Current role of body MRI in pediatric oncology

Use of modern three-dimensional imaging models to guide surgical planning for local control of pediatric extracranial solid tumors

INTRODUCTION

In complex pediatric surgical oncology, surgical planning is contingent upon data gathered from preoperative imaging. Three-dimensional (3D) modeling and printing has been shown to be beneficial for adult presurgical planning, though pediatric literature is less robust. The study reviews our institutional experience with the use of 3D image segmentation and printed models in approaching resection of extracranial solid tumors in children.

METHODS

This is a single institutional series from 2021 to 2023. Models were based on computed tomography and magnetic resonance imaging studies, optimized for 3D imaging. The feasibility and creation of the models is reviewed, including specific techniques, software, and printing materials from our institution. Clinical implications for surgical planning are also described, along with detailed preoperative and intraoperative images.

RESULTS

3D modeling and printing was performed for four pediatric patients diagnosed with extracranial solid tumors. Diagnoses included Ewing sarcoma, hepatoblastoma, synovial sarcoma, and osteosarcoma. No intraoperative complications or discrepancies with the preoperative 3D-printed model were noted. No evidence of local recurrence was identified in any patient thus far.

CONCLUSION

Our institutional series demonstrates a wide spectrum of clinical application for 3D modeling and printing technology within pediatric surgical oncology. This technology may aid in surgical planning for both resection and reconstruction, can be applied to a diverse breadth of diagnoses, and may potentially augment patient and/or family education about their condition.

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases

Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-based diagnosis in patients with uterine sarcomas. Fifteen sequences of MRI for patients (uterine sarcoma group: n = 63; uterine leiomyoma: n = 200) were used to train the models. Six radiologists (three specialists, three practitioners) interpreted the same images for validation. The most important individual sequences for diagnosis were axial T2-weighted imaging (T2WI), sagittal T2WI, and diffusion-weighted imaging. These sequences also represented the most accurate combination (accuracy: 91.3%), achieving diagnostic ability comparable to that of specialists (accuracy: 88.3%) and superior to that of practitioners (accuracy: 80.1%). Moreover, radiologists' diagnostic accuracy improved when provided with DNN results (specialists: 89.6%; practitioners: 92.3%). Our DNN models are valuable to improve diagnostic accuracy, especially in filling the gap of clinical skills between interpreters. This method can be a universal model for the use of deep learning in the diagnostic imaging of rare tumors.

The role of whole-body MRI in musculoskeletal inflammation detection and treatment response evaluation in inflammatory arthritis across age: A systematic review

OBJECTIVE

To evaluate the relation between whole-body MRI (WBMRI) outcomes and disease activity measures, including clinical examination, composite scores, and other imaging outcomes, and the ability of WBMRI to detect treatment response in patients with inflammatory arthritis (IA) across age.

METHODS

Human studies published as full text or abstract in the PubMed and MEDLINE and Cochrane databases from inception to 11th April 2021 were systematically and independently searched by two reviewers. Studies including patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), spondyloarthritis (SpA), juvenile idiopathic arthritis (JIA) or unclassified inflammatory arthritis (UA) who underwent WBMRI and which reported on disease outcomes were included.

RESULTS

Nineteen full-text studies were eligible for inclusion: 2 interventional, 7 retrospective and 10 prospective observational studies, comprising 540 participants (SpA 38.7%, RA 24.8%, JIA 17.8%, PsA 11.5%, healthy controls 5.9%, UA 1.3%). Abstracts of 6 conference papers were reported separately. Five studies in PsA and SpA and 4 in RA measured the frequency of WBMRI-detected and clinically-detected synovitis, and all found the former to be more frequent. Less enthesitis was detected by WBMRI than clinical examination in 5/8 studies. After biologic treatment, the WBMRI inflammation scores declined in 3 studies in SpA and 2 in RA, whilst in 3 studies the results were equivocal.

CONCLUSION

The ability of WBMRI to assess disease activity and treatment response in IA was adequate overall. Further studies are needed to corroborate WBMRI findings with IA outcomes and investigate the clinical value of subclinical inflammation.

Predictors of Anesthetic Exposure in Pediatric MRI

BACKGROUND. Anesthetic exposure in children may impact long-term neurocognitive outcomes. Therefore, minimizing pediatric MRI scan time in children under anesthesia and the associated anesthetic exposure is necessary. OBJECTIVE. The purpose of this study was to evaluate pediatric MRI scan time as a predictor of total propofol dose, considering imaging and clinical characteristics as covariates. METHODS. Electronic health records were retrospectively searched to identify MRI examinations performed from 2016 to 2019 in patients 0-18 years old who received propofol anesthetic. Brain; brain and spine; brain and abdomen; and brain, head, and neck MRI examinations were included. Demographic, clinical, and imaging data were extracted for each examination, including anesthesia maintenance phase time, MRI scan time, and normalized propofol dose. MRI scan time and propofol dose were compared between groups using a t test. A multiple linear regression with backward selection (threshold, p < .05) was used to evaluate MRI scan time as a predictor of total propofol dose, adjusting for sex, age, time between scan and study end, body part, American Society of Anesthesiologists (ASA) classification, diagnosis, magnet strength, and IV contrast medium administration as covariates. RESULTS. A total of 501 examinations performed in 426 patients (172 girls, 254 boys; mean age, 6.55 ± 4.59 [SD] years) were included. Single body part examinations were shorter than multiple body part examinations (mean, 52.7 ± 18.4 vs 89.3 ± 26.4 minutes) and required less propofol (mean, 17.7 ± 5.7 vs 26.1 ± 7.7 mg/kg; all p < .001). Among single body part examinations, a higher ASA classification, oncologic diagnosis, 1.5-T magnet, and IV contrast medium administration were associated with longer MRI scan times (all p ≤ .009) and higher propofol exposure (all p ≤ .005). In multivariable analysis, greater propofol exposure was predicted by MRI scan time (mean dose per minute of examination, 0.178 mg/kg; 95% CI, 0.155-0.200; p < .001), multiple body part examination (p = .04), and IV contrast medium administration (p = .048); lower exposure was predicted by 3-T magnet (p = .04). CONCLUSION. Anesthetic exposure during pediatric MRI can be quantified and predicted based on imaging and clinical variables. CLINICAL IMPACT. This study serves as a valuable baseline for future efforts to reduce anesthetic doses and scan times in pediatric MRI.

Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique

OBJECTIVES

To evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combined with a deep learning-based noise reduction technique for pediatric abdominal CT, compared with standard iodine concentration single-energy polychromatic CT (SECT).

METHODS

From December 2016 to May 2017, DECT with 300 mg•I/mL contrast medium was performed in 29 pediatric patients (17 boys, 12 girls; age, 2-19 years). The DECT images were reconstructed using a noise-optimized virtual monoenergetic reconstruction image (VMI) with and without a deep learning method. SECT images with 350 mg•I/mL contrast medium, performed within the last 3 months before the DECT, served as reference images. The quantitative and qualitative parameters were compared using paired t tests and Wilcoxon signed-rank tests, and the differences in radiation dose and total iodine administration were assessed.

RESULTS

The linearly blended DECT showed lower attenuation and higher noise than SECT. The 60-keV VMI showed an increase in attenuation and higher noise than SECT. The combined 60-keV VMI plus deep learning images showed low noise, no difference in contrast-to-noise ratios, and overall image quality or diagnostic image quality, but showed a higher signal-to-noise ratio in the liver and lower enhancement of lesions than SECT. The overall image and diagnostic quality of lesions were maintained on the combined noise reduction approach. The CT dose index volume and total iodine administration in DECT were respectively 19.6% and 14.3% lower than those in SECT.

CONCLUSION

Low iodine concentration DECT, combined with deep learning in pediatric abdominal CT, can maintain image quality while reducing the radiation dose and iodine load, compared with standard SECT.

KEY POINTS

• An image noise reduction approach combining deep learning and noise-optimized virtual monoenergetic image reconstruction can maintain image quality while reducing radiation dose and iodine load. • The 60-keV virtual monoenergetic image reconstruction plus deep learning images showed low noise, no difference in contrast-to-noise ratio, and overall image quality, but showed a higher signal-to-noise ratio in the liver and a lower enhancement of lesion than single-energy polychromatic CT. • This combination could offer a 19.6% reduction in radiation dose and a 14.3% reduction in iodine load, in comparison with a control group that underwent single-energy polychromatic CT with the standard protocol.

Ceramic resonators for targeted clinical magnetic resonance imaging of the breast

Currently, human magnetic resonance (MR) examinations are becoming highly specialized with a pre-defined and often relatively small target in the body. Conventionally, clinical MR equipment is designed to be universal that compromises its efficiency for small targets. Here, we present a concept for targeted clinical magnetic resonance imaging (MRI), which can be directly integrated into the existing clinical MR systems, and demonstrate its feasibility for breast imaging. The concept comprises spatial redistribution and passive focusing of the radiofrequency magnetic flux with the aid of an artificial resonator to maximize the efficiency of a conventional MR system for the area of interest. The approach offers the prospect of a targeted MRI and brings novel opportunities for high quality specialized MR examinations within any existing MR system.

Here, the authors present a concept for targeted clinical magnetic resonance imaging for relatively small targets in the body. They use an artificial resonator for spatial redistribution and passive focusing of the radiofrequency magnetic flux and demonstrate feasibility for targeted breast imaging.

Whole-body magnetic resonance imaging of pediatric cancer predisposition syndromes: special considerations, challenges and perspective

Cancer predisposition syndromes increase the incidence of tumors during childhood and are associated with significant morbidity and mortality. Imaging is paramount for ensuring early detection of neoplasms, impacting therapeutic interventions and potentially improving outcome. While conventional imaging techniques involve considerable exposure to ionizing radiation, whole-body MRI is a radiation-free modality that allows continuous imaging of the entire body and has increasingly gained relevance in the surveillance, diagnosis, staging and monitoring of pediatric patients with cancer predisposition syndromes. Nevertheless, widespread implementation of whole-body MRI faces several challenges as a screening tool. Some of these challenges include developing clinical indications, variability in protocol specifications, image interpretation as well as coding and billing practices. These factors impact disease management, patient and family experience and research collaborations. In this discussion we review the aforementioned special considerations and the potential direction that might help overcome these challenges and promote more widespread use of whole-body MRI in children with cancer predisposition syndromes.

Pediatric Renal Neoplasms:: MR Imaging-Based Practical Diagnostic Approach

Pediatric renal tumors may be malignant or benign. Wilms tumor, the most common malignant pediatric renal tumor, arises sporadically or with various syndromes. Renal cell carcinoma typically presents in older children. Renal clear cell sarcoma and rhabdoid tumor are typically less common, more aggressive, and present in younger children. Benign renal tumors include mesoblastic nephroma, multilocular cystic renal tumor, angiomyolipoma, and metanephric adenoma. Lymphoma and leukemia may secondarily involve the kidney. Although there is overlap in the imaging appearance of several pediatric renal tumors, magnetic resonance characteristics and clinical data narrow the differential diagnosis and suggest a specific diagnosis. This article reviews current MR techniques, as well as the common MR imaging characteristics of malignant and benign pediatric renal neoplasms.

Pediatric Cancer Predisposition Imaging: Focus on Whole-Body MRI

The American Association for Cancer Research convened a meeting of international pediatric oncologists, geneticists, genetic counselors, and radiologists expert in childhood cancer predisposition syndromes (CPS) in October 2016 to propose consensus surveillance guidelines. Imaging plays a central role in surveillance for most, though not all, syndromes discussed. While encompassing the full gamut of modalities, there is increasing emphasis on use of nonionizing radiation imaging options such as magnetic resonance imaging (MRI) in children and adolescents, especially in the pediatric CPS population. In view of rapid evolution and widespread adoption of whole-body MRI (WBMRI), the purpose of our review is to address WBMRI in detail. We discuss its place in the surveillance of a range of pediatric CPS, the technical and logistical aspects of acquiring and interpreting these studies, and the inherent limitations of WBMRI. We also address issues associated with sedation and use of gadolinium-based contrast agents in MRI in children. Clin Cancer Res; 23(11); e6-e13. ©2017 AACRSee all articles in the online-only CCR Pediatric Oncology Series.

Whole body MRI of the non-human primate using a clinical 3T scanner: initial experiences

With the advent of parallel imaging MRI techniques, whole-body MRI is being increasingly used in clinical diagnosis. However, its application in preclinical research using large animals remains very limited. In the present study, the whole-body MRI techniques for adult macaque monkeys were explored using a conventional clinic 3T scanner. The T1, T2 anatomical images, and MR angiography of adult macaque whole bodies were illustrated. The preliminary results suggest whole-body MRI can be a robust tool to examine multiple organs of non-human primate (NHP) models from head to toe non-invasively and simultaneously using a conventional clinical setting. As NHPs are intensely used in biomedical research such as HIV/AIDS and vaccine discovery, whole body MRI techniques can have a wide range of applications in translational research using NHPs.