Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients with Adnexal Masses

Doppler ultrasonographic evaluation of tissue revascularization following connective tissue graft at implant sites

AIM

To assess the Doppler ultrasonographic tissue perfusion at dental implant sites augmented with connective tissue graft (CTG) using coronally advanced flap (CAF) or tunnel technique (TUN).

MATERIALS AND METHODS

Twenty-eight patients presenting with isolated healthy peri-implant soft-tissue dehiscence (PSTD) were included in this randomized clinical trial. PSTDs were treated with either CAF + CTG or TUN + CTG. Ultrasound scans were taken at baseline, 1 week, 1 month, 6 months and 12 months. Tissue perfusion at the mid-facial, mesial and distal aspects of the implant sites was assessed by colour Doppler velocity (CDV) and power Doppler imaging (PDI). Early vascularization of the graft and the flap at 1 week and at 1 month were evaluated via dynamic tissue perfusion measurements (DTPMs), including flow intensity (FI), mean perfusion relief intensity (pRI) and mean perfused area (pA).

RESULTS

Regression analysis did not reveal significant differences in terms of mid-facial CDV and PDI changes between CAF and TUN over 12 months (p > .05), while significant differences between the two groups were observed at the interproximal areas (p < .001 for both CDV and PDI changes). Higher early DTPMs were observed at the TUN-treated sites in terms of mean FI of the graft (p = .027) and mean FI (p = .024) and pRI of the flap (p = .031) compared with CAF-treated sites at 1 week. Assessment of the FI direction showed that CTG perfusion at 1 week and at 1 month mainly occurred from the flap towards the implant/bone. Early tissue perfusion outcomes were found to be associated with the 12-month mean PSTD coverage and mucosal thickness gain.

CONCLUSIONS

Doppler ultrasonography shows tissue perfusion changes occurring at implant sites augmented with CTG. The main differences in tissue perfusion between CAF and TUN were observed at the interproximal sites, with early perfusion associated with clinical and volumetric outcomes at 12 months.

ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies

Objectives

To conduct a systematic review of studies externally validating the ADNEX (Assessment of Different Neoplasias in the adnexa) model for diagnosis of ovarian cancer and to present a meta-analysis of its performance.

Design

Systematic review and meta-analysis of external validation studies.

Data sources

Medline, Embase, Web of Science, Scopus, and Europe PMC, from 15 October 2014 to 15 May 2023.

Eligibility criteria for selecting studies

All external validation studies of the performance of ADNEX, with any study design and any study population of patients with an adnexal mass. Two independent reviewers extracted the data. Disagreements were resolved by discussion. Reporting quality of the studies was scored with the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) reporting guideline, and methodological conduct and risk of bias with PROBAST (Prediction model Risk Of Bias Assessment Tool). Random effects meta-analysis of the area under the receiver operating characteristic curve (AUC), sensitivity and specificity at the 10% risk of malignancy threshold, and net benefit and relative utility at the 10% risk of malignancy threshold were performed.

Results

47 studies (17 007 tumours) were included, with a median study sample size of 261 (range 24-4905). On average, 61% of TRIPOD items were reported. Handling of missing data, justification of sample size, and model calibration were rarely described. 91% of validations were at high risk of bias, mainly because of the unexplained exclusion of incomplete cases, small sample size, or no assessment of calibration. The summary AUC to distinguish benign from malignant tumours in patients who underwent surgery was 0.93 (95% confidence interval 0.92 to 0.94, 95% prediction interval 0.85 to 0.98) for ADNEX with the serum biomarker, cancer antigen 125 (CA125), as a predictor (9202 tumours, 43 centres, 18 countries, and 21 studies) and 0.93 (95% confidence interval 0.91 to 0.94, 95% prediction interval 0.85 to 0.98) for ADNEX without CA125 (6309 tumours, 31 centres, 13 countries, and 12 studies). The estimated probability that the model has use clinically in a new centre was 95% (with CA125) and 91% (without CA125). When restricting analysis to studies with a low risk of bias, summary AUC values were 0.93 (with CA125) and 0.91 (without CA125), and estimated probabilities that the model has use clinically were 89% (with CA125) and 87% (without CA125).

Conclusions

The results of the meta-analysis indicated that ADNEX performed well in distinguishing between benign and malignant tumours in populations from different countries and settings, regardless of whether the serum biomarker, CA125, was used as a predictor. A key limitation was that calibration was rarely assessed.

Systematic review registration

PROSPERO CRD42022373182.