Value of virtual touch tissue imaging quantification in diagnosing breast mass-type lesions and nonmass lesions: a comparative analysis

Introduction

Breast cancer is the most prevalent malignancy in women in the world, accounting for 11.7% of all cancers (1). Ultrasound is considered the first-line screening modality in many geographic regions due to it being cost-effective and accessible. In breast ultrasound, the image of nonmass lesions (NMLs) differ from that of mass-type lesions. NMLs appear as a structurally distorted hypoechoic area with an indistinct shape in two different projections but lacks a distinct outer boundary, which increases the difficulty of the examination. Moreover, conventional ultrasonography shows limited specificity in differentiating between benign and malignant NMLs, often leading to unnecessary biopsies in 60–70% of cases (2,3). Notably, 53.8–72.7% of NMLs are pathologically benign (4,5). The misdiagnosis of NMLs not only increases unnecessary biopsy and surgical intervention rates, imposing significant physical, psychological, and financial burdens on patients, but also leads to substantial healthcare resource waste. This underscores the critical need for more accurate noninvasive diagnostic techniques.

The development of shear wave elastography has increased diagnostic accuracy through the quantification of tissue stiffness through shear wave velocity (SWV) measurements (6). Compared to strain elastography, which is operator-dependent and provides only semiquantitative stiffness data, virtual touch tissue imaging quantification (VTIQ)—a second-generation shear wave elastography technique—offers operator-independent quantitative assessment (7,8). VTIQ can measure SWV directly, enabling objective quantification of tissue stiffness. This advantage can reduce operator dependence and provide comparable numerical results, offering a more intuitive and objective basis for determining the nature of lesions. The quantitative values obtained through shear wave elastography can reflect changes in the intrinsic physical properties of tissue sensitively. For instance, when tissue undergoes necrosis or liquefaction, SWV decreases significantly, directly quantifying the destruction of tissue structure (9). Given the unique value of shear wave elastography in providing quantitative tissue stiffness information, its application potential in the evaluation of breast diseases has garnered heightened attention. Although related studies have focused on mass-type lesions, studies on the diagnostic utility of VTIQ for NMLs are rare (10,11).

In this study, we analyzed the diagnostic value of the SWV in these two types of lesions by detecting the SWV in breast mass-type lesions and NMLs and comparing them. Our findings may promote the use of ultrasound in the diagnosis of breast diseases and serve as a framework for the diagnosis of breast diseases in clinic. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-623/rc).

Methods

Patient selection

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Ethics Committee of Affiliated Hospital of Jiangnan University (No. LS2024232). Informed consent was obtained from all individual participants.

This prospective study included 838 patients with breast lesions classified as Breast Imaging Reporting and Data System (BI-RADS) categories 4 or 5 based on ultrasonography. The patients were consecutively recruited from the Affiliated Hospital of Jiangnan University between January 2024 and February 2025. The inclusion criteria were as follows: (I) first detected breast lesions; (II) diagnosis via surgical pathology; and (III) complete ultrasonography and clinical data. The exclusion criteria were as follows: (I) administration of neoadjuvant chemotherapy; (II) no pathological results or diagnosis confirmed by puncture pathology; and (III) lesions with gross calcification (as gross calcification can block shear wave propagation, cause acoustic shadowing, or produce artificially high stiffness values) or cystic lesions affecting the measurement of VTIQ and precluding the accurate assessment of SWV accurately.

Imaging evaluation

An ACUSON S3000 color Doppler ultrasonography machine (Siemens Healthineers, Erlangen, Germany), equipped with VTIQ software, with a linear array probe at a probe frequency of 7.5–12 MHz, was used for scans in this study. For scans, patients were placed in the supine position with their arms raised to fully expose the breast and axilla, and routine ultrasonography was performed in the breast scanning mode. The size, morphology, orientation, internal echoes, and posterior features of the lesion were observed and recorded as described by the fifth edition of BI-RADS (12). The region of interest was adjusted without the application of pressure, and the lesion was placed in the center of the region of interest, with largest possible area of the lesion being covered. Patients were asked to hold their breath, the VTIQ quality mode map was acquired, and the velocity mode was switched when the image had a uniform green or light blue background and if red or yellow areas appeared inside the lesion. The velocity mode map was acquired, calcified foci and liquefied necrotic areas were avoided, the sampling frame on the part of the image that showed a higher velocity (i.e., the inside of the lesion) was placed, the effective measurement range was adjusted, and the best measurement range was considered when the normal breast tissue around the lesion had a uniform light green or light blue background and if red or yellow areas appeared inside the lesion (Figure 1). The SWV inside the lesion was measured five times, and the average value was recorded. All breast lesions were scanned by one sonographer with more than 10 years of experience and evaluated by two sonographers with more than 10 years of experience. The results were reviewed by a chief physician if there were discrepancies in interpretation.

Figure 1 Diagram of SWV measurement. The arrow shows areas of liquefied necrosis. SWV, shear wave velocity.

Statistical analysis

Statistical analysis was performed via SPSS 26.0 (IBM Corp., Armonk, NY, USA) and MedCalc 19.3.1 (MedCalc Software, Ostend, Belgium) statistical software. Continuous variables that conformed to a normal distribution are expressed as the mean ± standard deviation and were analyzed via the independent samples t-test. Continuous variables that did not conform to a normal distribution are expressed as medians and quartiles and were analyzed via the Mann-Whitney test. Categorical variables are expressed as frequencies (%) and were analyzed with the χ² test or the Fisher exact test. With the pathological results serving as the gold standard, the receiver operating characteristic curve (ROC) was plotted, and the area under the curve (AUC) was calculated for each group. ROC curves visualized the tradeoff relationship between sensitivity and specificity, determined cutoff values, and evaluated diagnostic performance (quantified by AUC). The AUC had a value between 0.5 and 1; the closer the value was to 1, the better the diagnostic performance of the index/model and the higher the accuracy. AUC values were interpreted according to the following scheme: an AUC of 0.5 indicated no diagnostic efficacy and that the model has no clinical value; an AUC >0.5 and ≤0.7 indicated low diagnostic efficacy and that the model should be used with caution for clinical decision making; an AUC >0.7 but ≤0.9 indicated the moderate diagnostic efficacy and reliable reference value of the model; and AUC >0.9 and <1.0 indicated excellent diagnostic efficacy and that the model can independently support critical clinical decision making, with a low rate of missed diagnosis or misdiagnosis; and an AUC =1.0 indicated complete accuracy and perfect discrimination between target states (ideal state, almost nonexistent in reality). The optimal cutoff value was selected according to the maximal Youden index. All results were considered to be statistically significant at P<0.05 (13).

Results

Pathological results

Based on the inclusion and exclusion criteria, 761 breast lesions were included in this study; all breast lesions were single. Among these lesions, 433 cases were mass-type lesions and 328 cases were NMLs. According to the pathologic types of breast tumors prescribed by the fifth edition of the World Health Organization (WHO) guidelines in 2019, there were 190 malignant cases, accounting for 43.88% of the breast mass-type lesions, and 243 benign cases, accounting for 56.12% (14). Among the NMLs, there were 131 malignant cases, accounting for 39.94% of NMLs, and 197 benign cases, accounting for 60.06% (Table 1). The distributions of benign and malignant mass-type lesions and NMLs were not significantly different (P=0.276).

Comparative analysis of clinical baseline data and conventional ultrasound characteristics

In the comparison of clinical baseline and conventional ultrasound characteristics between patients with breast mass-type lesions and those with NMLs, no significant difference was found for age distribution (P=0.687); however, there were significant differences (all P values <0.05) for several multiple sonographic parameters, including maximum diameter, shape, orientation, margin characteristics, internal echogenicity, posterior acoustic features, calcification patterns, and vascularity distribution. These findings suggest that mass-type lesions and NMLs have distinct sonographic profiles (Table 2).

ROC curve of VTIQ for diagnosing mass lesions and NMLs

In both malignant breast mass-type lesions and NMLs, the SWV values were significantly greater than those of benign lesions (all P values <0.001); representative ultrasound images are provided in Figure 2. ROC curves were constructed based on SWV measurements derived from VTIQ and corresponding pathological outcomes (Figure 3). The results of the analysis revealed that for breast mass-type lesions, VTIQ yielded an AUC of 0.807 [95% confidence interval (CI): 0.767–0.843], with an optimal SWV cutoff value of 3.39 m/s. In contrast, for NML cases, VTIQ achieved greater diagnostic performance, with an AUC of 0.886 (95% CI: 0.846–0.918), and the optimal SWV cutoff value was found to be 3.52 m/s.

Figure 2 Ultrasound images and VTIQ images of mass-type lesions and NMLs. (A) Ultrasound image of a benign mass-type lesion. (B) VTIQ image of a benign mass-type lesion. (C) Ultrasound image of a malignant mass-type lesion. (D) VTIQ image of a malignant mass-type lesion. (E) Ultrasound image of a benign NML. (F) VTIQ image of a benign NML. (G) Ultrasound image of a malignant NML. (H) VTIQ image of a malignant NML. NML, nonmass lesion; VTIQ, virtual touch tissue imaging quantification.

Figure 3 The receiver operating curve for SWV diagnosis of (A) mass-type lesions and (B) NMLs. AUC, area under the curve; NMLs, nonmass lesions; SWV, shear wave velocity.

Efficacy of VTIQ in distinguishing between breast mass lesions and NMLs

For mass-type lesions, VTIQ exhibited a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 68.42%, 85.19%, 78.31%, 77.53%, and 77.83%, respectively; meanwhile, for NMLs, these values were 79.39%, 86.80%, 80.00%, 86.40%, and 83.80%, respectively. The sensitivity, negative predictive value, and accuracy of VTIQ for diagnosing mass-type lesions were significantly lower than those of NMLs (all P values <0.05). The detailed results are presented in Table 3 and indicate that VTIQ has a low missed diagnosis rate, high reliability of negative results, and high overall diagnostic accuracy in the evaluation of NMLs compared with mass-type lesions.

Discussion

As a relatively novel breast imaging modality, VTIQ allows for the quantitative assessment of shear wave elasticity in breast lesions, thus providing valuable supplementary diagnostic information (15). Previous studies have applied elastography techniques to breast examinations, demonstrating their potential to significantly enhance the diagnostic accuracy of breast malignancies (16,17). However, no systematic investigation of the stratification of breast lesions into mass-type lesions and NMLs has been conducted. Our findings suggest that VTIQ has diagnostic utility for both mass-type lesions and NMLs, with the diagnostic efficacy for NMLs being superior. Specifically, the technology showed enhanced discriminatory performance in the characterization of NMLs, suggesting its clinical relevance for differentiation across different lesion subtypes.

Our study included 761 patients with breast lesions, including 433 patients with mass-type lesions and 328 patients with NMLs. The SWV of both malignant mass-type lesions and NMLs was greater than that of the corresponding benign lesions. Some studies have reported significant proliferation of collagen fibers in malignant breast lesion tissue, which causes the malignant lesion tissue to be considerably harder than the tissue of benign lesions (18). As shear waves propagate faster in harder tissue, the SWV of malignant lesions is significantly greater than that of benign lesions, and our findings are in line with this (19). By constructing ROC curves, we found that the AUCs for VTIQ in diagnosing breast mass-type lesions and NMLs were 0.807 (95% CI: 0.767–0.843) and 0.886 (95% CI: 0.846–0.918), respectively, while the optimal cutoff values were 3.39 and 3.52 m/s, respectively. The AUC and SWV of mass-type lesions were both lower than those of NMLs. From a pathological perspective, adenosis is the most common type of benign NLMs, with a significantly higher incidence rate than fibroadenoma, inflammation, atypical ductal hyperplasia, and intraductal papilloma (20,21). In contrast, most benign mass-type lesions are fibroadenomas. The following is a list of various breast diseases and breast tissues ranked from highest to lowest according to SWV: invasive ductal carcinoma, ductal carcinoma in situ, adenosis, intraductal papilloma, fibroadenoma, glandular tissue, and fat (22). The SWV of adenosis lesions is greater than that of fibroadenoma lesions, and the SWV of NMLs is also greater than that of mass-type lesions, which is why the optimal cutoff values of the SWV for mass-type lesions and NMLs were different in our study. The results of the comparative analysis of the ultrasound characteristics of the breast lesions showed that the incidence rates of irregular shapes, ill-defined margins, and microcalcifications in the ultrasound features of malignant NMLs were greater than those of mass-type lesions, all of which increase the hardness of malignant NMLs to some extent (23,24). The irregular shape and ill-defined margins also somewhat reflect the invasiveness of the tumor: the greater the degree of invasion into surrounding tissues, the greater the hardness (25). During their growth, malignant breast lesions, after breaking through the basement membrane and infiltrating into the stromal tissue to differing degrees, present with spiculated or crab-claw-like patterns. This process, coupled with the effect of the immune mechanism of the body, causes the internal tissue components and structures of the tumor to become disordered, with fibrous tissue hyperplasia, tumor cell proliferation, and angiogenesis forming an irregular, ill-defined mixed infiltration zone, which increases the hardness of the tumor and surrounding tissues (26). Moreover, microcalcification also significantly increases the hardness of NMLs. In this study, the maximum diameter of breast NMLs was greater than that of the mass-type lesions. A few studies have reported that tumor size is positively correlated with the SWV: the larger the tumor is, the greater the degree of invasion into surrounding tissues and the greater the hardness. This which increases the hardness of malignant NMLs to some extent (27,28).

Furthermore, the sensitivity, negative predictive value, and accuracy of VTIQ for mass-type lesions were lower than those for NMLs, a finding which may diverge from other studies. For instance, Sravani et al. reported that when the optimal cutoff value of the SWV was 3.43 m/s, the sensitivity and specificity of VTIQ technology in diagnosing breast lesions was 87.1% and 90%, respectively (29). Gürüf et al. found that when the optimal cutoff value of the SWV was 3.41 m/s, the sensitivity and specificity of VTIQ technology in diagnosing breast lesions was 88.1% and 86.7%, respectively (10). These discrepancies may be due to the fact that 75.26% of the malignant mass-type lesions in our study were invasive ductal carcinomas. Early invasive ductal carcinomas have fewer fibrous components, resulting in lower hardness and thus increasing the possibility of false-negative outcomes. Some invasive ductal carcinomas often undergo liquefaction and necrosis, which can also reduce the hardness of the mass. Certain pathological types (such as mucinous carcinoma) have lower hardness, which can also lead to false negatives. One study reported that the accuracy and specificity of conventional ultrasound for detecting breast NMLs are 61.2% and 56.1%, respectively, which are significantly lower than the diagnostic accuracy rates of conventional ultrasound for detecting breast mass-type lesions (30). However, the results of our study showed that VTIQ can significantly improve the diagnostic efficacy of ultrasound for NMLs. Due to conventional ultrasound being limited in its ability to accurately diagnose NMLs, biopsy is considered the main choice for diagnosis. For some NMLs, SWV can provide an important basis for differentiating their benignity and malignancy, thus reducing unnecessary biopsies.

This study involved certain limitations that should be addressed. To begin, due to the lack of clear boundaries of NMLs on conventional ultrasound, the determination of whether the measurement of the SWV exceeds the scope of the lesion is subjective to some extent. Moreover, unlike mass-type lesions, NMLs consists of normal breast tissue and lesion tissue, which could decrease the SWV of NMLs to some degree (31). Finally, the sample size was small and the cutoff values obtained in this study may not be applicable to other users.

Conclusions

This study demonstrated the value of SWV in the diagnosis of breast mass-type lesions and NMLs, providing strong support for its ability to diagnose and differentially diagnose of breast diseases. Especially for NMLs, given the difficulty of conventional ultrasound diagnosis, VTIQ significantly reduces misdiagnosis and missed diagnosis of NMLs and increases diagnostic accuracy, which largely reduces the occurrence of invasive tests (including puncture biopsy and surgery). With the refinement of the sixth edition of the BI-RADS guidelines and the use of multimodal ultrasound, VTIQ has the potential to become an integral part of the diagnostic and therapeutic system for NMLs.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-623/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-623/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-623/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Affiliated Hospital of Jiangnan University (No. LS2024232) and informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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