FRAX® scores were acted on appropriately. Conclusions There has been a significant increase in the number of patients who have their bone health appropriately assessed and managed after presenting to SFU. However, achieving optimum care is under constant review with the aim to deliver more treatment on SFU, thereby reducing the need for repeat visits to the MBC.


2018 ◽  
Vol 03 (03n04) ◽  
pp. 1840002 ◽  
Author(s):  
Dandan Lyu ◽  
Shaofan Li

The development of crystal plasticity theory based on dislocation patterns dynamics has been an outstanding problem in materials science and condensed matter of physics. Dislocation is the origin of crystal plasticity, and it is both the individual dislocation behavior as well as the aggregated dislocations behaviors that govern the plastic flow. The interactions among dislocations are complex statistical and stochastic events, in which the spontaneous emergence of organized dislocation patterns formations is the most critical and intriguing events. Dislocation patterns consist of quasi-periodic dislocation-rich and dislocation poor regions, e.g. cells, veins, labyrinths, ladders structures, etc. during cyclic loadings. Dislocation patterns have prominent and decisive effects on work hardening and plastic strain localization, and thus these dislocation micro-structures are responsible to material properties at macroscale. This paper reviews the recent developments of experimental observation, physical modeling, and computer modeling on dislocation microstructure. In particular, we focus on examining the mechanism towards plastic deformation. The progress and limitations of different experiments and modeling approaches are discussed and compared. Finally, we share our perspectives on current issues and future challenges in both experimental, analytical modeling, and computational aspects of dislocation pattern dynamics.


2016 ◽  
Vol 67 (1) ◽  
pp. 28-40 ◽  
Author(s):  
Thomas M. Link

The radiologist has a number of roles not only in diagnosing but also in treating osteoporosis. Radiologists diagnose fragility fractures with all imaging modalities, which includes magnetic resonance imaging (MRI) demonstrating radiologically occult insufficiency fractures, but also lateral chest radiographs showing asymptomatic vertebral fractures. In particular MRI fragility fractures may have a nonspecific appearance and the radiologists needs to be familiar with the typical locations and findings, to differentiate these fractures from neoplastic lesions. It should be noted that radiologists do not simply need to diagnose fractures related to osteoporosis but also to diagnose those fractures which are complications of osteoporosis related pharmacotherapy. In addition to using standard radiological techniques radiologists also use dual-energy x-ray absorptiometry (DXA) and quantitative computed tomography (QCT) to quantitatively assess bone mineral density for diagnosing osteoporosis or osteopenia as well as to monitor therapy. DXA measurements of the femoral neck are also used to calculate osteoporotic fracture risk based on the Fracture Risk Assessment Tool (FRAX) score, which is universally available. Some of the new technologies such as high-resolution peripheral computed tomography (HR-pQCT) and MR spectroscopy allow assessment of bone architecture and bone marrow composition to characterize fracture risk. Finally radiologists are also involved in the therapy of osteoporotic fractures by using vertebroplasty, kyphoplasty, and sacroplasty. This review article will focus on standard techniques and new concepts in diagnosing and managing osteoporosis.


2021 ◽  
Vol 22 (19) ◽  
pp. 10276
Author(s):  
Julia Hofmann ◽  
Verena Hackl ◽  
Hannah Esser ◽  
Andras T. Meszaros ◽  
Margot Fodor ◽  
...  

The liver, in combination with a functional biliary system, is responsible for maintaining a great number of vital body functions. However, acute and chronic liver diseases may lead to irreversible liver damage and, ultimately, liver failure. At the moment, the best curative option for patients suffering from end-stage liver disease is liver transplantation. However, the number of donor livers required by far surpasses the supply, leading to a significant organ shortage. Cellular therapies play an increasing role in the restoration of organ function and can be integrated into organ transplantation protocols. Different types and sources of stem cells are considered for this purpose, but highly specific immune cells are also the focus of attention when developing individualized therapies. In-depth knowledge of the underlying mechanisms governing cell differentiation and engraftment is crucial for clinical implementation. Additionally, novel technologies such as ex vivo machine perfusion and recent developments in tissue engineering may hold promising potential for the implementation of cell-based therapies to restore proper organ function.


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