Magnetic resonance imaging is often misleading when used as an adjunct to ultrasound in the management of placenta accreta spectrum disorders

Comparison between abdominal ultrasound and nuclear magnetic resonance imaging detection of placenta accreta in the second and third trimester of pregnancy

This study is to determine accuracy of abdominal ultrasound and nuclear magnetic resonance imaging (MRI) for placenta accreta in the second and third trimester of pregnancy and to define the most relevant features of abdominal ultrasound and MRI for placenta accreta prediction.Between September 2012 and September 2018, 245 high risk of placenta accreta in the second trimester of pregnancy were prenatal diagnosed by abdominal ultrasound and MRI and they were followed up until the end of pregnancy.Forty-six patients at the second trimester of pregnancy and 40 patients at the third trimester of pregnancy were confirmed as placenta accreta. For the second and third trimester of pregnancy, the sensitivity (Se), specificity (Sp), positive and negative predictive value (PPV and NPV) of abdominal ultrasound were 95.65% versus 97.50%, 91.78% versus 90.70%, 88% versus 83%, and 97% versus 99%, respectively, while the Se, Sp, PPV, and NPV of MRI were 89.13% versus 92.50%, 87.67% versus 8721%, 82% versus 77%, and 93% versus 96%, respectively. Five features having significant statistical differences between normal placentation women and placenta accreta patients in second or third trimester of pregnancy, including loss of the normal retroplacental clear space, thinning or disappearance of the myometrium, increased vascularization at the uterine serosa-bladder wall interface, and vascularization perpendicular to the uterine wall on abdominal ultrasound, and uterine bulging and dark intraplacental bands on MRI.Abdominal ultrasound and MRI for placenta accreta in the second and third trimester of pregnancy could provide meaningful imaging evidences.

Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study

BACKGROUND

Identification of pregnancies with postpartum haemorrhage (PPH) antenatally rather than intrapartum would aid delivery planning, facilitate transfusion requirements and decrease maternal complications. MRI has been increasingly used for placenta evaluation. Here, we aim to build a nomogram incorporating both clinical and radiomic features of placenta to predict the risk for PPH in pregnancies during caesarian delivery (CD).

METHODS

A total of 298 pregnant women were retrospectively enrolled from Henan Provincial People's Hospital (training cohort: n = 207) and from The Third Affiliated Hospital of Zhengzhou University (external validation cohort: n = 91). These women were suspected with placenta accreta spectrum (PAS) disorders and underwent MRI for placenta evaluation. All of them underwent CD and were singleton. PPH was defined as more than 1000 mL estimated blood loss (EBL) during CD. Radiomic features were selected based on their correlations with EBL. Radiomic, clinical, radiological, clinicoradiological and clinicoradiomic models were built to predict the risk of PPH for each patient. The model with the best prediction performance was validated with its discrimination ability, calibration curve and clinical application.

FINDINGS

Thirty-five radiomic features showed strong correlation with EBL. The clinicoradiomic model resulted in the best discrimination ability for risk prediction of PPH, with AUC of 0.888 (95% CI, 0.844-0.933) and 0.832 (95% CI, 0.746-0.913), sensitivity of 91.2% (95% CI, 85.8%-96.7%) and 97.6% (95% CI, 92.7%-100%) in the training and validation cohort respectively. For patients with severe PPH (EBL more than 2000 mL), 53 out of 55 pregnancies (96.4%) in the training cohort and 18 out of 18 (100%) pregnancies in the validation cohort were identified by the clinicoradiomic model. The model performed better in patients without placenta previa (PP) than in patients with PP, with AUC of 0.983 compared with 0.867, sensitivity of 100% compared with 90.8% in the training cohort, AUC of 0.832 compared with 0.815, sensitivity of 97.6% compared with 97.2% in the validation cohort.

INTERPRETATION

The clinicoradiomic model incorporating both prenatal clinical factors and radiomic signature of placenta on T2WI showed good performance for risk prediction of PPH. The predictive model can identify severe PPH with high sensitivity and can be applied in patients with and without PP.

New evidence-based diagnostic and management strategies for placenta accreta spectrum disorders

The increasing incidence of caesarean delivery (CD) has resulted in an increase in placenta accreta spectrum (PAS), adversely impacting maternal outcomes globally. Currently, more than 90% of women diagnosed with PAS present with a placenta praevia (praevia PAS). Praevia PAS can be reliably diagnosed antenatally with ultrasound, and it is unclear whether magnetic resonance imaging improves diagnosis beyond what can be achieved by skilled ultrasound operators. Therefore, any screening programme for PAS will require improved training in the diagnosis of placental disorders and development of targeted scanning protocols. Management strategies for praevia PAS vary depending on the accuracy of prenatal diagnosis, findings at laparotomy and local surgical expertise. Current epidemiological data for PAS are highly heterogeneous, mainly due to wide variation in the clinical criteria used to diagnose the condition at birth. This significantly impacts research into all aspects of the condition, especially comparison of the efficacy of different management strategies.

US and MR imaging findings to detect placental adhesion spectrum (PAS) in patients with placenta previa: a comparative systematic study

PURPOSE

To compare the performance US and MR in identifying placental adhesion spectrum (PAS) in placenta previa (PP) and to establish a potential method of image interpretation.

METHODS

US and MR examinations of 51 patients with PP were selected. The presence of imaging signs commonly used to detect PAS was assessed. Penalized logistic regression was performed considering histology as standard of reference; only signs statistically significant (p < 0.05) were considered for ROC and multivariate analysis. The probability of PAS according to the presence of US and/or MR signs was then assessed.

RESULTS

At univariate analysis, loss of retroplacental clear space, myometrial thinning (MT) and placenta lacunar spaces on US, intraplacental dark bands (IDBs), focal interruption of myometrial border (FIMB) and abnormal vascularity (AV) on MR were statistically significant (p < 0.01). Three diagnostic methods for PAS were then developed for both US and MR when at least one (Method 1), two (Method 2) or three (Method 3) imaging signs occurred, respectively. Method 2 for MR showed a significantly (p < 0.05) higher accuracy (91%) compared to the other methods. When MR IDBs and AV as well as IDBs and FIMB were present in combination with US MT the probability of PAS increased from 75 to 90% and from 80 to 91%, respectively.

CONCLUSION

MR demonstrated a higher diagnostic accuracy than US to detect PAS. However, since the combination of MR and US signs could improve the probability to detect PAS, a complementary diagnostic role of these techniques could be considered.

Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?

PURPOSE

To determine if texture analysis can differentiate placenta accreta spectrum (PAS) from normal placenta on MRI.

METHODS

We performed retrospective image analysis of 80 patients, comprised of 46 patients with PAS and 34 patients without PAS. Histopathology was used as the reference standard. Sagittal single shot fast spin echo T2-weighted MRI sequences acquired from a single institution were analyzed. Placental heterogeneity was quantified using in-house software on a Matlab platform, including the standard deviation of pixel intensity, coefficient of variation, gray-level co-occurrence matrices (GLCM), histogram-oriented gradients (HOG), and fractal analysis with box sizes from 2 to 512. Two-tailed unpaired Student's t test was used with statistical significance of p < 0.05.

RESULTS

PAS was associated with higher values for standard deviation of pixel intensity and fractal analysis at every box size. Fractal analysis at box sizes 256 (p = 0.011) and 32 (p = 0.021), and standard deviation of pixel intensity (p = 0.023) were the most statistically significant. Fractal values at box size 256 for PAS was 0.13 versus 0.090 for patients without PAS, while standard deviation of pixel intensity was 3.7 for PAS versus 2.5 for patients without PAS. No statistically significant association between PAS and GLCM, coefficient of variation, and HOG was found.

CONCLUSION

Statistically significant differences were found between normal and abnormal groups using standard deviation of pixel intensity and fractal analysis.

Surgical Management of Placenta Accreta Spectrum

This is a discussion of the standard surgical treatment of placenta accreta spectrum disorders including preoperative considerations, diagnostic imaging, surgical steps for cesarean hysterectomy, and postoperative management.

Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa

PURPOSE

To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis is that TA features may reflect histological abnormalities underlying PAS in patients with PP thus helping in differentiating positive from negative cases.

MATERIALS AND METHODS

Pre-operative MRI examinations of 64 patients with PP of which 20 positive (12 accreta, 7 increta and 1 percreta) and 44 negative for PAS were retrospectively selected. Multiple (n = 3) rounded regions of interest (ROIs) were manually positioned on sagittal or coronal T2-weighted images over homogeneous placental tissue close to the placental-myometrial interface for each patient to extract TA features. After balancing the dataset with the Synthetic Minority Over-sampling Technique, training and testing sets were obtained using Hold-out with a 75/25% split. Different algorithms were applied on the training set using the wrapper method, which looks for the best combination of features based on the optimization of a heuristic function in order to get the highest accuracy, and a 10-fold Cross-validation. The accuracy of the best models was also assessed on the test set. Histology was used as the standard of reference.

RESULTS

A total of 192 ROIs were positioned and a ROI-based analysis was then conducted. Among the different algorithms, k-nearest neighbors obtained the highest accuracy (98.1%), precision (98.7%), sensitivity (97.5%) and specificity (98.7%) while exploiting the lowest number of features (n = 26); conversely, the Naïve Bayes algorithm got the lowest scores showing an accuracy of 80.5%.

CONCLUSION

ML analysis using MRI-derived TA features could be a feasible tool in the identification of placental tissue abnormalities underlying PAS in patients with PP. This approach might represent an additional tool in the clinical practice, thus expanding the application field of artificial intelligence to medical images.

Surgical Management of the Placenta Accreta Spectrum: An Institutional Experience

OBJECTIVE

The incidence of placenta accreta spectrum (PAS) has risen over the past decades, primarily in response to increasing Caesarean section rates. The surgical management of PAS is associated with significant morbidity, including hemorrhage and intensive care unit (ICU) admission. This study sought to evaluate the surgical outcomes of a PAS operative approach.

METHODS

A single-centre retrospective chart review of all Caesarean hysterectomies for PAS by an assigned surgeon over a 16-year period was performed. Surgical outcomes were described (Canadian Task Force Classification II-2).

RESULTS

The described surgical approach involves a midline skin incision, high midline hysterotomy, a rapid single-layer uterine closure with no placental removal attempt, constant cephalad uterine traction, and liberal choice of subtotal hysterectomy. A total of 47 patients were included: 19 (40.4%) with placenta accreta, 14 (29.8%) with placenta increta, and 14 (29.8%) with placenta percreta. Mean estimated blood loss was 1416 ± 699 mL, and mean operative time was 112 ± 49 minutes. Overall, 16 patients (34.0%) required blood transfusion, and 4 patients (8.5%) required ICU admission. The average hospitalization was 5.2 days, with no re-admission within 30 days. The use of internal iliac balloons did not result in a difference in blood loss or operative time (P > 0.05). Patients with placenta percreta had significantly more blood loss (P = 0.02) and longer operative time (P = 0.007) compared with those with placenta accreta and increta.

CONCLUSION

The current surgical model for planned Caesarean hysterectomy for PAS exhibits a low complication rate. Further research is needed for developing a standardized approach to the management of PAS.

Placenta Accreta Spectrum

Placenta accreta spectrum, formerly known as morbidly adherent placenta, refers to the range of pathologic adherence of the placenta, including placenta increta, placenta percreta, and placenta accreta. The most favored hypothesis regarding the etiology of placenta accreta spectrum is that a defect of the endometrial-myometrial interface leads to a failure of normal decidualization in the area of a uterine scar, which allows abnormally deep placental anchoring villi and trophoblast infiltration. Maternal morbidity and mortality can occur because of severe and sometimes life-threatening hemorrhage, which often requires blood transfusion. Although ultrasound evaluation is important, the absence of ultrasound findings does not preclude a diagnosis of placenta accreta spectrum; thus, clinical risk factors remain equally important as predictors of placenta accreta spectrum by ultrasound findings. There are several risk factors for placenta accreta spectrum. The most common is a previous cesarean delivery, with the incidence of placenta accreta spectrum increasing with the number of prior cesarean deliveries. Antenatal diagnosis of placenta accreta spectrum is highly desirable because outcomes are optimized when delivery occurs at a level III or IV maternal care facility before the onset of labor or bleeding and with avoidance of placental disruption. The most generally accepted approach to placenta accreta spectrum is cesarean hysterectomy with the placenta left in situ after delivery of the fetus (attempts at placental removal are associated with significant risk of hemorrhage). Optimal management involves a standardized approach with a comprehensive multidisciplinary care team accustomed to management of placenta accreta spectrum. In addition, established infrastructure and strong nursing leadership accustomed to managing high-level postpartum hemorrhage should be in place, and access to a blood bank capable of employing massive transfusion protocols should help guide decisions about delivery location.

Retrospective analysis of 113 consecutive cases of placenta accreta spectrum from a single tertiary care center

Objective: Placenta accreta spectrum (PAS) remains a major cause of maternal morbidity. We sought to assess the characteristics and treatment outcomes of PAS managed at a tertiary care center with high volume of PAS.Study design: Electronic medical records of all patients with diagnosis of PAS from June 2010 to October 2016 were reviewed. Details of obstetric backgrounds, predelivery diagnosis, peripartum management, and outcomes were analyzed.Results: One hundred thirteen women with PAS were identified from 50,448 deliveries during the study period. Vaginal delivery, emergency, and elective cesarean section were accomplished in 41.6, 30.1, and 28.3%, respectively. There was no maternal mortality. Approximately 41.6% of women with PAS had peripartum hysterectomy. There was a fair inverse correlation between intraoperative blood loss and gestational weeks at delivery (r = -0.311; p=.001), but not gestational weeks at diagnosis (p = .249). Cases with predelivery diagnosis (n = 29) had higher intraoperative blood loss than those diagnosed postdelivery (n = 84) (p<.001). Anterior PAS (n = 58) is associated with attachment to previous uterine scar, antepartum bleeding, and intraoperative blood loss compared to posterior PAS (n = 44) (p<.05). The PAS patients with previous uterine surgery had the highest chance of peripartum hysterectomy (p<.001).Conclusions: Contradictory to previous reports, our data suggest a more severe spectrum of PAS in those with predelivery detection earlier gestational weeks at delivery. Peripartum hysterectomy was highest in anterior PAS that attached to the previous uterine scar.