Generalizing Diffusion Tensor Imaging of the Physis and Metaphysis.

BACKGROUND: Current methods to predict height potential are inaccurate. Predicting height by using MRI of the physeal cartilage has shown promise but the applicability of this technique in different imaging setups has not been well-evaluated. PURPOSE: To assess variability in diffusion tensor imaging of the physis and metaphysis (DTI-P/M) of the distal femur between different scanners, imaging parameters, tractography software, and resolution. STUDY TYPE: Prospective. POPULATION/SUBJECTS: Eleven healthy subjects (five males and six females ages 10-16.94). FIELD STRENGTH/SEQUENCE: 3 T; DTI single shot echo planar sequences. ASSESSMENT: Physeal DTI tract measurements of the distal femur were compared between different scanners, imaging parameters, tractography settings, interpolation correction, and tractography software. STATISTICAL TESTS: Bland-Altman, Spearman correlation, linear regression, and Shapiro-Wilk tests. Threshold for statistical significance was set at P = 0.05. RESULTS: DTI tract values consistently showed low variability with different imaging and analysis settings. Vendor to vendor comparison exhibited strong correlation (ρ = 0.93) and small but significant bias (bias -5.76, limits of agreement [LOA] -24.31 to 12.78). Strong correlation and no significant difference were seen between technical replicates of the General Electric MRI scanner (ρ = 1, bias 0.17 [LOA -1.5 to 1.2], P = 0.42) and the Siemens MRI scanner (ρ = 0.89, bias = 0.56, P = 0.71). Different voxel sizes (1 × 1 × 2 mm3 vs. 2 × 2 × 3 mm3) did not significantly affect DTI values (bias = 1.4 [LOA -5.7 to 8.4], P = 0.35) but maintained a strong correlation (ρ = 0.82). Gap size (0 mm vs. 0.6 mm) significantly affects tract volume (bias = 1.8 [LOA -5.4 to 1.8]) but maintains a strong correlation (ρ = 0.93). Comparison of tractography algorithms generated significant differences in tract number, length, and volume while maintaining correlation (ρ = 0.86, 0.99, 0.93, respectively). Comparison of interobserver variability between different tractography software also revealed significant differences while maintaining high correlation (ρ = 0.85-0.98). DATA CONCLUSION: DTI of the pediatric physis cartilage shows high reproducibility between different imaging and analytic parameters. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Can diffusion tensor imaging unlock the secrets of the growth plate?

"How tall will I be?" Every paediatrician has been asked this during their career. The growth plate is the main site of longitudinal growth of the long bones. The chondrocytes in the growth plate have a columnar pattern detectable by diffusion tensor imaging (DTI). DTI shows the diffusion of water in a tissue and whether it is iso- or anisotropic. By detecting direction and magnitude of diffusion, DTI gives information about the microstructure of the tissue. DTI metrics include tract volume, length, and number, fractional anisotropy (FA), and mean diffusivity. DTI metrics, particularly tract volume, provide quantitative data regarding skeletal growth and, in conjunction with the fractional anisotropy, be used to determine whether a growth plate is normal. Tractography is a visual display of the diffusion, depicting its direction and amplitude. Tractography gives a more qualitative visualization of cellular orientation in a tissue and reflects the activity in the growth plate. These two components of DTI can be used to assess the growth plate without ionizing radiation or pain. Further refinements in DTI will improve prediction of post-imaging growth and growth plate closure, and assessment of the positive and negative effect of treatments like cis-retinoic acid and growth hormone administration.

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm2) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm3 voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics.

Stressed or fractured: MRI differentiating indicators of physeal injury.

OBJECTIVE: To identify MRI findings that can indicate chronic physeal stress injury and differentiate it from acute Salter-Harris (SH) fracture of the pediatric knee or wrist. METHODS: IRB-approved retrospective study of consecutively selected knee and wrist MRIs from 32 athletes with chronic physeal stress injury and 30 children with acute SH fracture. MRI characteristics (physeal patency, physeal thickening, physeal signal intensity (SI), continuity of the zone of provisional calcification (ZPC), integrity of the periosteum and/or perichondrium, pattern of periphyseal and soft tissue edema signal, and joint effusion) were compared. RESULTS: Forty-eight chronic physeal stress injuries (mean age 13.1 years [8.2-17.5 years]) and 35 SH fractures (mean age 13.3 years [5.1-16.0 years]) were included. Any physeal thickening was more common with chronic stress injury (98% vs 77%, p = 0.003). Abnormal physeal SI was more common with SH fractures (91% vs 67%, p = 0.008). ZPC discontinuity strongly suggested chronic stress injury (79% vs 49%, p < 0.004). Periosteal and/or perichondrial elevation or rupture and soft tissue edema characterized most of the acute SH fractures (p < 0.001) and were seen only in 1 chronic stress injury (< 2%). While periphyseal edema was not significantly different in the two groups (p = 0.890), a joint effusion was associated with acute SH fracture (p < 0.001). CONCLUSION: Chronic physeal stress injury of the pediatric knee and wrist shows higher incidence of ZPC discontinuity and focal physeal thickening compared to SH fracture, reflecting disruption in normal endochondral ossification. However, these findings can overlap in the 2 groups. Periosteal and/or perichondrial injury, soft tissue edema signal, and joint effusion strongly suggest SH fracture and are rarely present with chronic stress injury.

Lower Extremity Growth according to AI Automated Femorotibial Length Measurement on Slot-Scanning Radiographs in Pediatric Patients.

Background Commonly used pediatric lower extremity growth standards are based on small, dated data sets. Artificial intelligence (AI) enables creation of updated growth standards. Purpose To train an AI model using standing slot-scanning radiographs in a racially diverse data set of pediatric patients to measure lower extremity length and to compare expected growth curves derived using AI measurements to those of the conventional Anderson-Green method. Materials and Methods This retrospective study included pediatric patients aged 0-21 years who underwent at least two slot-scanning radiographs in routine clinical care between August 2015 and February 2022. A Mask Region-based Convolutional Neural Network was trained to segment the femur and tibia on radiographs and measure total leg, femoral, and tibial length; accuracy was assessed with mean absolute error. AI measurements were used to create quantile polynomial regression femoral and tibial growth curves, which were compared with the growth curves of the Anderson-Green method for coverage based on the central 90% of the estimated growth distribution. Results In total, 1874 examinations in 523 patients (mean age, 12.7 years ± 2.8 [SD]; 349 female patients) were included; 40% of patients self-identified as White and not Hispanic or Latino, and the remaining 60% self-identified as belonging to a different racial or ethnic group. The AI measurement training, validation, and internal test sets included 114, 25, and 64 examinations, respectively. The mean absolute errors of AI measurements of the femur, tibia, and lower extremity in the test data set were 0.25, 0.27, and 0.33 cm, respectively. All 1874 examinations were used to generate growth curves. AI growth curves more accurately represented lower extremity growth in an external test set (n = 154 examinations) than the Anderson-Green method (90% coverage probability: 86.7% [95% CI: 82.9, 90.5] for AI model vs 73.4% [95% CI: 68.4, 78.3] for Anderson-Green method; χ2 test, P < .001). Conclusion Lower extremity growth curves derived from AI measurements on standing slot-scanning radiographs from a diverse pediatric data set enabled more accurate prediction of pediatric growth. © RSNA, 2024 Supplemental material is available for this article.

Retrospective Follow-up Assessment of Risk Variables Influencing the Outcome of Autologous Tooth Transplantation.

INTRODUCTION: This retrospective study aimed to identify which patient-, donor tooth-, recipient site-, and surgical procedure-related variables may influence the outcome of tooth autotransplantation. METHODS: The sample included 128 autotransplants performed in 122 patients. Single-visit clinical/imaging examinations were used to define the outcome as successful, survival, or failure. The association of potential indicators with the survival or failure categories was analyzed individually and adjusted for confounders through multivariate logistic regression models. RESULTS: After a follow-up period of 1 to 30.11 years, success was achieved in 71.8% of autotransplants, whereas the survival and failure groups had rates of 14.1% each, and the grouped success/survival rate reached 85.9%. An extraoral time >15 minutes and difficult handling/placement were strong/independent risk covariates for survival and failure categories (odds ratio >1, P < .05). Additionally, unerupted/partially erupted status of the donor tooth was a significant indicator for survival, whereas deficient bone level at the recipient site, surgical extraction, poor initial stability, and lack of prophylactic antibiotics were independently linked to failure (odds ratio > 1, P < .05). The root morphology and socket status acted as modifiers of the effect of the recipient site location on the survival group (P > .05). CONCLUSION: Based on the results of this study, unerupted/partially erupted status of the donor tooth, surgical extraction, total extraoral time >15 minutes, deficient recipient's bone level, difficult handling/placement of the autotransplant, poor initial stability, and lack of prophylactic antibiotics during the surgical procedure must be considered with caution when performing autotransplantation because of their deleterious influence on the outcome.

Deep learning to detect left ventricular structural abnormalities in chest X-rays.

BACKGROUND AND AIMS: Early identification of cardiac structural abnormalities indicative of heart failure is crucial to improving patient outcomes. Chest X-rays (CXRs) are routinely conducted on a broad population of patients, presenting an opportunity to build scalable screening tools for structural abnormalities indicative of Stage B or worse heart failure with deep learning methods. In this study, a model was developed to identify severe left ventricular hypertrophy (SLVH) and dilated left ventricle (DLV) using CXRs. METHODS: A total of 71 589 unique CXRs from 24 689 different patients completed within 1 year of echocardiograms were identified. Labels for SLVH, DLV, and a composite label indicating the presence of either were extracted from echocardiograms. A deep learning model was developed and evaluated using area under the receiver operating characteristic curve (AUROC). Performance was additionally validated on 8003 CXRs from an external site and compared against visual assessment by 15 board-certified radiologists. RESULTS: The model yielded an AUROC of 0.79 (0.76-0.81) for SLVH, 0.80 (0.77-0.84) for DLV, and 0.80 (0.78-0.83) for the composite label, with similar performance on an external data set. The model outperformed all 15 individual radiologists for predicting the composite label and achieved a sensitivity of 71% vs. 66% against the consensus vote across all radiologists at a fixed specificity of 73%. CONCLUSIONS: Deep learning analysis of CXRs can accurately detect the presence of certain structural abnormalities and may be useful in early identification of patients with LV hypertrophy and dilation. As a resource to promote further innovation, 71 589 CXRs with adjoining echocardiographic labels have been made publicly available.

Deep Learning-Assisted Diffusion Tensor Imaging for Evaluation of the Physis and Metaphysis.

Diffusion tensor imaging of physis and metaphysis can be used as a biomarker to predict height change in the pediatric population. Current application of this technique requires manual segmentation of the physis which is time-consuming and introduces interobserver variability. UNET Transformers (UNETR) can be used for automatic segmentation to optimize workflow. Three hundred and eighty-five DTI scans from 191 subjects with mean age of 12.6 years ± 2.01 years were retrospectively used for training and validation. The mean Dice correlation coefficient was 0.81 for the UNETR model and 0.68 for the UNET. Manual extraction and segmentation took 15 min per volume, whereas both deep learning segmentation techniques took < 1 s per volume and were deterministic, always producing the same result for a given input. Intraclass correlation coefficient (ICC) for ROI-derived femur diffusion metrics was excellent for tract count (0.95), volume (0.95), and FA (0.97), and good for tract length (0.87). The results support the hypothesis that a hybrid UNETR model can be trained to replace the manual segmentation of physeal DTI images, therefore automating the process.

Acute patellar dislocation: how skeletal maturity affects patterns of injury.

OBJECTIVE: The main objective of this study was to understand the role of skeletal maturity in the different patterns of osteochondral and ligamentous injuries after an acute lateral patellar dislocation. MATERIALS AND METHODS: Two radiologists independently reviewed MRIs of 212 knees performed after an acute lateral patellar dislocation to evaluate the presence of high-grade patellar osteochondral injury, femoral osteochondral injury, and medial patellofemoral ligament injury. The association of skeletal maturity (indicated by a closed distal femoral physis), age, sex, and first-time versus recurrent dislocation with each of these various lesions was analyzed using Chi-square or T test, and multivariable logistic regression with estimation of odds ratios (OR). RESULTS: Skeletal maturity was significantly associated with high-grade patellar osteochondral injury [OR=2.72 (95% CI 1.00, 7.36); p=0.049] and femoral-side MPFL tear [OR=2.34 (95% CI 1.05, 5.25); p=0.039]. Skeletal immaturity was significantly associated with patellar-side MPFL tear [OR=0.35 (95% CI 0.14, 0.90); p=0.029]. CONCLUSION: Patterns of injury to the patella and medial patellofemoral ligament vary notably between the skeletally immature and mature, and these variations may be explained by the inherent weakness of the patellar secondary physis.

Applications of Diffusion-Weighted MRI to the Musculoskeletal System.

Diffusion-weighted imaging (DWI) is an established MRI technique that can investigate tissue microstructure at the scale of a few micrometers. Musculoskeletal tissues typically have a highly ordered structure to fulfill their functions and therefore represent an optimal application of DWI. Even more since disruption of tissue organization affects its biomechanical properties and may indicate irreversible damage. The application of DWI to the musculoskeletal system faces application-specific challenges on data acquisition including susceptibility effects, the low T2 relaxation time of most musculoskeletal tissues (2-70 msec) and the need for sub-millimetric resolution. Thus, musculoskeletal applications have been an area of development of new DWI methods. In this review, we provide an overview of the technical aspects of DWI acquisition including diffusion-weighting, MRI pulse sequences and different diffusion regimes to study tissue microstructure. For each tissue type (growth plate, articular cartilage, muscle, bone marrow, intervertebral discs, ligaments, tendons, menisci, and synovium), the rationale for the use of DWI and clinical studies in support of its use as a biomarker are presented. The review describes studies showing that DTI of the growth plate has predictive value for child growth and that DTI of articular cartilage has potential to predict the radiographic progression of joint damage in early stages of osteoarthritis. DTI has been used extensively in skeletal muscle where it has shown potential to detect microstructural and functional changes in a wide range of muscle pathologies. DWI of bone marrow showed to be a valuable tool for the diagnosis of benign and malignant acute vertebral fractures and bone metastases. DTI and diffusion kurtosis have been investigated as markers of early intervertebral disc degeneration and lower back pain. Finally, promising new applications of DTI to anterior cruciate ligament grafts and synovium are presented. The review ends with an overview of the use of DWI in clinical routine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.

UTE T2* cartilage mapping in the hip: a pilot study assessing cartilage in patients with femoroacetabular impingement.

BACKGROUND: UTE T2* cartilage mapping use in patients undergoing femoroacetabular impingement (FAI) has been lacking but may allow the detection of early cartilage damage. PURPOSE: To assess the reproducibility of UTE T2* cartilage mapping and determine the difference in UTE T2* values between FAI and asymptomatic patients and to evaluate the correlation between UTE T2* values and patient-reported symptoms. MATERIAL AND METHODS: Prospective evaluation of both hips (7 FAI and 7 asymptomatic patients). Bilateral hip 3-T MRI scans with UTE T2* cartilage maps were acquired. A second MRI scan was acquired 1-9 months later. Cartilage was segmented into anterosuperior, superior, and posterosuperior regions. Assessment was made of UTE T2* reproducibility (ICC). Mean UTE T2* values in patients were compared (t-tests) and correlation was made with patient-reported outcomes (Spearman's). RESULTS: ICCs of mean UTE T2* were as follows: acetabular, 0.82 (95% CI=0.50-0.95); femoral, 0.76 (95% CI=0.35-0.92). Significant strong correlation was found between mean acetabular UTE T2* values and iHOT12 (ρ = -0.63) and moderate correlation with mHHS (ρ = -0.57). There was no difference in mean UTE T2* values between affected vs. non-affected FAI hips. FAI-affected hips had significantly higher values in acetabulum vs. asymptomatic patients (13.47 vs. 12.55 ms). There was no difference in mean femoral cartilage values between the FAI-affected hips vs. asymptomatic patients. The posterosuperior femoral region had a higher mean value in non-affected FAI hips vs. asymptomatic patients (12.60 vs. 11.53 ms). CONCLUSION: UTE T2* cartilage mapping had excellent reproducibility. Affected FAI hips had higher mean acetabular UTE T2* values than asymptomatic patients. Severity of patient-reported symptoms correlates with UTE T2* acetabular cartilage values.

Borderline Phyllodes Tumor in a Child.

Phyllodes tumor (PT) is considered a rare fibroepithelial tumor. Very few series have been reported in children and adolescents. Based on histopathological features, it can be classified as benign, borderline, or malignant, with the latter having a more aggressive clinical behavior. We report the case of a 10-year-old female who began with an asymptomatic mobile right breast mass. An initial fine needle biopsy (FNB) concluded fibroadenoma (FA). Months later, the mass kept growing, with the appearance of pain and nipple discharge. Benign PT was demonstrated in a new biopsy. A total mastectomy was performed. The post-surgical histopathological examination was compatible with a borderline PT. The patient is now symptom-free and with no signs of relapse. Not all breast masses in the pediatric or adolescent age bracket are FA. Attention is warranted when the clinical behavior does not follow the usual outline. PT has to be considered as a possible diagnosis and treated accordingly.

Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs.

BACKGROUND: Pediatric fractures are challenging to identify given the different response of the pediatric skeleton to injury compared to adults, and most artificial intelligence (AI) fracture detection work has focused on adults. OBJECTIVE: Develop and transparently share an AI model capable of detecting a range of pediatric upper extremity fractures. MATERIALS AND METHODS: In total, 58,846 upper extremity radiographs (finger/hand, wrist/forearm, elbow, humerus, shoulder/clavicle) from 14,873 pediatric and young adult patients were divided into train (n = 12,232 patients), tune (n = 1,307), internal test (n = 819), and external test (n = 515) splits. Fracture was determined by manual inspection of all test radiographs and the subset of train/tune radiographs whose reports were classified fracture-positive by a rule-based natural language processing (NLP) algorithm. We trained an object detection model (Faster Region-based Convolutional Neural Network [R-CNN]; "strongly-supervised") and an image classification model (EfficientNetV2-Small; "weakly-supervised") to detect fractures using train/tune data and evaluate on test data. AI fracture detection accuracy was compared with accuracy of on-call residents on cases they preliminarily interpreted overnight. RESULTS: A strongly-supervised fracture detection AI model achieved overall test area under the receiver operating characteristic curve (AUC) of 0.96 (95% CI 0.95-0.97), accuracy 89.7% (95% CI 88.0-91.3%), sensitivity 90.8% (95% CI 88.5-93.1%), and specificity 88.7% (95% CI 86.4-91.0%), and outperformed a weakly-supervised model (AUC 0.93, 95% CI 0.92-0.94, P < 0.0001). AI accuracy on cases preliminary interpreted overnight was higher than resident accuracy (AI 89.4% vs. 85.1%, 95% CI 87.3-91.5% vs. 82.7-87.5%, P = 0.01). CONCLUSION: An object detection AI model identified pediatric upper extremity fractures with high accuracy.

Diffusion tensor imaging of the physis: the ABC's.

The physis, or growth plate, is the primary structure responsible for longitudinal growth of the long bones. Diffusion tensor imaging (DTI) is a technique that depicts the anisotropic motion of water molecules, or diffusion. When diffusion is limited by cellular membranes, information on tissue microstructure can be acquired. Tractography, the visual display of the direction and magnitude of water diffusion, provides qualitative visualization of complex cellular architecture as well as quantitative diffusion metrics that appear to indirectly reflect physeal activity. In the growing bones, DTI depicts the columns of cartilage and new bone in the physeal-metaphyseal complex. In this "How I do It", we will highlight the value of DTI as a clinical tool by presenting DTI tractography of the physeal-metaphyseal complex of children and adolescents during normal growth, illustrating variation in qualitative and quantitative tractography metrics with age and skeletal location. In addition, we will present tractography from patients with physeal dysfunction caused by growth hormone deficiency and physeal injury due to trauma, chemotherapy, and radiation therapy. Furthermore, we will delineate our process, or "DTI pipeline," from image acquisition to data interpretation.

Fibrous hamartoma of infancy: imaging findings.

BACKGROUND: Fibrous hamartoma of infancy is a benign tumor that typically arises within the first 2 years of life in the subcutaneous and lower dermal layers. Diagnosis can be challenging as it is a rare tumor, and the imaging appearance is not well known. OBJECTIVE: To describe the imaging features in 4 cases of fibrous hamartoma of infancy focusing on ultrasound (US) and magnetic resonance (MR) findings. MATERIALS AND METHODS: In this retrospective IRB-approved study, informed consent was waived. We searched patient charts for histopathology-confirmed fibrous hamartoma of infancy diagnosis between November 2013 and November 2022. We found four cases, three boys and one girl, and the mean age was 1.4 years (5 months-3 years). The lesions were located in the axilla, posterior elbow, posterior neck, and lower back. All four patients underwent ultrasound evaluation of the lesion, and two patients also underwent MRI evaluation. The imaging findings were reviewed by consensus by two pediatric radiologists. RESULTS: US imaging revealed subcutaneous lesions with variably defined hyperechoic regions and intervening hypoechoic bands resulting in a linear "serpentine" pattern or a "multiple semicircle" pattern. MR imaging evidenced heterogeneous soft tissue masses, localized in the subcutaneous fat, and showed hyperintense fat interspersed with hypointense septations on both T1- and T2-weighted images. CONCLUSION: Fibrous hamartoma of infancy has a suggestive appearance on US with heterogeneous, echogenic subcutaneous lesions with intervening hypoechoic portions, in parallel or circumferential arrangement that can be seen as a serpentine or semicircular pattern. On MRI, interspersed macroscopic fatty components show high signal intensity on T1- and T2-weighted images and reduced signal on fat-suppressed inversion recovery images, with irregular peripheral enhancement.

Soft-Tissue Anaplastic Lymphoma Kinase-Positive Anaplastic Large Cell Lymphoma in a Child Unmasked by COVID-19.

Anaplastic large cell lymphoma (ALCL) is children's most common mature T-cell neoplasm. The majority is positive for anaplastic lymphoma kinase (ALK). Initial presentation as a soft-tissue pelvic mass without nodal involvement is rare and can be easily misdiagnosed. We report a case of a 12-year-old male presenting with pain and movement restriction in the right extremity. Computed tomography (CT) scan revealed a solitary pelvic mass. Initial biopsy examination concluded rhabdomyosarcoma. After developing pediatric multisystemic inflammatory syndrome due to coronavirus disease 2019 (COVID-19), central and peripheral lymph node enlargement appeared. New cervical adenopathy and pelvic mass biopsies were performed. Immunohistochemistry concluded an ALK-positive ALCL with a small-cell pattern. The patient was treated with brentuximab-based chemotherapy and eventually improved. Differential diagnosis of pelvic masses in children and adolescents must include ALCL. An inflammatory trigger may promote the appearance of a typical nodal disease, previously absent. Attention is warranted during histopathological examination to avoid diagnostic errors.

MR Imaging of the Developing Pediatric Marrow: An Overview of Pearls and Pitfalls.

The dynamic and developing pediatric skeleton is a well-elucidated process that occurs in a stepwise faction. Normal development has been reliably tracked and described with Magnetic Resonance (MR) imaging. The recognition of the normal patterns of skeletal development is essential, as normal development may mimic pathology and vice versa. The authors review normal skeleton maturation and the corollary imaging findings while highlighting common marrow imaging pitfalls and pathology.

Subcutaneous fat necrosis of the newborn: a pictorial essay of an under-recognized entity.

Subcutaneous fat necrosis of the newborn is a self-limited disorder predominantly affecting full-term and post-term neonates during the first 6 weeks after birth. Subcutaneous fat necrosis can be focal or multifocal and affect one or both sides with a predilection for areas of pressure in certain anatomical areas. Subcutaneous fat necrosis of the newborn is associated with perinatal asphyxia and other neonatal and maternal risk factors. Subcutaneous fat necrosis of the newborn presents as a self-limited area of dermal edema followed by indurated subcutaneous plaques, or nontender and mobile nodules, sometimes with skin discoloration [1-3]. The diagnosis is based on the child's history and physical examination, but when in doubt, imaging is helpful. US is the imaging modality of choice to confirm the diagnosis of subcutaneous fat necrosis of the newborn because it provides the best resolution of superficial lesions, requires no sedation and lacks ionizing radiation. US can also help evaluate and characterize other pathologies affecting the superficial subcutaneous soft tissues at this age. Familiarity with subcutaneous fat necrosis of the newborn is important to make a prompt and precise diagnosis and avoid unnecessary imaging tests or invasive procedures.

Isolated Renal Relapse in a Post-Allogenic Transplant Adult Patient With Acute Lymphoblastic Leukemia.

Acute lymphoblastic leukemia (ALL) is an aggressive hematological neoplasm typically more common in children than adults. More prolonged remissions and a potential cure can be achieved if allogeneic hematopoietic stem cell transplantation (allo-HSCT) is performed. Outcomes after allo-HSCT vary significantly among patients, and multiple factors contribute to these outcomes. Isolated extramedullary relapse (iEMR) after allo-HSCT is rare. We present the case of a 43-year-old man who was diagnosed with Philadelphia chromosome-negative (Ph-neg), B-cell ALL and underwent haploidentical allo-HSCT because of high-risk features at diagnosis. One year later, he was admitted to the hospital with facial and peripheral edema, proteinuria, elevated serum creatinine levels, and hypertension. Renal biopsy was performed immediately. Renal infiltration of TdT+ leukemic cells was detected by immunohistochemistry. Bone marrow aspiration, lumbar puncture, and computed tomography (CT) scans were performed to identify other sites of possible relapse. No other sites were identified, and an extramedullary isolated renal relapse was diagnosed. Intensive re-induction with chemotherapy was not possible because of the coronavirus disease 2019 (COVID-19) infection. Six weeks later, a medullary relapse was noted. Medullary infiltration of B-cell ALL after allo-HSCT has a historically poor prognosis; however, iEMR appears to have a better overall prognosis. The optimal treatment for renal iEMR is still a matter of debate.

Relapsing Myopathy With Granulomatous Inflammation as Chronic Graft vs Host Disease Feature: A Case Report.

BACKGROUND: Graft-vs-host disease (GVHD) is a common complication of allogeneic hematopoietic stem cell transplant. Myopathy is a rare neuromuscular sign of chronic GVHD, with an incidence of less than 4% in all patients. The data are heterogeneous, and no standard criteria exists for diagnosis or treatment. CASE REPORT: We present the case of an 18-year-old man with acute lymphoblastic leukemia, who developed myopathy associated with GVHD 19 months after allogeneic hematopoietic stem cell transplant from an unrelated donor. The patient had a previous history of acute cutaneous and chronic hepatic GVHD. At the time of symptom onset, the immunosuppressive drugs were tapered. He developed with sudden symmetrical proximal muscle weakness that prevented him from walking. Diagnosis was confirmed using magnetic resonance imaging, electromyography, muscle enzymes, and muscle biopsy results. He initially responded to immunosuppressive therapy but relapsed after quick tapering of prednisone, requiring a prolonged course of steroids and an additional dose of immune globulin intravenous. At the moment of the publication, the patient has 9 months free from GVHD relapse. CONCLUSIONS: GVHD-associated myopathy is a rare complication of hematopoietic stem cell transplant and must be suspected in patients with sudden proximal muscle weakness and moderate pain. Diagnosis is challenging and must include magnetic resonance imaging, electromyography, muscle enzymes, and muscle biopsy results. Usually, all patients respond adequately to immunosuppression.