Evaluation of 3D T1-weighted spoiled gradient echo MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.

PURPOSE: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (SPGR) MRI using artificial intelligence (AI) reconstruction. MATERIALS AND METHODS: This prospective, IRB-approved study enrolled 50 pediatric patients (mean age = 11.8 ± 3.1 years) undergoing clinical brain MRI. In addition to standard of care (SOC) compressed SENSE (CS = 2.5), 3D T1-weighted SPGR images were obtained with higher CS acceleration factors (5 and 8) to evaluate the ability of AI reconstruction to improve image quality and reduce scan time. Images were reviewed independently on dedicated research PACS workstations by two neuroradiologists. Quantitative analysis of signal intensities to calculate apparent grey and white matter signal to noise (aSNR) and grey-white matter apparent contrast to noise ratios (aCNR) was performed. RESULTS: AI improved overall image quality compared to standard CS reconstruction in 35% (35/100) of evaluations in CS = 2.5 (average scan time = 221 ± 6.9 s), 100% (46/46) of CS = 5 (average scan time = 113.3 ± 4.6 s) and 94% (47/50) of CS = 8 (average scan time = 74.1 ± 0.01 s). Quantitative analysis revealed significantly higher grey matter aSNR, white matter aSNR and grey-white matter aCNR with AI reconstruction compared to standard reconstruction for CS 5 and 8 (all p-values < 0.001), however not for CS 2.5. CONCLUSIONS: AI reconstruction improved overall image quality and gray-white matter qualitative and quantitative aSNR and aCNR in highly accelerated (CS = 5 and 8) 3D T1W SPGR images in the majority of pediatric patients.

Evaluation of T2W FLAIR MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.

BACKGROUND: Artificial intelligence (AI) reconstruction techniques have the potential to improve image quality and decrease imaging time. However, these techniques must be assessed for safe and effective use in clinical practice. OBJECTIVE: To assess image quality and diagnostic confidence of AI reconstruction in the pediatric brain on fluid-attenuated inversion recovery (FLAIR) imaging. MATERIALS AND METHODS: This prospective, institutional review board (IRB)-approved study enrolled 50 pediatric patients (median age=12 years, Q1=10 years, Q3=14 years) undergoing clinical brain MRI. T2-weighted (T2W) FLAIR images were reconstructed by both standard clinical and AI reconstruction algorithms (strong denoising). Images were independently rated by two neuroradiologists on a dedicated research picture archiving and communication system (PACS) to indicate whether AI increased, decreased, or had no effect on image quality compared to standard reconstruction. Quantitative analysis of signal intensities was also performed to calculate apparent signal to noise (aSNR) and apparent contrast to noise (aCNR) ratios. RESULTS: AI reconstruction was better than standard in 99% (reader 1, 49/50; reader 2, 50/50) for overall image quality, 99% (reader 1, 49/50; reader 2, 50/50) for subjective SNR, and 98% (reader 1, 49/50; reader 2, 49/50) for diagnostic preference. Quantitative analysis revealed significantly higher gray matter aSNR (30.6±6.5), white matter aSNR (21.4±5.6), and gray-white matter aCNR (7.1±1.6) in AI-reconstructed images compared to standard reconstruction (18±2.7, 14.2±2.8, 4.4±0.8, p<0.001) respectively. CONCLUSION: We conclude that AI reconstruction improved T2W FLAIR image quality in most patients when compared with standard reconstruction in pediatric patients.

Fetal magnetic resonance imaging, ultrasound, and echocardiography findings in twin reversed arterial perfusion sequence.

BACKGROUND: Twin reversed arterial perfusion (TRAP) sequence is a rare complication of monochorionic multiple gestation pregnancies, in which the pump twin provides hemodynamic support to a nonviable co-twin (acardius). Fetal magnetic resonance imaging (MRI) is used to detect pump twin abnormalities, particularly brain ischemia, prior to fetal intervention to interrupt umbilical blood flow to the acardius. OBJECTIVE: To summarize the imaging findings of TRAP sequence pregnancies in a large series. MATERIALS AND METHODS: A single-center retrospective review was performed of all TRAP sequence pregnancies referred for fetal MRI (2004-2021). Fetal MRI, ultrasound, and echocardiography data were collected. RESULTS: Eighty-eight TRAP sequence pregnancies with MRI were included (mean gestational age, 19.8±2.8 weeks). Demise of the pump twin was noted in two pregnancies at the time of MRI. By MRI, 12% (10/86) of live pump twins had abnormalities, including 3% (3/86) with brain abnormalities and 9% (8/86) with extra-cranial abnormalities. By echocardiography, 7% (6/86) of pump twins had structural cardiac abnormalities. Three acardius morphological subtypes were identified by MRI: acephalus (55%, 48/88), anceps (39%, 34/88), and amorphous (7%, 6/88). The mean ultrasound acardius to pump twin ratio A/P ratio, calculated for each twin pair as the ratio of the acardius trunk (and head, if present) plus limb volume to the pump twin estimated fetal weight) differed among the three acardius subtypes (P=.03). The mean A/P ratio moderately correlated with pump twin cardiothoracic ratio and combined cardiac output (Pearson's r=0.45 and 0.48, respectively, both P<.001). CONCLUSION: Fetal MRI of TRAP sequence pregnancies found anomalies in a substantial number of pump twins. The three acardius subtypes differed in A/P ratio, which moderately correlated with the pump twin cardiothoracic ratio and combined cardiac output.

Imaging Fetal Spine Malformations in the Context of In Utero Surgery.

This review covers the embryology, definition, and diagnosis of open spinal dysraphism with a focus on fetal ultrasound and MR imaging findings. Differentiating open versus closed spinal dysraphic defects on fetal imaging will also be discussed. Current fetal surgery practices and imaging findings in the context of fetal surgery are also reviewed.

A Prospective Multi-Institutional Study Comparing the Brain Development in the Third Trimester between Opioid-Exposed and Nonexposed Fetuses Using Advanced Fetal MR Imaging Techniques.

BACKGROUND AND PURPOSE: While the adverse neurodevelopmental effects of prenatal opioid exposure on infants and children in the United States are well described, the underlying causative mechanisms have yet to be fully understood. This study aims to compare quantitative volumetric and surface-based features of the fetal brain between opioid-exposed fetuses and unexposed controls by using advanced MR imaging processing techniques. MATERIALS AND METHODS: This is a multi-institutional IRB-approved study in which pregnant women with and without opioid use during the current pregnancy were prospectively recruited to undergo fetal MR imaging. A total of 14 opioid-exposed (31.4 ± 2.3 weeks of gestation) and 15 unexposed (31.4 ± 2.4 weeks) fetuses were included. Whole brain volume, cortical plate volume, surface area, sulcal depth, mean curvature, and gyrification index were computed as quantitative features by using our fetal brain MR imaging processing pipeline. RESULTS: After correcting for gestational age, fetal sex, maternal education, polysubstance use, high blood pressure, and MR imaging acquisition site, all of the global morphologic features were significantly lower in the opioid-exposed fetuses compared with the unexposed fetuses, including brain volume, cortical volume, cortical surface area, sulcal depth, cortical mean curvature, and gyrification index. In regional analysis, the opioid-exposed fetuses showed significantly decreased surface area and sulcal depth in the bilateral Sylvian fissures, central sulci, parieto-occipital fissures, temporal cortices, and frontal cortices. CONCLUSIONS: In this small cohort, prenatal opioid exposure was associated with altered fetal brain development in the third trimester. This adds to the growing body of literature demonstrating that prenatal opioid exposure affects the developing brain.