Imaging Assessment of Radiation Therapy-Related Normal Tissue Injury in Children: A PENTEC Visionary Statement.

The Pediatric Normal Tissue Effects in the Clinic (PENTEC) consortium has made significant contributions to understanding and mitigating the adverse effects of childhood cancer therapy. This review addresses the role of diagnostic imaging in detecting, screening, and comprehending radiation therapy-related late effects in children, drawing insights from individual organ-specific PENTEC reports. We further explore how the development of imaging biomarkers for key organ systems, alongside technical advancements and translational imaging approaches, may enhance the systematic application of imaging evaluations in childhood cancer survivors. Moreover, the review critically examines knowledge gaps and identifies technical and practical limitations of existing imaging modalities in the pediatric population. Addressing these challenges may expand access to, minimize the risk of, and optimize the real-world application of, new imaging techniques. The PENTEC team envisions this document as a roadmap for the future development of imaging strategies in childhood cancer survivors, with the overarching goal of improving long-term health outcomes and quality of life for this vulnerable population.

CT and MR Appearance of Teeth: Analysis of Anatomy and Embryology and Implications for Disease.

Abnormalities of dental development and anatomy may suggest the presence of congenital or acquired anomalies. The detection of abnormalities, therefore, is an important skill for radiologists to achieve. Knowledge of dental embryology and an understanding of the radiologic appearances of teeth at various stages of maturation are required for the appreciation of abnormal dental development. While many tooth abnormalities are well-depicted on dedicated dental radiographs, the first encounter with a dental anomaly may be by a radiologist on a computed tomographic (CT) or magnetic resonance (MR) exam performed for other reasons. This article depicts normal dental anatomy and development, describing the appearance of the neonatal dentition on CT and MRI, the modalities most often encountered by clinical radiologists. The radiology and dental literature are reviewed, and key concepts are illustrated with supplemental cases from our institution. The value of knowledge of dental development is investigated using the analysis of consecutive MR brain examinations. Finally, the anatomical principles are applied to the diagnosis of odontogenic infection on CT. Through analysis of the literature and case data, the contrast of dental pathology with normal anatomy and development facilitates the detection and characterization of both congenital and acquired dental disease.

Hepatic steatosis modeling and MRI signal simulations for comparison of single- and dual-R2* models and estimation of fat fraction at 1.5T and 3T.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI) has emerged as a noninvasive clinical tool for assessment of hepatic steatosis. Multi-spectral fat-water MRI models, incorporating single or dual transverse relaxation decay rate(s) (R2*) have been proposed for accurate fat fraction (FF) estimation. However, it is still unclear whether single- or dual-R2* model accurately mimics in vivo signal decay for precise FF estimation and the impact of signal-to-noise ratio (SNR) on each model performance. Hence, this study aims to construct virtual steatosis models and synthesize MRI signals with different SNRs to systematically evaluate the accuracy of single- and dual-R2* models for FF and R2* estimations at 1.5T and 3.0T. METHODS: Realistic hepatic steatosis models encompassing clinical FF range (0-60 %) were created using morphological features of fat droplets (FDs) extracted from human liver biopsy samples. MRI signals were synthesized using Monte Carlo simulations for noise-free (SNRideal) and varying SNR conditions (5-100). Fat-water phantoms were scanned with different SNRs to validate simulation results. Fat water toolbox was used to calculate R2* and FF for both single- and dual-R2* models. The model accuracies in R2* and FF estimates were analyzed using linear regression, bias plot and heatmap analysis. RESULTS: The virtual steatosis model closely mimicked in vivo fat morphology and Monte Carlo simulation produced realistic MRI signals. For SNRideal and moderate-high SNRs, water R2* (R2*W) by dual-R2* and common R2* (R2*com) by single-R2* model showed an excellent agreement with slope close to unity (0.95-1.01) and R2 > 0.98 at both 1.5T and 3.0T. In simulations, the R2*com-FF and R2*W-FF relationships exhibited slopes similar to in vivo calibrations, confirming the accuracy of our virtual models. For SNRideal, fat R2* (R2*F) was similar to R2*W and dual-R2* model showed slightly higher accuracy in FF estimation. However, in the presence of noise, dual-R2* produced higher FF bias with decreasing SNR, while leading to only marginal improvement for high SNRs and in regions dominated by fat and water. In contrast, single-R2* model was robust and produced accurate FF estimations in simulations and phantom scans with clinical SNRs. CONCLUSION: Our study demonstrates the feasibility of creating virtual steatosis models and generating MRI signals that mimic in vivo morphology and signal behavior. The single-R2* model consistently produced lower FF bias for clinical SNRs across entire FF range compared to dual-R2* model, hence signifying that single-R2* model is optimal for assessing hepatic steatosis.

Current and emerging 3D visualization technologies in radiology.

As the field of three-dimensional (3D) visualization rapidly advances, how healthcare professionals perceive and interact with real and virtual objects becomes increasingly complex. Lack of clear vocabulary to navigate the changing landscape of 3D visualization hinders clinical and scientific advancement, particularly within the field of radiology. In this article, we provide foundational definitions and illustrative examples for 3D visualization in clinical care, with a focus on the pediatric patient population. We also describe how understanding 3D visualization tools enables better alignment of hardware and software products with intended use-cases, thereby maximizing impact for patients, families, and healthcare professionals.

Virtual reality applications in pediatric surgery.

Virtual reality modeling (VRM) is a 3-dimensional (3D) simulation. It is a powerful tool and has multiple uses and applications in pediatric surgery. Patient-specific 2-dimensional imaging can be used to generate a virtual reality model, which can improve anatomical perception and understanding, and can aid in preoperative planning for complex operations. VRM can also be used for realistic training and simulation. It has also proven effective in distraction for pediatric patients experiencing pain and/or anxiety. We detail the technical requirements and process required for VRM generation, the applications, and future directions.

Case 320: Intrathyroidal Thymic Tissue.

HISTORY: A 7-year-old boy with a history of pleuropulmonary blastoma after resection 6 years prior and germline DICER1 mutation was being monitored by physicians at a multidisciplinary genetic predisposition clinic. He demonstrated no evidence of recurrent pleuropulmonary blastoma, and his renal US, chest radiographic, and ocular screening examination results remained normal. Per age-directed screening guidelines, he underwent thyroid US. He had no signs or symptoms of hyper- or hypothyroidism. Physical examination was notable for the absence of thyromegaly or palpable nodule. US at 12-month follow-up showed no change in size or appearance of the left lobe (not shown). However, at this time, the Thyroid Imaging Reporting and Data System (TI-RADS) classification scheme was applied to the stable left lobe finding. The findings were discussed at a multidisciplinary thyroid nodule conference, and the decision was made to bring the patient back for a short-term follow-up for limited unenhanced MRI without sedation. A diagnosis was made based on the follow-up imaging findings.

Case 320.

HISTORY: A 7-year-old boy with a history of pleuropulmonary blastoma after resection 6 years prior and germline DICER1 mutation was being monitored by physicians at a multidisciplinary genetic predisposition clinic. He demonstrated no evidence of recurrent pleuropulmonary blastoma, and his renal US, chest radiographic, and ocular screening examination results remained normal. Per age-directed screening guidelines, he underwent thyroid US (Figs 1-3). He had no signs or symptoms of hyper- or hypothyroidism. Physical examination was notable for the absence of thyromegaly or palpable nodule. US at 12-month follow-up showed no change in size or appearance of the left lobe (not shown). However, at this time, the Thyroid Imaging Reporting and Data System (TI-RADS) classification scheme was applied to the stable left lobe finding. The findings were discussed at a multidisciplinary thyroid nodule conference, and the decision was made to bring the patient back for a short-term follow-up for limited unenhanced MRI without sedation (Fig 4). A diagnosis was made based on the follow-up imaging findings.

Simulation of a virtual liver iron overload model and R2 * estimation using multispectral fat-water models for GRE and UTE acquisitions at 1.5 T and 3 T.

R2 *-MRI has emerged as a noninvasive alternative to liver biopsy for assessment of hepatic iron content (HIC). Multispectral fat-water R2 * modeling techniques such as the nonlinear least squares (NLSQ) fitting and autoregressive moving average (ARMA) models have been proposed for the accurate assessment of iron overload by also considering fat, which can otherwise confound R2 *-based HIC measurements in conditions of coexisting iron overload and steatosis. However, the R2 * estimation by these multispectral models has not been systematically investigated for various acquisition methods in iron overload only conditions and across the full clinically relevant range of HICs (0-40 mg Fe/g dry liver weight). The purpose of this study is to evaluate the R2 * accuracy and precision of multispectral models for various multiecho gradient echo (GRE) and ultrashort echo time (UTE) imaging acquisitions by constructing virtual iron overload models based on true histology and synthesizing MRI signals via Monte Carlo simulations at 1.5 T and 3 T, and comparing their results with monoexponential model and published in vivo R2 *-HIC calibrations. The signals were synthesized with TE1 = 1.0 ms for GRE and TE1 = 0.1 ms for UTE acquisition for varying echo spacing, ΔTE (0.1, 0.5, 1, 2 ms), and maximum echo time, TEmax (2, 4, 6, 10 ms). An iron-doped phantom study is also conducted to validate the simulation results in experimental GRE (TE1 = 1.2 ms, ΔTE = 0.72 ms, TEmax = 6.24 ms) and UTE (TE1 = 0.1 ms, ΔTE = 0.5 ms, TEmax = 6.1 ms) acquisitions. For GRE acquisitions, the multispectral ARMA and NLSQ models produced higher slopes (0.032-0.035) compared with the monoexponential model and published in vivo R2 *-HIC calibrations (0.025-0.028). However, for UTE acquisition for shorter echo spacing (≤0.5 ms) and longer maximum echo time, TEmax (≥6 ms), the multispectral and monoexponential signal models produced similar R2 *-HIC slopes (1.5 T, 0.028-0.032; 3 T, 0.014-0.016) and precision values (coefficient of variation < 25%) across the full clinical spectrum of HICs at both 1.5 T and 3 T. The phantom analysis also showed that all signal models demonstrated a significant improvement in R2 * estimation for UTE acquisition compared with GRE, confirming our simulation findings. Future work should investigate the performance of multispectral fat-water models by simulating liver models in coexisting conditions of iron overload and steatosis for accurate R2 * and fat quantification.

Aggressive Pursuit of No Evidence of Disease Status in Hepatoblastoma Improves Survival: An Observational Study.

BACKGROUND: The utility of repeated surgical interventions in hepatoblastoma to achieve no evidence of disease (NED) is not well-defined. We examined the effect of aggressive pursuit of NED status on event-free (EFS) and overall survival (OS) in hepatoblastoma with subgroup analysis of high-risk patients. METHODS: Hospital records were queried for patients with hepatoblastoma from 2005 to 2021. Primary outcomes were OS and EFS stratified by risk and NED status. Group comparisons were performed using univariate analysis and simple logistic regression. Survival differences were compared with log-rank tests. RESULTS: Fifty consecutive patients with hepatoblastoma were treated. Forty-one (82%) were rendered NED. NED was inversely correlated with 5-year mortality (OR 0.006; CI 0.001-0.056; P < .01). Ten-year OS (P < .01) and EFS (P < .01) were improved by achieving NED. Ten-year OS was similar between 24 high-risk and 26 not high-risk patients when NED was attained (P = .83). Fourteen high-risk patients underwent a median of 2.5 pulmonary metastasectomies, 7 for unilateral disease, and 7 for bilateral, with a median of 4.5 nodules resected. Five high-risk patients relapsed, and three were salvaged. CONCLUSIONS: NED status is necessary for survival in hepatoblastoma. Repeated pulmonary metastasectomy and/or complex local control strategies to obtain NED can achieve long-term survival in high-risk patients. LEVEL OF EVIDENCE: Level III - Treatment Study - Retrospective Comparative Study.

Progressive metastatic infantile fibrosarcoma with multiple acquired mutations.

Infantile fibrosarcoma is the most common soft-tissue sarcoma in children under the age of 1 yr and is defined molecularly by NTRK fusion proteins. This tumor is known to be locally invasive; however, although rare, metastases can occur. The NTRK fusion acts as a driver for tumor formation, which can be targeted by first- and second-generation TRK inhibitors. Although NTRK gatekeeper mutations have been well-described as mechanisms of resistance to these agents, alternative pathway mutations are rare. Here, we report the case of a patient with infantile fibrosarcoma treated with chemotherapy and TRK inhibition that developed metastatic, progressive disease with multiple acquired mutations, including TP53, SUFU, and an NTRK F617L gatekeeper mutation. Alterations in pathways of SUFU and TP53 have been widely described in the literature in other tumors; however, not yet in infantile fibrosarcoma. Although most patients have a sustained response to TRK inhibitors, a subset will go on to develop mechanisms of resistance that have implications for clinical management, such as in our patient. We hypothesize this constellation of mutations contributed to the patient's aggressive clinical course. Taken together, we report the first case of infantile fibrosarcoma with ETV6::NTRK3 and acquired SUFU, TP53, and NTRK F617L gatekeeper mutation along with detailed clinical course and management. Our report highlights the importance of genomic profiling in recurrent infantile fibrosarcoma to reveal actionable mutations, such as gatekeeper mutations, that can improve patient outcomes.