The use of magnetic resonance imaging to predict placenta previa with placenta accreta spectrum

Development and validation of MRI-based scoring models for predicting placental invasiveness in high-risk women for placenta accreta spectrum

OBJECTIVES

To develop and validate MRI-based scoring models for predicting placenta accreta spectrum (PAS) invasiveness.

MATERIALS AND METHODS

This retrospective study comprised a derivation cohort and a validation cohort. The derivation cohort came from a systematic review of published studies evaluating the diagnostic performance of MRI signs for PAS and/or placenta percreta in high-risk women. The significant signs were identified and used to develop prediction models for PAS and placenta percreta. Between 2016 and 2021, consecutive high-risk pregnant women for PAS who underwent placental MRI constituted the validation cohort. Two radiologists independently evaluated the MRI signs. The reference standard was intraoperative and pathologic findings. The predictive ability of MRI-based models was evaluated using the area under the curve (AUC).

RESULTS

The derivation cohort included 26 studies involving 2568 women and the validation cohort consisted of 294 women with PAS diagnosed in 258 women (88%). Quantitative meta-analysis revealed that T2-dark bands, placental/uterine bulge, loss of T2 hypointense interface, bladder wall interruption, placental heterogeneity, and abnormal intraplacental vascularity were associated with both PAS and placenta percreta, and myometrial thinning and focal exophytic mass were exclusively associated with PAS. The PAS model was validated with an AUC of 0.90 (95% CI: 0.86, 0.93) for predicting PAS and 0.85 (95% CI: 0.79, 0.90) for adverse peripartum outcome; the placenta percreta model showed an AUC of 0.92 (95% CI: 0.86, 0.98) for predicting placenta percreta.

CONCLUSION

MRI-based scoring models established based on quantitative meta-analysis can accurately predict PAS, placenta percreta, and adverse peripartum outcome.

CLINICAL RELEVANCE STATEMENT

These proposed MRI-based scoring models could help accurately predict PAS invasiveness and provide evidence-based risk stratification in the management of high-risk pregnant women for PAS.

KEY POINTS

• Accurately identifying placenta accreta spectrum (PAS) and assessing its invasiveness depending solely on individual MRI signs remained challenging. • MRI-based scoring models, established through quantitative meta-analysis of multiple MRI signs, offered the potential to predict PAS invasiveness in high-risk pregnant women. • These MRI-based models allowed for evidence-based risk stratification in the management of pregnancies suspected of having PAS.

Nanoparticle Contrast-enhanced MRI for Visualization of Retroplacental Clear Space Disruption in a Mouse Model of Placental Accreta Spectrum (PAS)

INTRODUCTION

Prior preclinical studies established the utility of liposomal nanoparticle blood-pool contrast agents in visualizing the retroplacental clear space (RPCS), a marker of normal placentation, while sparing fetuses from exposure because the agent does not cross the placental barrier. In this work, we characterized RPCS disruption in a mouse model of placenta accreta spectrum (PAS) using these agents.

MATERIALS AND METHODS

Contrast-enhanced MRI (CE-MRI) and computed tomography (CE-CT) using liposomal nanoparticles bearing gadolinium (liposomal-Gd) and iodine were performed in pregnant Gab3-/- and wild type (WT) mice at day 16 of gestation. CE-MRI was performed on a 1T scanner using a 2D T1-weighted sequence (100×100×600 µm3 voxels) and CE-CT was performed at a higher resolution (70×70×70 µm3 voxels). Animals were euthanized post-imaging and feto-placental units (FPUs) were harvested for histological examination. RPCS conspicuity was scored through blinded assessment of images.

RESULTS

Pregnant Gab3-/- mice showed elevated rates of complicated pregnancy. Contrast-enhanced imaging demonstrated frank infiltration of the RPCS of Gab3-/- FPUs. RPCS in Gab3-/- FPUs was smaller in volume, demonstrated a heterogeneous signal profile, and received lower conspicuity scores than WT FPUs. Histology confirmed in vivo findings and demonstrated staining consistent with a thinner RPCS in Gab3-/- FPUs.

DISCUSSION

Imaging of the Gab3-/- mouse model at late gestation with liposomal contrast agents enabled in vivo characterization of morphological differences in the RPCS that could cause the observed pregnancy complications. An MRI-based method for visualizing the RPCS would be valuable for early detection of invasive placentation.

Predicting Placenta Accreta Spectrum Disorders in a Cohort of Pregnant Patients in the North-East Region of Romania-Diagnostic Accuracy of Ultrasound and Magnetic Resonance Imaging

Background: Placenta accreta spectrum (PAS) disorders are associated with high mortality and morbidity due to postpartum hemorrhage, hysterectomy, and organ injury, and a multidisciplinary team is required for an individualized case management. In this study, we assessed the diagnostic and prognostic accuracy of the most important ultrasonographic (US) and magnetic resonance imagining (MRI) markers for PAS disorders. Material and Methods: The study included 39 adult pregnant patients with at least one previous cesarean delivery and both US and MRI investigations for placenta previa evaluated at the tertiary maternity hospital ‘Cuza Voda’, Iasi, between 2019 and 2021. The following US signs were evaluated: intra-placental lacunae, loss of the retroplacental hypoechoic zone, myometrial thinning < 1 mm, bladder wall interruption, placental bulging, bridging vessels, and the hypervascularity of the uterovesical or retroplacental space. The MRI signs that were evaluated were intra-placental dark T2 bands, placental bulging, loss of the retroplacental hypointense line on T2 images, myometrial thinning, bladder wall interruption, focal exophytic placental mass, and abnormal vascularization of the placental bed. Results: The US and MRI signs analyzed in our study presented adequate sensitivities and specificities for PAS, but no sign proved to be a useful predictor by itself. The presence of three or more US markers for accretion was associated with a sensitivity of 84.6.6% and a specificity of 92.3% (p < 0.001). The presence of three or more MRI signs supplemented these results and were associated with a sensitivity of 92.3% and a specificity of 61.5% for predicting PAS (p < 0.001). Moreover, US and MRI findings were correlated with FIGO grading and severity of PAS. Conclusions: Even though no US or MRI finding alone can predict PAS with high sensitivity and specificity, our study proves that the presence of three or more imagistic signs could significantly increase the diagnostic accuracy of this condition. Furthermore, US and MRI could be useful tools for evaluating prognostic and perinatal planning.

Effectiveness of a fetal magnetic resonance imaging scoring system for predicting the prognosis of pernicious placenta previa: A retrospective study

Background: The value of multiple magnetic resonance imaging (MRI) signs in predicting pernicious placenta previa (PPP) with placenta accreta spectrum disorders (PAS) is still controversial. This study aimed to investigate the value of a self-made fetal magnetic resonance imaging scoring system in predicting the different types of PAS in pernicious placenta previa and its associated risk of bleeding.

Methods: This retrospective study included 193 patients diagnosed with PPP based on MRI findings before delivery. Based on pathological and intraoperative findings, we divided patients into four groups: non-PAS, placental adhesion, placental implantation, and placenta percreta. Receiver operator characteristic curves of the MRI total score and placental implantation type were drawn using pROC packages in the R Studio environment, and cutoff values of each type were calculated, as well as diagnostic evaluation indexes, such as sensitivity, specificity, and the Youden index. Hemorrhage during surgery was compared between the groups.

Results: The boundary value between the non-PAS and placental adhesion was 5.5, that between placental adhesion and placental implantation was 11.5, and that between placental implantation and placenta percreta was 15.5 points. The respective specificities were 0.700, 0.869, and 0.958, and the respective sensitivities were 0.994, 0.802, and 0.577. The Youden indices were 0.694, 0.671, and 0.535, respectively. The median (minimum, maximum) quantities of hemorrhage during the operation in the non-PAS, placental adhesion, placental implantation, and placenta percreta groups were 225 (100, 3700), 600 (200, 6000), 1500 (300, 7000), and 3000 (400, 6300) ml, respectively. Hemorrhage was significantly different between the four groups (p < 0.001).

Conclusion: These results suggest that the proposed MRI scoring system could be an effective diagnostic tool for assessing PPP types and predicting the associated bleeding risk.

Deep Learning Algorithm-Based Ultrasound Image Information in Diagnosis and Treatment of Pernicious Placenta Previa

This study was to explore the value of the deep dictionary learning algorithm in constructing a B ultrasound scoring system and exploring its application in the clinical diagnosis and treatment of pernicious placenta previa (PPP). 60 patients with PPP were divided into a low-risk group (severe, implantable) and high-risk group (adhesive, penetrating) according to their clinical characteristics, B ultrasound imaging characteristics, and postpartum pathological examination results. Under PPP ultrasonic image information using the deep learning algorithm, the B ultrasound image diagnostic scoring system was established to predict the depth of various types of placenta accreta. The results showed that the cut-off values of severe, implantable, adhesive, and penetrating types were <2.3, 2.3-6.5, 6.5-9, and ≥9 points, respectively; there were significant differences in the termination of pregnancy and neonatal birth weight between the two groups (P < 0.05); the positive predictive value, negative predictive value, and false positive rate of ultrasound images based on the deep dictionary learning algorithm for PPP were 95.33%, 94.89%, and 3.56%, respectively. Thus, the ultrasound image diagnostic scoring system based on the deep learning algorithm has an important predictive role for PPP, which can provide a more targeted diagnosis and treatment plan for patients in clinical practice and improve the prediction and treatment efficiency.

Clinical Analysis of Factors Influencing the Development of Placenta Praevia and Perinatal Outcomes in First-Time Pregnant Patients

Objective

To analyze the risk factors associated with the development of placenta praevia (PP) in first-time pregnant patients and to observe the perinatal clinical outcomes of patients.

Methods

The clinical data of 112 pregnant women with PP (PP group) and 224 pregnant women with normal placental position (general group) who delivered in our hospital from August 2016 to August 2021 were retrospectively analyzed. Baseline demographic data such as age, gestational week, uterine history, assisted reproductive technology use, pregnancy comorbidities, pre-pregnancy body mass index (BMI), smoking, alcohol consumption, placental position, educational level, work were collected from both groups, and logistic regression models were used to analyze the factors influencing the occurrence of PP in patients with first pregnancy. Perinatal outcomes such as implementation of hemostatic treatment (uterine balloon compression, arterial ligation, and B-Lynch suture), maternal postpartum related indicators (amount of postpartum bleeding, incidence of postpartum hemorrhage, blood transfusion rate, blood transfusion volume, and length of hospital stay), and neonatal condition (birth weight, Apgar score at 1 and 5 min after birth) were counted and compared between the two groups.

Results

Histories of endometriosis, use of assisted reproductive technology, and smoking or secondhand smoke inhalation were all high risk factors for PP in patients with first pregnancies, and the proportion of maternal and neonatal adverse outcomes was significantly higher in the PP group than in the general group (P < 0.05).

Conclusion

Histories of endometriosis, smoking (secondhand smoke), and use of assisted reproductive technologies are independent risk factors for PP in patients with first pregnancies, which can increase the risk of labor and death of the newborn.

Criteria for placenta accreta spectrum in the International Federation of Gynaecology and Obstetrics classification, and topographic invasion area are associated with massive hemorrhage in patients with placenta previa

INTRODUCTION

Placenta previa with placenta accreta spectrum (PAS) is a life-threatening disease that results in massive hemorrhage. The clinical and histologic criteria of PAS were adopted according to the International Federation of Gynaecology and Obstetrics (FIGO) classification. We aimed to investigate whether FIGO criteria and topography were associated with maternal complications in patients with placenta previa.

MATERIAL AND METHODS

Patients with placenta previa who underwent cesarean section at our institution between January 2003 and December 2019 were identified. First, they were divided based on FIGO classification, as follows: Group A, with clinical criteria; Group B, with histologic criteria; and Group C: without clinical or histologic criteria. Next, cases with PAS were classified according to the topographic invasion area, as follows: type 1, upper posterior bladder; type 2, lower posterior bladder; type 3, parametrium; type 4, posterior lower uterine segment. Predictive factors for massive hemorrhage were retrospectively analyzed.

RESULTS

Among the 350 patients, 24 (6.9%) were classified as Group A, 16 (4.6%) as Group B and 310 (88.5%) as Group C. Regarding maternal history and hemostatic procedures, there were no significant factors other than hysterectomy (p < .01) in Groups A and B. The volume of blood loss in both Groups A and B was greater than in Group C (p < .01). The rates of uterine artery embolization and blood transfusion were higher in Groups A and B than in Group C (p < .01). In addition, there were no significant factors other than hysterectomy between Groups A and B. In the multivariate analysis for massive hemorrhage, Group A (odds ratio: 2.73, p = .04) and Group B (odds ratio: 12.69, p < .01) were identified as independent predictive factors. In addition, massive hemorrhage was closely related to the lower posterior bladder and parametrial invasion in both Groups A and B.

CONCLUSIONS

Both clinical and histologic criteria for PAS in the FIGO classification were associated with massive hemorrhage. Diagnosing clinical PAS using the FIGO classification, additional hemostatic procedures might be necessary according to the topographic invasion area.