## 4 Discussion  
The main goal of the present study was to evaluate the best risk-stratification reporting system for sonoelastographic breast examination, in order to improve its diagnostic value, considering multiple algorithms of risk reassessment for 1405 solid breast nodules. The best outcomes for ultrasonography in the evaluation of solid breast nodules was proven to be the addition of elastography [14, 20, 34, 37]. It has been previously shown that elastography can improve the accuracy of classical ultrasonography by up to 26% [14]. There is still the need for improvement, especially in the BIRADS categories 3 and 4A, in order to properly differentiate malignant from benign lesions. BIRADS 4A lesions may be the group where elastography should play a decisive role when deciding between immediate biopsy and only regular follow-up [18, 38, 39]. In our study, both semiquantitative and qualitative methods proved to be significantly accurate (Acc, 94%) as can be seen in Table 7, with Se values of 79.56% and 55.15%, respectively, and Sp values of 95.20% and 95.56%; the results are found to be comparable to other studies where Se = 88%, Sp = 83% and Acc = 85% for the fat-to-lesion ratio, and Se = 86.5%, Sp = 89.8% and Acc = 88.3% for the elastography score values are described [14, 18]. The optimal FLR value from the data set (obtained by maximizing the sensitivity to false-positive differences) was 4.34 and can be seen in the following table (Table 9). This is comparable with the threshold of 4.88 from a previous study carried out in our endocrine unit [19]. Other studies found optimal FLR values from 2.24 to 5.6 [24, 25, 31, 39]. Figure 1: Receiver operating characteristic curves for proposed diagnostic methods. Although the initially considered threshold of FLR \(>=\) 4.5 is different from the resulting optimal value from the dataset, the diagnostic metrics shown in the table above are nearly identical. Both can be used with the same degree of confidence. Our study showed (Table 7) that the sensitivity, specificity and accuracy of classical ultrasound for the diagnosis of malignant lesions, using a BIRADS cut-off value of 4A, were 74.23%, 63.95% and 65%, respectively, and its positive and negative predictive values were 13.53% and 97.79%, respectively. Due to the low PPV, it cannot be used alone to rule out malignancy given the probability of false-negative results. As can be seen in Table 4, there were 19 malignancies out of 93 in BIRADS category 3 when assessing only by classical US alone. The BIRADS score downgraded according to EFSUMB proved to have better diagnostic quality compared to classical BIRADS, showing a 71.23% sensitivity, an 81.55% specificity and an accuracy of 81%. The PPV and NPV were 22.68% and 97.99%, respectively. While there was no significant difference in sensitivity after combining conventional US with elastography, the accuracy increased by 16% and the PPV was increased by 9.15%. The newly proposed risk-reassessment BIRADS TM showed an 81.23% sensitivity, 75.84% specificity, 77% accuracy, 20.35% PPV and 98.81% NPV. It has similar diagnostic value to EFSUMB BIRADS but with a 10% higher sensitivity. It appears that considering both upgrading and downgrading the conventional BIRADS is more advisable than downgrading alone. We also considered the worst-case scenario BIRADS score. The sensitivity, specificity and accuracy values for this assumption were 84.23%, 58.23% and 60%, respectively, while the PPV and NPV values were 13.29% and 98.84%, giving this assumption the best sensitivity but the poorest PPV of all the considered risk-stratification reporting systems. The \"worst-case scenario\" is the most conservative approach, with the highest sensitivity but also with the lowest specificity. Using this approach may lead to an increase in false-positive malignancy results and subsequent biopsy recommendations, which would be against the goal of this study with regards to lowering unnecessary biopsy rates.