Statistical evaluation of a fully automated mammographic breast density algorithm

Place of a new radiological index in predicting pulp exposure before intervention for deep carious lesions

BACKGROUND

During interventions for deep caries lesions without severe symptoms, preserving pulpal vitality is important to ensure treatment success, improve organ prognosis, and decrease cost-effectiveness. Current pre-operative radiographs allow visual estimation but not accurate measurement of lesion depth.

PURPOSE

Investigate the ability of ratio 'remaining/total dentin thickness' (RDT/TDT, as determined on pre-operative radiographs) to predict pulp exposure during excavation.

METHODS

This retrospective study (January 2018-June 2020) analyzed data on 360 patients. Four independent raters examined standard pre-operative radiographs and their contrasted versions. Lines put at the dentino-enamel junction, the floor of the carious lesion, and the pulp chamber wall allowed deriving RDT/TDT. Inter-rater agreements and concordance were assessed. A logistic regression accounting for measurement errors provided odds ratios that estimated the ability of the RDT/TDT to predict pulp exposure.

RESULTS

The median RDT/TDT ratio ranges were 16.8-26.5% on standard and 16.2-24.6% on contrasted radiographs. Inter-rater agreements on RDT/TDT were rather poor and inter-rater reliability was low and similar in standard and contrasted radiographs: the concordance correlation coefficients (95% CIs) were estimated at 0.46 (0.40; 0.51) and 0.46 (0.40; 0.52), respectively. The risk of pulp exposure increased by 2.5 times [odds ratio (95% CI) 2.57 (2.06; 3.20)] per 10-point decrease of the ratio on standard radiographs vs. 4.15 (3.15; 5.46) on contrasted radiographs.

CONCLUSION

RDT/TDT ratio is potentially helpful in predicting pulp exposure. However, the measurement errors on RDT and TDT being non-negligible and the interrater agreements poor, there is still place for advances through development of an automated process that will improve reliability and reproducibility of pulp exposure risk assessment.

CLINICAL TRIAL

Trial registration number. ClinicalTrials.gov NCT04607395, October 29, 2020.

Reliability of Computer-Assisted Breast Density Estimation: Comparison of Interactive Thresholding, Semiautomated, and Fully Automated Methods

OBJECTIVE

The purpose of this study was to investigate the reliability of computer-assisted methods of estimating breast density.

MATERIALS AND METHODS

Craniocaudal mammograms of 100 healthy subjects were collected from a screening mammography database. Three expert readers independently assessed mammographic breast density twice in a 1-month period using interactive thresholding and semiautomated methods. In addition, fully automated breast density estimation software was used to generate objective breast density estimates. The reliability of the computer-assisted breast density estimation was assessed in terms of concordance correlation coefficients, limits of agreement, systematic difference, and reader variability.

RESULTS

Statistically significant systematic bias (paired t test, p < 0.01) and variability (4.75-10.91) were found within and between readers for both the interactive thresholding and the semiautomated methods. Using the semiautomated method significantly reduced the within-reader bias of one reader (p < 0.02) and the between-reader variability of all three readers (p < 0.05). The breast density estimates obtained with the fully automated method had excellent agreement with those of the reference standard (concordance correlation coefficient, 0.93) without a significant systematic difference.

CONCLUSION

Reader-dependent variability and systematic bias exist in breast density estimates obtained with the interactive thresholding method, but they may be reduced in part by use of the semiautomated method. Assessing reader performance may be necessary for more reliable breast density estimation, especially for surveillance of breast density over time. The fully automated method has the potential to provide reliable breast density estimates nearly free from reader-dependent systematic bias and reader variability.

Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer

Background

Mammographic breast density and parenchymal patterns are well-established risk factors for breast cancer. We aimed to report inter-observer agreement on three different subjective ways of assessing mammographic density and parenchymal pattern, and secondarily to examine what potential impact reproducibility has on relative risk estimates of breast cancer.

Methods

This retrospective case–control study included 122 cases and 262 age- and time matched controls (765 breasts) based on a 2007 screening cohort of 14,736 women with negative screening mammograms from Bispebjerg Hospital, Copenhagen. Digitised randomized film-based mammograms were classified independently by two readers according to two radiological visual classifications (BI-RADS and Tabár) and a computerized interactive threshold technique measuring area-based percent mammographic density (denoted PMD). Kappa statistics, Intraclass Correlation Coefficient (ICC) (equivalent to weighted kappa), Pearson’s linear correlation coefficient and limits-of-agreement analysis were used to evaluate inter-observer agreement. High/low-risk agreement was also determined by defining the following categories as high-risk: BI-RADS’s D3 and D4, Tabár’s PIV and PV and the upper two quartiles (within density range) of PMD. The relative risk of breast cancer was estimated using logistic regression to calculate odds ratios (ORs) adjusted for age, which were compared between the two readers.

Results

Substantial inter-observer agreement was seen for BI-RADS and Tabár (κ=0.68 and 0.64) and agreement was almost perfect when ICC was calculated for the ordinal BI-RADS scale (ICC=0.88) and the continuous PMD measure (ICC=0.93). The two readers judged 5% (PMD), 10% (Tabár) and 13% (BI-RADS) of the women to different high/low-risk categories, respectively. Inter-reader variability showed different impact on the relative risk of breast cancer estimated by the two readers on a multiple-category scale, however, not on a high/low-risk scale. Tabár’s pattern IV demonstrated the highest ORs of all density patterns investigated.

Conclusions

Our study shows the Tabár classification has comparable inter-observer reproducibility with well tested density methods, and confirms the association between Tabár’s PIV and breast cancer. In spite of comparable high inter-observer agreement for all three methods, impact on ORs for breast cancer seems to differ according to the density scale used. Automated computerized techniques are needed to fully overcome the impact of subjectivity.