Pediatric Bone Marrow: Normal and Abnormal MRI Appearance

[MR Imaging Features of Pediatric Bone Marrow]

MRI plays a crucial role in bone marrow (BM) assessment, and has very high sensitivity in diagnosing marrow disorders. However, for radiologists who may not frequently encounter pediatric imaging, distinguishing pathologic BM lesion from normal BM can be challenging. Conditions involving the BM in pediatric patients, such as leukemia and metastatic neuroblastoma, often manifest with diverse musculoskeletal symptoms and may be diagnosed using musculoskeletal MRI examinations. Accurate interpretation of pediatric MRI requires not only an understanding of the normal composition of BM but also an awareness of agerelated developmental changes in the marrow and familiarity with conditions that commonly involve pediatric BM. We aim to describe the composition of normal BM and outline the normal and abnormal MRI findings in pediatric BM. Additionally, we aim to present clinical cases of malignant BM disorders including leukemia, neuroblastoma metastasis, and other malignant BM disorders.

Pictorial review: challenges in distinguishing bilateral metaphyseal marrow abnormalities on magnetic resonance imaging

The paediatric metaphysis is afflicted by a wide range of pathological processes as it is the most metabolically active and well-vascularised part of the developing skeleton. This review focuses on metaphyseal marrow signal change detected with magnetic resonance imaging, which is most often occult on radiographs. When bilateral, these imaging appearances frequently present a diagnostic quandary. This review assists the radiologist to confidently dismiss physiological signal change and confidently work through the differential diagnosis. This is achieved by illustrating a practical method of classifying signal change into four categories: physiological red marrow, red marrow reconversion, marrow infiltration, and oedema-like marrow signal intensity. In doing so, various pathological entities are reviewed along with imaging pearls and next-step investigations.

Advantages of digital technology in the assessment of bone marrow involvement in Gaucher's disease

Gaucher disease (GD) is a genetic lysosomal disorder characterized by high bone marrow (BM) involvement and skeletal complications. The pathophysiology of these complications is not fully elucidated. Magnetic resonance imaging (MRI) is the gold standard to evaluate BM. This study aimed to apply machine-learning techniques in a cohort of Spanish GD patients by a structured bone marrow MRI reporting model at diagnosis and follow-up to predict the evolution of the bone disease. In total, 441 digitalized MRI studies from 131 patients (M: 69, F:62) were reevaluated by a blinded expert radiologist who applied a structured report template. The studies were classified into categories carried out at different stages as follows: A: baseline; B: between 1 and 4 y of follow-up; C: between 5 and 9 y; and D: after 10 years of follow-up. Demographics, genetics, biomarkers, clinical data, and cumulative years of therapy were included in the model. At the baseline study, the mean age was 37.3 years (1-80), and the median Spanish MRI score (S-MRI) was 8.40 (male patients: 9.10 vs. female patients: 7.71) (p < 0.001). BM clearance was faster and deeper in women during follow-up. Genotypes that do not include the c.1226A>G variant have a higher degree of infiltration and complications (p = 0.017). A random forest machine-learning model identified that BM infiltration degree, age at the start of therapy, and femur infiltration were the most important factors to predict the risk and severity of the bone disease. In conclusion, a structured bone marrow MRI reporting in GD is useful to standardize the collected data and facilitate clinical management and academic collaboration. Artificial intelligence methods applied to these studies can help to predict bone disease complications.

Dual-Energy Computed Tomography-Based Quantitative Bone Marrow Imaging in Non-Hematooncological Subjects: Associations with Age, Gender and Other Variables

Background: Our aim is to assess the utility and associations of quantitative bone marrow attenuation (BMA) values measured on clinical dual-energy computed tomography (DECT) exams in non-hematooncologic subjects with skeletal regions, patient age, gender, and other clinical variables. Methods: Our local ethics committee approved this retrospective image data analysis. Between July 2019 and July 2021, 332 eligible patients (mean age, 64 ± 18 years; female, 135) were identified. Inclusion criteria were the availability of a standardized abdominopelvic DECT data set acquired on the same scanner with identical protocol. Eleven regions-of-interest were placed in the T11-L5 vertebral bodies, dorsal iliac crests, and femur necks. Patient age, gender, weight, clinical, habitual variables, inflammation markers, and anemia were documented in all cases. Results: Multi-regression analyses (all, p < 0.05) identified age as the strongest predictor of lumbar BMA (standardized coefficient: β = −0.74), followed by CRP (β = 0.11), LDH (β = 0.11), and gender (β = −0.10). In the lower thoracic spine, age was the strongest predictor (β = −0.58) of BMA, followed by gender (β = −0.09) and LDH (β = 0.12). In femoral bones, age was negatively predictive of BMA (β = −0.12), whereas LDH and anemia were positively predictive (β = 0.16 both). Heart insufficiency significantly decreased (β = 0.12, p = 0.034) a BMA value gradient from higher to lower HU values along the vertebrae T11 and L5, whereas age significantly increased this gradient (β = −0.2, p ≤ 0.001). Conclusions: DECT-based BMA measurements can be obtained from clinical CT exams. BMA values are negatively associated with patient age and influenced by gender, anemia, and inflammatory markers.