Whole body magnetic resonance imaging in healthy children and adolescents. Bone marrow appearances of the axial skeleton

Brandis, Elisabeth von; Zadig, Pia; Avenarius, Derk F M; Flatø, Berit; Knudsen, Per Kristian; Lilleby, Vibke; Nguyen, Bac; Rosendahl, Karen; Müller, Lil-Sofie Ording

doi:10.1016/j.ejrad.2022.110425

Cited by 11 publications

(3 citation statements)

References 71 publications

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“…According to von Brandis et al, it is important not to mistake an unfused growth plate for a fracture line when interpreting sacral images [12]. Lumbarization is the complete or incomplete fusion of the upper sacral vertebrae with the L5 [13].…”

Section: Discussionmentioning

confidence: 99%

Age-specific normative values of sacral development and fusion in children and adolescents: a cross-sectional study utilizing multi-planar reconstruction computed tomography imaging

Ishizuka,

Nozawa,

Watanabe

et al. 2024

Preprint

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Background This study aimed to determine the index of the sacral vertebrae fusion period in children and adolescents to diagnose the lesion around the sacral spine accurately. Methods Patients aged 0–40 years who underwent computed tomography (CT), including the sacrum, for abdominal disorders, trauma, etc., between 2019 and 2022 were retrospectively examined. There were 402 eligible sacra (385 patients: 206 women and 179 men). We evaluated bony fusion at six parts of the sacral vertebrae (anterior or posterior of each intervertebral and both side lateral masses). The predicted probability of bony fusion obtained from the logistic regression model is depicted graphically by sex. Results The association between bony fusion in each vertebral segment and age was evaluated using a logistic regression model with a Huber–White robust sandwich estimator, including the patient as a clustering variable. Bony fusion of the sacral bodies of S1/S2 was slowest, with 80% of patients achieving bony fusion at 28.7 and 24.6 years of age for men and women, respectively. Compared to men, women exhibited earlier fusion of the intervertebral segments of the sacral vertebrae; however, no significant difference between the sexes in terms of eventual bony fusion at the lateral mass was observed, while the initiation of bony fusion occurred earlier in women. Conclusion The predicted probability of bony fusion could aid pediatricians, orthopedists, radiologists, and other physicians in understanding the normal development of the sacral spine and accurately diagnosing the lesion around the sacral spine.

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Section: Discussionmentioning

confidence: 99%

Age-specific normative values of sacral development and fusion in children and adolescents: a cross-sectional study utilizing multi-planar reconstruction computed tomography imaging

Ishizuka,

Nozawa,

Watanabe

et al. 2024

Preprint

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“…This latter group of patients was used to sample and to extrapolate texture data of the bone marrow growth-related changes. In the absence of histological evidence, for ethical reasons, areas of hyperintensity in the context of a healthy bone were interpreted as expression of physiological changes in bone marrow appearance related to growth in the presence of certain characteristics such as congruence with age, topographical distribution, pattern and symmetry, taking into account the notions known from older studies to the most recent bone marrow identification methods [ 22 , 31 , 32 ].…”

Section: Methodsmentioning

confidence: 99%

Machine Learning Algorithm: Texture Analysis in CNO and Application in Distinguishing CNO and Bone Marrow Growth-Related Changes on Whole-Body MRI

Forestieri,

Napolitano,

Tomà

et al. 2023

Diagnostics

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Objective: The purpose of this study is to analyze the texture characteristics of chronic non-bacterial osteomyelitis (CNO) bone lesions, identified as areas of altered signal intensity on short tau inversion recovery (STIR) sequences, and to distinguish them from bone marrow growth-related changes through Machine Learning (ML) and Deep Learning (DL) analysis. Materials and methods: We included a group of 66 patients with confirmed diagnosis of CNO and a group of 28 patients with suspected extra-skeletal systemic disease. All examinations were performed on a 1.5 T MRI scanner. Using the opensource 3D Slicer software version 4.10.2, the ROIs on CNO lesions and on the red bone marrow were sampled. Texture analysis (TA) was carried out using Pyradiomics. We applied an optimization search grid algorithm on nine classic ML classifiers and a Deep Learning (DL) Neural Network (NN). The model’s performance was evaluated using Accuracy (ACC), AUC-ROC curves, F1-score, Positive Predictive Value (PPV), Mean Absolute Error (MAE) and Root-Mean-Square Error (RMSE). Furthermore, we used Shapley additive explanations to gain insight into the behavior of the prediction model. Results: Most predictive characteristics were selected by Boruta algorithm for each combination of ROI sequences for the characterization and classification of the two types of signal hyperintensity. The overall best classification result was obtained by the NN with ACC = 0.91, AUC = 0.93 with 95% CI 0.91–0.94, F1-score = 0.94 and PPV = 93.8%. Between classic ML methods, ensemble learners showed high model performance; specifically, the best-performing classifier was the Stack (ST) with ACC = 0.85, AUC = 0.81 with 95% CI 0.8–0.84, F1-score = 0.9, PPV = 90%. Conclusions: Our results show the potential of ML methods in discerning edema-like lesions, in particular by distinguishing CNO lesions from hematopoietic bone marrow changes in a pediatric population. The Neural Network showed the overall best results, while a Stacking classifier, based on Gradient Boosting and Random Forest as principal estimators and Logistic Regressor as final estimator, achieved the best results between the other ML methods.

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“…Finally, although BME was one of the most important diagnostic and differential features, recent work by Zadig et al [61] showed that focal areas of high signal intensity on WB-MRI fat suppressed images that cause concern, as in our study group, are seen in more than half of healthy, asymptomatic children and adolescents. An awareness of this is important when interpreting WB-MRI in this age group as some findings may resemble clinically silent lesions in children with suspected multifocal skeletal disease [61,62].…”

Section: Wb-mri In Namentioning

confidence: 99%

Whole-Body MRI at Initial Presentation of Chronic Recurrent Multifocal Osteomyelitis, Juvenile Idiopathic Arthritis, Their Overlapping Syndrome, and Non-Specific Arthropathy

Lanckoroński,

Gietka,

Mańczak

et al. 2024

JCM

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(1) Background: Whole-body magnetic resonance imaging (WB-MRI) is central to defining total inflammatory burden in juveniles with arthritis. Our aim was to determine and compare the initial distribution of lesions in the WB-MRI in patients with chronic recurrent multifocal osteomyelitis (CRMO), juvenile idiopathic arthritis (JIA), their overlapping syndrome (OS), and with Non-specific Arthropathy (NA). (2) Methods: This retrospective single center study was performed on an Avanto 1.5-T MRI scanner with a dedicated multichannel surface coil system. A total of 173 pediatric patients were included with the following final diagnoses: CRMO (15.0%), JIA (29.5%), OS (4.6%), and NA (50.9%). (3) Results: Bone marrow edema (BME) was the most common abnormality, being seen in 100% patients with CRMO, 88% with OS, 55% with JIA, and 11% with NA. The bones of the lower extremities were the most affected in all compared entities. Effusion was seen in 62.5% children with OS, and in 52.9% with JIA, and in CRMO and NA, the exudate was sporadic. Enthesitis was found in 7.8% of patients with JIA and 3.8% with CRMO, and myositis was seen in 12.5% of patients with OS and in 3.9% with JIA. (4) Conclusions: The most frequent indication for WB-MRI in our center was JIA. The most common pathology in all rheumatic entities was BME, followed by effusion mainly seen in in OS and JIA. Enthesitis and myositis were less common; no case was observed in NA.

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Whole body magnetic resonance imaging in healthy children and adolescents. Bone marrow appearances of the axial skeleton

Cited by 11 publications

References 71 publications

Age-specific normative values of sacral development and fusion in children and adolescents: a cross-sectional study utilizing multi-planar reconstruction computed tomography imaging

Age-specific normative values of sacral development and fusion in children and adolescents: a cross-sectional study utilizing multi-planar reconstruction computed tomography imaging

Machine Learning Algorithm: Texture Analysis in CNO and Application in Distinguishing CNO and Bone Marrow Growth-Related Changes on Whole-Body MRI

Whole-Body MRI at Initial Presentation of Chronic Recurrent Multifocal Osteomyelitis, Juvenile Idiopathic Arthritis, Their Overlapping Syndrome, and Non-Specific Arthropathy

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