This editorial comment refers to the article “Identification of suspicious invasive placentation based on clinical MRI data using textural features and automated machine learning” by Sun et al. in
...European Radiology
.
Key Points
• Understanding how the placenta works is one of the major challenges facing radiologists.
• New perspectives are opening up for MRI studies of the placenta.
• The authors propose a new approach to placental MRI based on texture analysis and machine learning.
Abstract Background Ultrasound (US) is the primary imaging modality for the diagnosis of placenta accreta, but it is not sufficiently accurate. MRI morphologic criteria have recently emerged as a ...useful tool in this setting, but their analysis is too subjective. Recent studies suggest that gadolinium enhancement may help to distinguish between the stretched myometrium and placenta within a scar area. However, objective MRI criteria are still required for prenatal diagnosis of placenta accreta. The purpose of this study was to assess the diagnostic value of dynamic contrast gadolinium enhancement (DCE) MRI patterns for placenta accreta. Materials and methods MR images were acquired with a 1.5-T unit at 30–35 weeks of gestation in women with a history of Caesarian section, a low-lying anterior placenta, and US features compatible with placenta accreta. Sagittal, axial and coronal SSFP (Steady State Free Precession) sequences were acquired before injection. Then, contrast-enhanced dynamic T1-weighted images were acquired through the entire cross-sectional area of the placenta. Images were obtained sequentially at 10- to 14-s intervals for 2 min, beginning simultaneously with the bolus injection. Functional analysis was performed retrospectively, and tissular relative enhancement parameters were extracted from the recorded images. The suspected area of accreta (SAA) was placed in the region of the previous scar, and a control area (CA) of similar size was placed on the same image plane, as far as possible from the SAA. Semi-quantitative analysis of DCE-MR images was based on the kinetic enhancement curves in these two regions of interest (ROI). Three tissular relative enhancement parameters were compared according to the pregnancy outcomes, namely time to peak, maximal signal intensity, and area under the enhancement curve. Results We studied 9 women (43%) with accreta and 12 women (57%) with a normal placenta. All three tissular relative enhancement parameters differed significantly between the two groups (p < 10−3 ). Conclusion The use of dynamic contrast-enhanced MRI at 30–35 weeks of gestation in women with a high risk of placenta accreta allows the extraction of tissular enhancement parameters that differ significantly between placenta accreta and normal placenta. It therefore provides objective parameters on which to base the diagnosis and patient management.
Abstract Purpose Warthin's tumor is the second most frequent benign tumor of the parotid gland, with no risk of malignant evolution. That is why surgery should be avoided if the preoperative ...diagnosis is certain. The aim of the study was to assess the added value of a decisional algorithm for the preoperative diagnosis of Warthin's tumor. Materials and methods This retrospective IRB-approved study included 75 patients who underwent standardised MRI with conventional sequences (T1- and T2-weighted images, and T1 post-contrast sequences with fat saturation) and functional sequences: diffusion ( b 0, b 1000) and perfusion MR. Two independent readers reviewed the images using the decisional algorithm. The conclusion of each reader was: the lesion is or is not a Warthin's tumor. The MRI conclusion was compared with histology or with cytology and follow-up. We calculated the Cohen's kappa coefficient between the two observers and the sensitivity and specificity of the algorithm-helped-reading for the diagnosis of Warthin's tumor. Results Seventy-five patients; histology ( n = 61) or cytology and follow-up ( n = 14) results revealed 20 Warthin's tumors and 55 other tumors. Using the algorithm, sensitivity and specificity were 80–96%, and 85–100%, respectively for readers 1 and 2. The Cohen's kappa coefficient between the two observers was 0.79 ( P < 0.05) for the diagnosis of Warthin's tumor. Conclusion Our decisional algorithm helps the preoperative diagnosis of Warthin's tumor. The specificity of the technique is sufficient to avoid surgery if a parotid gland tumor presents all the MRI characteristics of a Warthin's tumor.
Objectives
To evaluate whether changes in BOLD signal intensities following hyperoxygenation are related to intrauterine growth restriction (IUGR) in a rat model.
Methods
IUGR was induced in pregnant ...rats by ligating the left vascular uterine pedicle at day 16 of gestation. BOLD MR imaging using a balanced steady-state free-precession (balanced-SSFP) sequence on a 1.5-T system was performed on day 19. Signal intensities (SI) before and after maternal hyperoxygenation were compared in the maternal liver and in control and growth-restricted foetoplacental units (FPUs).
Results
Maternal hyperoxygenation resulted in a significant increase in SI in all regions of interest (
P
< 0.05) in the 18 rats. In the control group, the SI (mean ± SD) increased by 21 % ± 15 in placentas (
n
= 74) and 13 % ± 8.5 in foetuses (
n
= 53). In the IUGR group, the increase was significantly lower: 6.5 % ± 4 in placentas (
n
= 36) and 7 % ± 5.5 in foetuses (
n
= 34) (
P
< 0.05).
Conclusion
BOLD MRI allows non-invasive assessment of the foetoplacental response to maternal hyperoxygenation in the rat and demonstrates its alteration in an IUGR model. This imaging method may provide a useful adjunct for the early diagnosis, evaluation, and management of human IUGR.
Key Points
•
Intra-uterine growth restriction is an important cause of perinatal morbidity and mortality.
•
Blood oxygen level-dependent MRI non-invasively assesses foetoplacental response to maternal hyperoxygenation.
•
In the rat, foetoplacental response to maternal hyperoxygenation is altered in IUGR.
•
Functional MRI may help to assess human IUGR.
This paper presents the use of the multiobjective particle swarm optimization (PSO) technique for the identification of Jiles-Atherton model parameters. This approach, implemented for the first time ...in order to solve this kind of problem, is tested for two magnetic materials: NO 3% SiFe and NiFe 20-80. The results are compared with those obtained with a direct search method and a genetic algorithm procedure. Experimental measures performed on both samples of materials allow us to complete and argue the validation for the PSO method.