Temporal and external validation of the algorithm predicting first trimester outcome of a viable pregnancy.

BACKGROUND: Symptoms like vaginal bleeding or abdominal pain in early pregnancy can create anxiety about potential miscarriage. Previous studies have demonstrated ultrasonographic variables at the first trimester transvaginal scan (TVS) which can assist in predicting outcomes by 12 weeks gestation. AIM: To validate the miscarriage risk prediction model (MRP) in women who present with a viable intrauterine pregnancy (IUP) at the primary ultrasound. MATERIALS AND METHODS: A multi-centre diagnostic study of 1490 patients was performed between 2011 and 2019 for retrospective external and 2017-2019 for prospective temporal validation. The reference standard was a viable pregnancy at 12 + 6 weeks. The MRP model is a multinomial logistic regression model based on maternal age, embryonic heart rate, logarithm (gestational sac volume/crown-rump length (CRL)) ratio, CRL and presence or absence of clots. RESULTS: Temporal validation data from 290 viable IUPs were collected: 225 were viable at the end of the first trimester, 31 had miscarried and 34 were lost to follow-up. External validation data from 1203 viable IUPs were collected at two other ultrasound units: 1062 were viable, 69 had miscarried and 72 were lost to follow-up. Temporal validation with a cut-off of 0.1 demonstrated: area under the curve (AUC) of 0.8 (0.7-0.9), sensitivity 66.7%, specificity 83.9%, positive predictive value (PPV) 35.7%, negative predictive value (NPV) 94.9%, positive likelihood ration (LR+) 4.1 and negative LR (LR-) 0.4. External validation demonstrated: AUC 0.7 (0.7-0.8), sensitivity 44.9%, specificity 90.4%, PPV 23.3%, NPV 96.2%, LR+ 4.6 and LR- 0.6 (0.4-0.7). CONCLUSION: The MRP model is not able to be used in real time for counselling, and management should be individualised.

Pre-operative classification of molar pregnancy: How good is ultrasound?

BACKGROUND: Histopathology is the reference standard for diagnosing hydatidiform molar pregnancy (HMP). AIM: To assess the performance of pre-operative transvaginal ultrasound (TVS) to predict HMP. MATERIALS AND METHODS: A retrospective diagnostic accuracy study was performed on women who had both TVS and histopathological examination of uterine curettings between January 2011-February 2017. TVS diagnosis of partial MP (PMP) included assessment of fetal parts and/or empty gestational sac with small cystic spaces adjacent to gestational sac. TVS diagnosis of complete MP (CMP) included assessment of complex, echogenic intra-uterine mass(es) containing multiple small cystic areas. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive and negative likelihood ratios (PLR/NLR) for TVS were reported. Reference standard was histology. RESULTS: There were 4917 consecutive women who underwent TVS; 1636 underwent surgical curettage for miscarriage. Forty out of 4917 (0.6%) had HMP histologically; 25/40 (62.5%) had suspected HMP and 15/40 (37.5%) did not; 24/40 (60.0%) had CMP of which 19/24 (79.1%) were suspected on TVS and 5/24 (20.8%) were not; 16/40 (40.0%) had PMP of which 6/16 (37.5%) were suspected on TVS and 10/16 (62.6%) were not. The sensitivity, specificity, PPV, NPV, PLR and NLR of pre-operative TVS to predict HMP were: 60.0, 99.1, 63.2, 99.0% 68.4, 0.4; for CMP: 79.2, 99.8, 86.3, 99.6%, 421.7, 0.2; for PMP: 37.5, 99.3, 35.3, 99.4%, 54.3, 0.6. CONCLUSION: Histology remains the gold standard for diagnosing HMP. TVS is an acceptable diagnostic tool for HMP. When there are no ultrasound features of HMP, almost all these women will not have an underlying HMP.

Preoperative diagnosis of atypical pelvic leiomyoma and sarcoma: the potential role of diffusion-weighted imaging.

The objective of our study was to determine the utility of diffusion-weighted magnetic resonance (DWMR) to differentiate the atypical uterine leiomyomas and sarcomas, establishing a cut-off value of the apparent diffusion coefficient (ADC) to rule out the malignancy. We performed a diagnostic accuracy retrospective study including 10 patients with pelvic sarcomas and 17 patients with leiomyomas. Atypical morphological features in magnetic resonance (MR) studies occurred in 58.8% of the patients, leading to a significant number of indeterminate diagnoses. In contrast, ADC values were consistent for leiomyomas, sarcomas, primary tumours, recurrences, intrauterine and in the extrauterine pelvic locations. The ADC cut-off value was set in 1 (×10-3 mm2/s). Thus, the ADC values equal or superior to 1 × 10-3 mm2/s were always associated with a leiomyoma. The structural MR accuracy was 66.7%, reaching 100% when using DWMR with dichotomised ADC values. Diffusion-weighted imaging with the quantitative measurement of ADC may be considered a useful preoperative test for the differentiation of atypical leiomyomas from sarcomas. Impact statement What is already known on this subject? Papers reporting the utility of a diffusion-weighted MR for the diagnosis of uterine sarcomas are scarce and consist of a small series. However, the published results are consistent with our study, with the decreased ADCs in the case of malignancy. What do the results of this study add? The main differential characteristic of our study is that we selected only the atypical leiomyomas: they share sonographic and MR features with sarcomas, which often leads to an inaccurate diagnosis. This is also the first paper reporting on the role of DWMR with ADC for these types of tumours in extrauterine pelvic locations. We demonstrated a consistent relationship between dichotomised ADC values in leiomyomas/sarcomas for these particular cases and in recurrent tumours, with no overlap between both the groups, as a difference with the previous reports. What are the implications of these findings for clinical practice and/or further research? Our study can be considered as a proof of concept supporting DWMR with ADC measurement as a useful tool to enhance the diagnostic accuracy of MR, highlighting its value to rule out malignancy. Hence, DWMR seems to be a potential useful test to include in the preoperative evaluation of clinically atypical uterine tumours.

Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study.

OBJECTIVES: To assess interobserver reproducibility in detecting tubal ectopic pregnancies by reading data sets from 3-dimensional (3D) transvaginal ultrasonography (TVUS) and comparing it with real-time 2-dimensional (2D) TVUS. METHODS: Images were initially classified as showing pregnancies of unknown location or tubal ectopic pregnancies on real time 2D TVUS by an experienced sonologist, who acquired 5 3D volumes. Data sets were analyzed offline by 5 observers who had to classify each case as ectopic pregnancy or pregnancy of unknown location. The interobserver reproducibility was evaluated by the Fleiss κ statistic. The performance of each observer in predicting ectopic pregnancies was compared to that of the experienced sonologist. Women were followed until they were reclassified as follows: (1) failed pregnancy of unknown location; (2) intrauterine pregnancy; (3) ectopic pregnancy; or (4) persistent pregnancy of unknown location. RESULTS: Sixty-one women were included. The agreement between reading offline 3D data sets and the first real-time 2D TVUS was very good (80%-82%; κ = 0.89). The overall interobserver agreement among observers reading offline 3D data sets was moderate (κ = 0.52). The diagnostic performance of experienced observers reading offline 3D data sets had accuracy of 78.3% to 85.0%, sensitivity of 66.7% to 81.3%, specificity of 79.5% to 88.4%, positive predictive value of 57.1% to 72.2%, and negative predictive value of 87.5% to 91.3%, compared to the experienced sonologist's real-time 2D TVUS: accuracy of 94.5%, sensitivity of 94.4%, specificity of 94.5%, positive predictive value of 85.0%, and negative predictive value of 98.1%. CONCLUSIONS: The diagnostic accuracy of 3D TVUS by reading offline data sets for predicting ectopic pregnancies is dependent on experience. Reading only static 3D data sets without clinical information does not match the diagnostic performance of real time 2D TVUS combined with clinical information obtained during the scan.