Shear-wave elastography improves the specificity of breast US: the BE1 multinational study of 939 masses

Estimating the viscoelastic anisotropy of human skin through high-frequency ultrasound elastography

BACKGROUND

The skin is the largest organ of the human body and serves distinct functions in protecting the body. The viscoelastic properties of the skin play a key role in supporting the skin-healing process, also it may be changed due to some skin diseases.

PROPOSE

In this study, high-frequency ultrasound (HFUS) elastography based on a Lamb wave model was used to noninvasively assess the viscoelastic anisotropy of human skin.

METHOD

Elastic waves were generated through an external vibrator, and the wave propagation velocity was measured through 40 MHz ultrafast HFUS imaging. Through the use of a thin-layer gelatin phantom, HFUS elastography was verified to produce highly accurate estimates of elasticity and viscosity. In a human study involving five volunteers, viscoelastic anisotropy was assessed by rotating an ultrasound transducer 360°.

RESULTS

An oval-shaped pattern in the elasticity of human forearm skin was identified, indicating the high elastic anisotropy of skin; the average elastic moduli were 24.90 ± 6.63 and 13.64 ± 2.67 kPa along and across the collagen fiber orientation, respectively. The average viscosity of all the recruited volunteers was 3.23 ± 0.93 Pa·s.

CONCLUSIONS

Although the examined skin exhibited elastic anisotropy, no evident viscosity anisotropy was observed.

Prediction of disease-free survival using strain elastography and diffuse optical tomography in patients with T1 breast cancer: a 10-year follow-up study

BACKGROUND

Early-stage breast cancer (BC) presents a certain risk of recurrence, leading to variable prognoses and complicating individualized management. Yet, preoperative noninvasive tools for accurate prediction of disease-free survival (DFS) are lacking. This study assessed the potential of strain elastography (SE) and diffuse optical tomography (DOT) for non-invasive preoperative prediction of recurrence in T1 BC and developed a prediction model for estimating the probability of DFS.

METHODS

A total of 565 eligible patients with T1 invasive BC were enrolled prospectively and followed to investigate the recurrence. The associations between imaging features and DFS were evaluated and a best-prediction model for DFS was developed and validated.

RESULTS

During the median follow-up period of 10.8 years, 77 patients (13.6%) developed recurrences. The fully adjusted Cox proportional hazards model showed a significant trend between an increasing strain ratio (SR) (P < 0.001 for trend) and the total hemoglobin concentration (TTHC) (P = 0.001 for trend) and DFS. In the subgroup analysis, an intensified association between SR and DFS was observed among women who were progesterone receptor (PR)-positive, lower Ki-67 expression, HER2 negative, and without adjuvant chemotherapy and without Herceptin treatment (all P < 0.05 for interaction). Significant interactions between TTHC status and the lymphovascular invasion, estrogen receptor (ER) status, PR status, HER2 status, and Herceptin treatment were found for DFS(P < 0.05).The imaging-clinical combined model (TTHC + SR + clinicopathological variables) proved to be the best prediction model (AUC = 0.829, 95% CI = 0.786-0.872) and was identified as a potential risk stratification tool to discriminate the risk probability of recurrence.

CONCLUSION

The combined imaging-clinical model we developed outperformed traditional clinical prognostic indicators, providing a non-invasive, reliable tool for preoperative DFS risk stratification and personalized therapeutic strategies in T1 BC. These findings underscore the importance of integrating advanced imaging techniques into clinical practice and offer support for future research to validate and expand on these predictive methodologies.

Usefulness of color Doppler and strain elastography adjunctive to B-mode ultrasonography in the diagnosis of non-mass abnormalities of the breast: results of the BC-07 multicenter study of 385 cases

PURPOSE

The concept of non-mass abnormalities of the breast has been employed in Japan for approximately 20 years. Although B-mode findings are classified as non-mass abnormalities, the usefulness of adding color Doppler ultrasonography (US) and strain elastography to B-mode US is unclear. Therefore, we conducted a multicenter study (JABTS BC-07) to establish the diagnostic criteria for breast US, including color Doppler and elastography, for non-mass abnormalities of the breast and verify their diagnostic usefulness.

METHODS

We registered US images of non-mass abnormalities of the breast and their clinical and histopathological data from 13 institutions (202 malignant and 183 benign non-mass lesions). Furthermore, we evaluated the centralized image interpretation usefulness of the diagnostic criteria for B-mode and color Doppler US, as well as the sensitivity and specificity when color Doppler US and elastography were added to B-mode US.

RESULTS

Echogenic foci in the mammary gland (odds ratio 3.45, 95% confidence interval [CI] 1.92-6.19, p < 0.0001) and the configuration of internal solid components of the ducts (odds ratio 0.056, 95% CI 0.005-0.591, p < 0.0165) significantly differentiated benign and malignant non-mass abnormalities. The sensitivity of B-mode alone (83.7%) was significantly improved by adding color Doppler US (93.1%) (p = 0.0004); however, adding color Doppler US and elastography to B-mode US made no significant difference in either sensitivity or specificity.

CONCLUSION

Although adding color Doppler US and elastography to B-mode US improved sensitivity, the diagnostic significance was limited. Therefore, a comprehensive diagnostic method comprising mammography and magnetic resonance imaging is warranted.

Breast multiparametric ultrasound: a single-center experience

PURPOSE

To evaluate the role of multiparametric ultrasound (mpUS) in the characterization of focal breast lesions (FBLs).

METHODS

This prospective study enrolled patients undergoing multiparametric breast ultrasound for FBLs. An experienced breast radiologist evaluated the following ultrasound features: US BI-RADS category, vascularization pattern (internal, vessels in rim and combined) and presence of penetrating vessels with each Doppler method (Color-Doppler, Power-Doppler, Microvascular imaging), strain ratio (SR) and Tsukuba score (TS) with Strain Elastography (SE), Emax, Emean, Emin and Eratio with 2D-shear wave elastography (2D-SWE). Core biopsy for all BI-RADS 4-5 FBLs and 24-month follow-up for all BI-RADS 2-3 FBLs were considered for standard of reference. The diagnostic performance was assessed with the area under curve (AUCs) and cut-off values were determined according to the Youden's index.

RESULTS

A total of 139 FBLs were included with 75/139 (53.9%) benign and 64/139 (46.1%) malignant FBLs. Internal vascularization patterns (p < 0.001), penetrating vessels (p < 0.001), TS 4-5 (p < 0.001) and all 2D-SWE parameters (p < 0.001) were significantly different between benign and malignant FBLs. The BI-RADS score provided an AUC of 0.876 (95% CI 0.810-0.926) for the diagnosis of malignant FBLs. Among the 2D-SWE measurements, an excellent diagnostic performance was observed for Emax with an AUC of 0.915 (95% CI 0.856-0.956) and Emean of 0.908 (95% CI 0.847-0.951). Optimal cutoff for the diagnosis of malignant FBLs were US BI-RADS > 3, Strain Ratio > 2.52, Tsukuba Score > 3, Emax > 82.6 kPa, Emean > 66.0 kPa, Emin > 54.4 kPa and Eratio > 330.8. Multiparametric ultrasound, particularly SWE, can improve specificity in the characterization of FBLs.

Shear-Wave Elastography Gradient Analysis of Newly Diagnosed Breast Tumours: A Critical Analysis

BACKGROUND

A better understanding of the peritumoral stroma changes due to tumour invasion using non-invasive diagnostic methods may improve the differentiation between benign and malignant breast lesions. This study aimed to assess the correlation between breast lesion differentiation and intra- and peritumoral shear-wave elastography (SWE) gradients.

METHODS

A total of 135 patients with newly diagnosed breast lesions were included. Intratumoral, subsurface, and three consecutive peritumoral SWE value measurements (with three repetitions) were performed. Intratumoral, interface, and peritumoral gradients (Gradient 1 and Gradient 2) were calculated using averaged SWE values. Statistical analysis included descriptive statistics and an ordinary one-way ANOVA to compare overall and individual gradients among Breast Imaging-Reporting and Data System (BI-RADS) 2, 3, and 5 groups.

RESULTS

Malignant tumours showed higher average SWE velocity values at the tumour centre (BI-RADS 2/3: 4.1 ± 1.8 m/s vs. BI-RADS 5: 4.9 ± 2.0 m/s, p = 0.04) and the first peritumoral area (BI-RADS 2/3: 3.4 ± 1.8 m/s vs. BI-RADS 5: 4.3 ± 1.8 m/s, p = 0.003). No significant difference was found between intratumoral gradients (0.03 ± 0.32 m/s vs. 0.0 ± 0.28 m/s; p > 0.999) or gradients across the tumour-tissue interface (-0.17 ± 0.18 m/s vs. -0.13 ± 0.35 m/s; p = 0.202). However, the first peritumoral gradient (-0.16 ± 0.24 m/s vs. -0.35 ± 0.31 m/s; p < 0.0001) and the second peritumoral gradient (-0.11 ± 0.18 m/s vs. -0.22 ± 0.28 m/s; p = 0.037) were significantly steeper in malignant tumours. The AUC was best for PTG1 (0.7358) and PTG2 (0.7039). A threshold value for peritumoral SWI PT1 above 3.76 m/s and for PTG1 below -0.238 m/s·mm-1 indicated malignancy in 90.6% of cases.

CONCLUSIONS

Evaluating the peritumoral SWE gradient may improve the diagnostic pre-test probability, as malignant tumours showed a significantly steeper curve of the elasticity values in the peritumoral stroma compared to the linear regression with a relatively flat curve of benign lesions.

Ultrasonographic Assessment of Tissue Stiffness: Recent Progress in Transient Elastography and Shear Wave Elastography in the Liver and Various Organs

Ultrasonography is a noninvasive and widely accessible modality in clinical practice. Recently, ultrasonography has been used to evaluate tissue stiffness; the two representative techniques are transient elastography (FibroScan®) and shear wave elastography. These modalities are now generally used for the assessment of liver fibrosis, the prediction of hepatocarcinogenesis, and determining prognosis. In addition, shear wave elastography is available, not only for the liver but also for various other organs, including the breast and brain. In the breast and brain, shear wave elastography distinguishes malignant lesions from benign ones. Moreover, shear wave elastography can be useful for differentiating between ischemic and hemorrhagic strokes. This review summarizes the recent progress in transient elastography and shear wave elastography of the liver and introduces the advantages of ultrasonographic assessment of tissue stiffness in various organs, including the breast, brain, kidney, heart, thyroid, pancreas, muscle, and bone.

Shear wave elastography to assess stiffness of the human ovary and other reproductive tissues across the reproductive lifespan in health and disease†

The ovary is one of the first organs to show overt signs of aging in the human body, and ovarian aging is associated with a loss of gamete quality and quantity. The age-dependent decline in ovarian function contributes to infertility and an altered endocrine milieu, which has ramifications for overall health. The aging ovarian microenvironment becomes fibro-inflammatory and stiff with age, and this has implications for ovarian physiology and pathology, including follicle growth, gamete quality, ovulation dynamics, and ovarian cancer. Thus, developing a non-invasive tool to measure and monitor the stiffness of the human ovary would represent a major advance for female reproductive health and longevity. Shear wave elastography is a quantitative ultrasound imaging method for evaluation of soft tissue stiffness. Shear wave elastography has been used clinically in assessment of liver fibrosis and characterization of tendinopathies and various neoplasms in thyroid, breast, prostate, and lymph nodes as a non-invasive diagnostic and prognostic tool. In this study, we review the underlying principles of shear wave elastography and its current clinical uses outside the reproductive tract as well as its successful application of shear wave elastography to reproductive tissues, including the uterus and cervix. We also describe an emerging use of this technology in evaluation of human ovarian stiffness via transvaginal ultrasound. Establishing ovarian stiffness as a clinical biomarker of ovarian aging may have implications for predicting the ovarian reserve and outcomes of Assisted Reproductive Technologies as well as for the assessment of the efficacy of emerging therapeutics to extend reproductive longevity. This parameter may also have broad relevance in other conditions where ovarian stiffness and fibrosis may be implicated, such as polycystic ovarian syndrome, late off target effects of chemotherapy and radiation, premature ovarian insufficiency, conditions of differences of sexual development, and ovarian cancer. Summary sentence:  Shear Wave Elastography is a non-invasive technique to study human tissue stiffness, and here we review its clinical applications and implications for reproductive health and disease.

Value of Contrast-Enhanced Microflow Imaging in Diagnosis of Breast Masses in Comparison with Contrast-Enhanced Ultrasound

RATIONALE AND OBJECTIVES

To investigate the value of contrast-enhanced microflow imaging (CEUS-MFI) in distinguishing benign and malignant breast masses.

METHODS

A total of 116 breast masses classified as Breast Imaging Reporting and Data System (BI-RADS) category 3-5 by ultrasound (US) were included. Both contrast-enhanced ultrasound (CEUS) and CEUS-MFI were performed before excision or biopsy, with features and diagnostic efficiency analyzed. The US and CEUS BI-RADS 4A masses were also re-assessed by CEUS-MFI.

RESULTS

The features of CEUS-MFI including both interior and peripheral enlarged, twisted vessels (both P < 0.05), penetrating vessels (P = 0.007), and radial/spiculated vessels (P < 0.001) were more frequently detected in malignant masses, while peripheral annular vessels were mostly observed in benign masses (P < 0.001). Interestingly, a significant difference in the orientation of penetrating vessels between benign and malignant masses was found (P < 0.001), with parallel orientation mostly displayed in benign masses, while vertical or multiple-direction orientation mostly displayed in malignant masses. The microvascular architecture of breast masses was categorized into five patterns: avascular, line-like, tree-like, root hair-like, and crab claw-like pattern. Benign masses mainly displayed tree-like pattern (77.1% vs 10.9%, P < 0.05); malignant masses mainly displayed root hair-like (34.8% vs 5.7%, P < 0.05) and crab claw-like patterns (50.0% vs 1.4%, P < 0.05). The diagnostic efficiency of CEUS-MFI was higher relative to CEUS and US. In addition, CEUS-MFI decreased the biopsy rates of US and CEUS BI-RADS 4A masses without missing malignancies.

CONCLUSION

CEUS-MFI could be a valuable and promising technique in diagnosis of breast masses, and could provide more diagnostic information for radiologists.

Shear wave elastography for solid breast masses evaluation: Quantitative measurement of mean elasticity value and elasticity ratio

Purpose

Shear wave elastography (SWE), an ultrasonographic technique to measure the elasticity of mass lesions to evaluate breast mass. This study aimed to find out the cutoff values identifying breast malignancy using the mean elasticity (E-mean) and elasticity ratio (E-ratio) of breast masses.

Methods

This retrospective study included women underwent SWE and US-guided biopsy of breast masses. During conventional US, the SWE mode was also performed, determining elasticity measurements, E-mean and E-ratio. Histopathological reports were obtained to identify mass status. The optimal and alternative cutoff values for E-mean and E-ratio to determine malignancy were assessed by receiver operating characteristic (ROC) curve analysis and Youden's index score.

Results

Among 147 benign and 93 malignant masses, the median of E-means were 26.20 (IQR 15.70-56.60) and 141.60 (IQR 119.80-154.60) kPa and the median E-ratios were 3.11 (IQR 1.83-5.23) and 9.24 (IQR 6.76-12.44), respectively. Using Youden's index, the optimal cutoff values for E-mean and E-ratio were 90.35 and 5.89, with sensitivity of 87.1 % and 82.8 %, specificity of 89.1 % and 83.7 %, positive predictive value (PPV) of 83.5 % and 76.2 %, negative predictive value (NPV) of 91.6 % and 88.5 %, positive likelihood ratio (LR+) of 8.00 and 5.07, and negative likelihood ratio (LR-) of 0.14 and 0.21, respectively.

Conclusion

This study revealed that SWE is useful in predicting malignancy. With the optimal cutoff values of E-mean and E-ratio at 90.35 kPa and 5.89, the sensitivity was nearly 90 % with E-mean and slightly over 80 % with E-ratio, respectively. These findings could be used in conjunction with conventional US.

Preoperative Role of Superb Microvascular Imaging and Shear-Wave Elastography for Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer

ABSTRACT

This study aims to evaluate the role of shearwave elastography (SWE) and superb microvascular imaging (SMI) for preoperative prediction of axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 214 women with breast cancer, B-Mode ultrasonography (US), SMIvascular-index (SMIvi), and SWE (E-mean, E-ratio) values were recorded before tru-cut biopsy. Axillary fine-needle aspiration biopsy (FNAB) and sentinel lymph node sampling results were collected. Imaging findings and histopathological data were statistically compared. Receiver operating characteristic curve analysis was used to evaluate diagnostic performance. Reverse stepwise logistical regression analysis was conducted. Although ALNM was negative in 111 cases, it was positive in 103 patients. Axillary lymph node metastasis (+) group had larger size ( P < 0.001), higher vascularization (SMIvi: 8.0 ± 6.0 versus 5.0 ± 4.3, P < 0.001), and higher elasticity value (E-mean: 129 ± 31 kPa versus 117.3 ± 40 kPa, P = 0.014). Axillary lymph node metastasis was observed statistically more frequently in Her-2 positive cases ( P = 0.005). There was no significant difference between other B-mode US findings ( P > 0.05), SMI Adler ( P = 0.878), and E-ratio ( P = 0.212). The most appropriate cutoff value for the prediction of ALNM was 23.5 mm for size, 3.8 for SMIvi, and 138.5 kPa for E-mean. The most sensitive (77%) method was the SMIvi measurement, while the most specific (86%) finding was Her-2 positivity. The combined model (being Her-2 positive, >23.5 cm, and >3.8 SMIvi) increased the specificity (78%), PPV (71%), and accuracy (68%). Although the increased size is a previously studied parameter in predicting the risk of ALNM, Her-2 and data obtained by SWE, and SMI can be used to assist conventional US.

Ultrasound Shear Elastography With Expanded Bandwidth (USEWEB): A Novel Method for 2D Shear Phase Velocity Imaging of Soft Tissues

Ultrasound shear wave elastography (SWE) is a noninvasive approach for evaluating mechanical properties of soft tissues. In SWE either group velocity measured in the time-domain or phase velocity measured in the frequency-domain can be reported. Frequency-domain methods have the advantage over time-domain methods in providing a response for a specific frequency, while time-domain methods average the wave velocity over the entire frequency band. Current frequency-domain approaches struggle to reconstruct SWE images over full frequency bandwidth. This is especially important in the case of viscoelastic tissues, where tissue viscoelasticity is often studied by analyzing the shear wave phase velocity dispersion. For characterizing cancerous lesions, it has been shown that considerable biases can occur with group velocity-based measurements. However, using phase velocities at higher frequencies can provide more accurate evaluations. In this paper, we propose a new method called Ultrasound Shear Elastography with Expanded Bandwidth (USEWEB) used for two-dimensional (2D) shear wave phase velocity imaging. We tested the USEWEB method on data from homogeneous tissue-mimicking liver fibrosis phantoms, custom-made viscoelastic phantom measurements, phantoms with cylindrical inclusions experiments, and in vivo renal transplants scanned with a clinical scanner. We compared results from the USEWEB method with a Local Phase Velocity Imaging (LPVI) approach over a wide frequency range, i.e., up to 200-2000 Hz. Tests carried out revealed that the USEWEB approach provides 2D phase velocity images with a coefficient of variation below 5% over a wider frequency band for smaller processing window size in comparison to LPVI, especially in viscoelastic materials. In addition, USEWEB can produce correct phase velocity images for much higher frequencies, up to 1800 Hz, compared to LPVI, which can be used to characterize viscoelastic materials and elastic inclusions.

Ultrasound Viscosity Imaging in Breast Lesions: A Multicenter Prospective Study

RATIONALE AND OBJECTIVES

To explore and validate the clinical value of ultrasound (US) viscosity imaging in differentiating breast lesions by combining with BI-RADS, and then comparing the diagnostic performances with BI-RADS alone.

MATERIALS AND METHODS

This multicenter, prospective study enrolled participants with breast lesions from June 2021 to November 2022. A development cohort (DC) and validation cohort (VC) were established. Using histological results as reference standard, the viscosity-related parameter with the highest area under the receiver operating curve (AUC) was selected as the optimal one. Then the original BI-RADS would upgrade or not based on the value of this parameter. Finally, the results were validated in the VC and total cohorts. In the DC, VC and total cohorts, all breast lesions were divided into the large lesion, small lesion and overall groups respectively.

RESULTS

A total of 639 participants (mean age, 46 years ± 14) with 639 breast lesions (372 benign and 267 malignant lesions) were finally enrolled in this study including 392 participants in the DC and 247 in the VC. In the DC, the optimal viscosity-related parameter in differentiating breast lesions was calculated to be A'-S2-Vmax, with the AUC of 0.88 (95% CI: 0.84, 0.91). Using > 9.97 Pa.s as the cutoff value, the BI-RADS was then modified. The AUC of modified BI-RADS significantly increased from 0.85 (95% CI: 0.81, 0.88) to 0.91 (95% CI: 0.87, 0.93), 0.85 (95% CI: 0.80, 0.89) to 0.90 (95% CI: 0.85, 0.93) and 0.85 (95% CI: 0.82, 0.87) to 0.90 (95% CI: 0.88, 0.92) in the DC, VC and total cohorts respectively (P < .05 for all).

CONCLUSION

The quantitative viscous parameters evaluated by US viscosity imaging contribute to breast cancer diagnosis when combined with BI-RADS.

Use of a commercial artificial intelligence-based mammography analysis software for improving breast ultrasound interpretations

OBJECTIVES

To evaluate the use of a commercial artificial intelligence (AI)-based mammography analysis software for improving the interpretations of breast ultrasound (US)-detected lesions.

METHODS

A retrospective analysis was performed on 1109 breasts that underwent both mammography and US-guided breast biopsy. The AI software processed mammograms and provided an AI score ranging from 0 to 100 for each breast, indicating the likelihood of malignancy. The performance of the AI score in differentiating mammograms with benign outcomes from those revealing cancers following US-guided breast biopsy was evaluated. In addition, prediction models for benign outcomes were constructed based on clinical and imaging characteristics with and without AI scores, using logistic regression analysis.

RESULTS

The AI software had an area under the receiver operating characteristics curve (AUROC) of 0.79 (95% CI, 0.79-0.82) in differentiating between benign and cancer cases. The prediction models that did not include AI scores (non-AI model), only used AI scores (AI-only model), and included AI scores (integrated model) had AUROCs of 0.79 (95% CI, 0.75-0.83), 0.78 (95% CI, 0.74-0.82), and 0.85 (95% CI, 0.81-0.88) in the development cohort, and 0.75 (95% CI, 0.68-0.81), 0.82 (95% CI, 0.76-0.88), and 0.84 (95% CI, 0.79-0.90) in the validation cohort, respectively. The integrated model outperformed the non-AI model in the development and validation cohorts (p < 0.001 for both).

CONCLUSION

The commercial AI-based mammography analysis software could be a valuable adjunct to clinical decision-making for managing US-detected breast lesions.

CLINICAL RELEVANCE STATEMENT

The commercial AI-based mammography analysis software could potentially reduce unnecessary biopsies and improve patient outcomes.

KEY POINTS

• Breast US has high rates of false-positive interpretations. • A commercial AI-based mammography analysis software could distinguish mammograms having benign outcomes from those revealing cancers after US-guided breast biopsy. • A commercial AI-based mammography analysis software may improve interpretations for breast US-detected lesions.

Investigation of correlation between shear wave elastography and lymphangiogenesis in invasive breast cancer and diagnosis of axillary lymph node metastasis

BACKGROUND

Accurate evaluation of axillary lymph node metastasis (LNM) in breast cancer is very important. A large number of hyperplastic and dilated lymphangiogenesis cases can usually be found in the pericancerous tissue of breast cancer to promote the occurrence of tumor metastasis.Shear wave elastography (SWE) can be used as an important means for evaluating pericancerous stiffness. We determined the stiffness of the pericancerous by SWE to diagnose LNM and lymphangiogenesis in invasive breast cancer (IBC).

METHODS

Patients with clinical T1-T2 stage IBC who received surgical treatment in our hospital from June 2020 to December 2020 were retrospectively enrolled. A total of 299 patients were eventually included in the preliminary study, which included an investigation of clinicopathological features, ultrasonic characteristics, and SWE parameters. Multivariable logistic regression analysis was used to establish diagnostic model and evaluated its diagnostic performance of LNM. The correlation among SWE values, collagen volume fraction (CVF), and microlymphatic density (MLD) in primary breast cancer lesions was analyzed in another 97 patients.

RESULTS

The logistic regression model is Logit(P)=-1.878 + 0.992*LVI-2.010*posterior feature enhancement + 1.230*posterior feature shadowing + 0.102*posterior feature combined pattern + 0.009*Emax. The optimum cutoff value of the logistic regression model was 0.365, and the AUC (95% CI) was 0.697 (0.636-0.758); the sensitivity (70.7 vs. 54.3), positive predictive value (PPV) (54.0 vs. 50.8), negative predictive value (NPV) (76.9 vs. 69.7), and accuracy (65.2 vs. 61.9) were all higher than Emax. There was no correlation between the SWE parameters and MLD in primary breast cancer lesions.

CONCLUSIONS

The logistic regression model can help us to determine LNM, thus providing more imaging basis for the selection of preoperative treatment. The SWE parameter of the primary breast cancer lesion cannot reflect the peritumoral lymphangiogenesis, and we still need to find a new ultrasonic imaging method.

Applications of ultrasound elastography to hand and upper limb disorders

Ultrasound elastography is a recently developed method for accurate measurement of soft tissue stiffness in addition to the clinician's subjective evaluation. The present review briefly describes the ultrasound elastography techniques and outlines clinical applications for tendon, muscle, nerve, skin and other soft tissues of the hand and upper limb. Strain elastography provides a qualitative evaluation of the stiffness, and shear-wave elastography generates quantitative elastograms superimposed on a B-mode image. The stiffness in degenerative tendinopathy and/or tendon injury was significantly lower than in a normal tendon in several studies. Elastography is also a reliable method to evaluate functional muscle activity, compared to conventional surface electromyography. The median nerve is consistently stiffer in patients with carpal tunnel syndrome than in healthy subjects, on whatever ultrasound elastography technique. Elastography distinguishes normal skin from scars and can be used to evaluate scar severity and treatment. Elastography has huge clinical applications in musculoskeletal tissues. Continued development of systems and increased training of clinicians will expand our knowledge of elastography and its clinical applications in the future.

Biopathologic Characterization and Grade Assessment of Breast Cancer With 3-D Multiparametric Ultrasound Combining Shear Wave Elastography and Backscatter Tensor Imaging

OBJECTIVE

Despite recent improvements in medical imaging, the final diagnosis and biopathologic characterization of breast cancers currently still requires biopsies. Ultrasound is commonly used for clinical examination of breast masses. B-Mode and shear wave elastography (SWE) are already widely used to detect suspicious masses and differentiate benign lesions from cancers. But additional ultrasound modalities such as backscatter tensor imaging (BTI) could provide relevant biomarkers related to tissue organization. Here we describe a 3-D multiparametric ultrasound approach applied to breast carcinomas in the aims of (i) validating the ability of BTI to reveal the underlying organization of collagen fibers and (ii) assessing the complementarity of SWE and BTI to reveal biopathologic features of diagnostic interest.

METHODS

Three-dimensional SWE and BTI were performed ex vivo on 64 human breast carcinoma samples using a linear ultrasound probe moved by a set of motors. Here we describe a 3-D multiparametric representation of the breast masses and quantitative measurements combining B-mode, SWE and BTI.

RESULTS

Our results reveal for the first time that BTI can capture the orientation of the collagen fibers around tumors. BTI was found to be a relevant marker for assessing cancer stages, revealing a more tangent tissue orientation for in situ carcinomas than for invasive cancers. In invasive cases, the combination of BTI and SWE parameters allowed for classification of invasive tumors with respect to their grade with an accuracy of 95.7%.

CONCLUSION

Our results highlight the potential of 3-D multiparametric ultrasound imaging for biopathologic characterization of breast tumors.

Predictive value of contrast-enhanced ultrasonography and ultrasound elastography for management of BI-RADS category 4 nonpalpable breast masses

PURPOSE

The objective of this study was to investigate the independent risk factors and associated predictive values of contrast-enhanced ultrasound (CEUS), shear wave elastography (SWE), and strain elastography (SE) for high-risk lesions (HRL) and malignant tumors (MT) among nonpalpable breast masses classified as BI-RADS category 4 on conventional ultrasound.

METHODS

This prospective study involved consecutively admitted patients with breast tumors from January 2018, aiming to explore the management of BI-RADS category 4 breast tumors using CEUS and elastography. We conducted a retrospective review of patient data, focusing on those with a history of a nonpalpable mass as the primary complaint. Pathologic findings after surgical resection served as the gold standard. The CEUS arterial-phase indices were analyzed using contrast agent arrival-time parametric imaging processing mode, while quantitative and qualitative indices were examined on ES images. Independent risk factors were identified through binary logistic regression multifactorial analysis. The predictive efficacy of different modalities was compared using a receiver operating characteristics curve. Subsequently, a nomogram for predicting the risk of HRL/MT was established based on a multifactorial logistic regression model.

RESULTS

A total of 146 breast masses from 146 patients were included, comprising 80 benign tumors, 12 HRLs, and 54 MTs based on the final pathology. There was no significant difference in pathologic size between the benign and HRL/MT groups [8.00(6.25,10.00) vs. 9.00(6.00,10.00), P = 0.506]. The diagnostic efficacy of US plus CEUS exceeded that of US plus SWE/SE for BI-RADS 4 nonpalpable masses, with an AUC of 0.954 compared to 0.798/0.741 (P ＜ 0.001). Further stratified analysis revealed a more pronounced improvement for reclassification of BI-RADS 4a masses (AUC: 0.943 vs. 0.762/0.675, P ＜ 0.001) than BI-RADS 4b (AUC:0.950 vs. 0.885/0.796, P＞0.05) with the assistance of CEUS than SWE/SE. Employing downgrade CEUS strategies resulted in negative predictive values ranging from 95.2 % to 100.0 % for BI-RADS 4a and 4b masses. Conversely, using upgrade nomogram strategies, which included the independent predictive risk factors of irregular enhanced shape, poor defined enhanced margin, earlier enhanced time, increased surrounding vessels, and presence of contrast agent retention, the diagnostic performance achieved an AUC of 0.947 with good calibration.

CONCLUSION

After investigating the potential of CEUS and ES in improving risk assessment and diagnostic accuracy for nonpalpable BI-RADS category 4 breast masses, it is evident that CEUS has a more significant impact on enhancing classification compared to ES, particularly for BI-RADS 4a subgroup masses. This finding suggests that CEUS may offer greater benefits in improving risk assessment and diagnostic accuracy for this specific subgroup of breast masses.

Correlation of shear-wave elastography stiffness and apparent diffusion coefficient values with tumor characteristics in breast cancer

We aimed to investigate the correlation between shear-wave elastography (SWE) and apparent diffusion coefficient (ADC) values in breast cancer and to identify the associated characteristics. We included 91 breast cancer patients who underwent SWE and breast MRI prior to surgery between January 2016 and November 2017. We measured the lesion's mean (Emean) and maximum (Emax) elasticities of SWE and ADC values. We evaluated the correlation between SWE, ADC values and tumor size. The mean SWE and ADC values were compared for categorical variable of the pathological/imaging characteristics. ADC values showed negative correlation with Emean (r =  - 0.315, p = 0.002) and Emax (r =  - 0.326, p = 0.002). SWE was positively correlated with tumor size (r = 0.343-0.366, p < 0.001). A higher SWE value indicated a tendency towards a higher T stage (p < 0.001). Triple-negative breast cancer showed the highest SWE values (p = 0.02). SWE were significantly higher in breast cancers with posterior enhancement, vascularity, and washout kinetics (p < 0.02). SWE stiffness and ADC values were negatively correlated in breast cancer. SWE values correlated significantly with tumor size, and were higher in triple-negative subtype and aggressive imaging characteristics.

Tumor-Infiltrating Lymphocyte Level Consistently Correlates with Lower Stiffness Measured by Shear-Wave Elastography: Subtype-Specific Analysis of Its Implication in Breast Cancer

Background: We aimed to elucidate the clinical significance of tumor stiffness across breast cancer subtypes and establish its correlation with the tumor-infiltrating lymphocyte (TIL) levels using shear-wave elastography (SWE). Methods: SWE was used to measure tumor stiffness in breast cancer patients from January 2016 to August 2020. The association of tumor stiffness and clinicopathologic parameters, including the TIL levels, was analyzed in three breast cancer subtypes. Results: A total of 803 patients were evaluated. Maximal elasticity (Emax) showed a consistent positive association with an invasive size and the pT stage in all cases, while it negatively correlated with the TIL level. A subgroup-specific analysis revealed that the already known parameters for high stiffness (lymphovascular invasion, lymph node metastasis, Ki67 levels) were significant only in hormone receptor-positive and HER2-negative breast cancer (HR + HER2-BC). In the multivariate logistic regression, an invasive size and low TIL levels were significantly associated with Emax in HR + HER2-BC and HER2 + BC. In triple-negative breast cancer, only TIL levels were significantly associated with low Emax. Linear regression confirmed a consistent negative correlation between TIL and Emax in all subtypes. Conclusions: Breast cancer stiffness presents varying clinical implications dependent on the tumor subtype. Elevated stiffness indicates a more aggressive tumor biology in HR + HER2-BC, but is less significant in other subtypes. High TIL levels consistently correlate with lower tumor stiffness across all subtypes.

Deep learning radiomics based prediction of axillary lymph node metastasis in breast cancer

This study aimed to develop and validate a deep learning radiomics nomogram (DLRN) for the preoperative evaluation of axillary lymph node (ALN) metastasis status in patients with a newly diagnosed unifocal breast cancer. A total of 883 eligible patients with breast cancer who underwent preoperative breast and axillary ultrasound were retrospectively enrolled between April 1, 2016, and June 30, 2022. The training cohort comprised 621 patients from Hospital I; the external validation cohorts comprised 112, 87, and 63 patients from Hospitals II, III, and IV, respectively. A DLR signature was created based on the deep learning and handcrafted features, and the DLRN was then developed based on the signature and four independent clinical parameters. The DLRN exhibited good performance, yielding areas under the receiver operating characteristic curve (AUC) of 0.914, 0.929, and 0.952 in the three external validation cohorts, respectively. Decision curve and calibration curve analyses demonstrated the favorable clinical value and calibration of the nomogram. In addition, the DLRN outperformed five experienced radiologists in all cohorts. This has the potential to guide appropriate management of the axilla in patients with breast cancer, including avoiding overtreatment.

Development of a Multi-Parametric ultrasonography nomogram for prediction of invasiveness in ductal carcinoma in situ

OBJECTIVE

To investigate the independent risk variables associated with the potential invasiveness of ductal carcinoma in situ (DCIS) on multi-parametric ultrasonography, and further construct a nomogram for risk assessment.

METHODS

Consecutive patients from January 2017 to December 2022 who were suspected of having ductal carcinoma in situ (DCIS) based on magnetic resonance imaging or mammography were prospectively enrolled. Histopathological findings after surgical resection served as the gold standard. Grayscale ultrasound, Doppler ultrasound, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS) examinations were preoperative performed. Binary logistic regression was used for multifactorial analysis to identify independent risk factors from multi-parametric ultrasonography. The correlation between independent risk factors and pathological prognostic markers was analyzed. The predictive efficacy of DCIS associated with invasiveness was assessed by logistic analysis, and a nomogram was established.

RESULTS

A total of 250 DCIS lesions were enrolled from 249 patients, comprising 85 pure DCIS and 165 DCIS with invasion (DCIS-IDC), of which 41 exhibited micro-invasion. The multivariate analysis identified independent risk factors for DCIS with invasion on multi-parametric ultrasonography, including image size (>2cm), Doppler ultrasound RI (≥0.72), SWE's Emax (≥66.4 kPa), hyper-enhancement, centripetal enhancement, increased surrounding vessel, and no contrast agent retention on CEUS. These factors correlated with histological grade, Ki-67, and human epidermal growth factor receptor 2 (HER2) (P < 0.1). The multi-parametric ultrasound approach demonstrated good predictive performance (sensitivity 89.7 %, specificity 73.8 %, AUC 0.903), surpassing single US modality or combinations with SWE or CEUS modalities. Utilizing these factors, a predictive nomogram achieved a respectable performance (AUC of 0.889) for predicting DCIS with invasion. Additionally, a separate nomogram for predicting DCIS with micro-invasion, incorporating independent risk factors such as RI (≥0.72), SWE's Emax (≥65.2 kPa), and centripetal enhancement, demonstrated an AUC of 0.867.

CONCLUSION

Multi-parametric ultrasonography demonstrates good discriminatory ability in predicting both DCIS with invasion and micro-invasion through the analysis of lesion morphology, stiffness, neovascular architecture, and perfusion. The use of a nomogram based on ultrasonographic images offers an intuitive and effective method for assessing the risk of invasion in DCIS. Although the nomogram is not currently considered a clinically applicable diagnostic tool due to its AUC being below the threshold of 0.9, further research and development are anticipated to yield positive outcomes and enhance its viability for clinical utilization.

The Japanese breast cancer society clinical practice guidelines for breast cancer screening and diagnosis, 2022 edition

This article provides updates to readers based on the newly published Japanese Breast Cancer Society Clinical Practice Guidelines for Breast Cancer Screening and Diagnosis, 2022 Edition. These guidelines incorporate the latest evaluation of evidence from studies of diagnostic accuracy. For each clinical question, outcomes for benefits and harms were established, and qualitative or quantitative systematic reviews were conducted. Recommendations were determined through voting by a multidisciplinary group, and guidelines were documented to facilitate shared decision-making among patients and medical professionals. The guidelines address screening, surveillance, and pre- and postoperative diagnosis of breast cancer. In an environment that demands an integrated approach, decisions are needed on how to utilize modalities, such as mammography, ultrasound, MRI, and PET/CT. Additionally, it is vital to understand the appropriate use of new technologies, such as tomosynthesis, elastography, and contrast-enhanced ultrasound, and to consider how best to adapt these methods for individual patients.

Diffusion-Weighted MRI-Based Virtual Elastography and Shear-Wave Elastography for the Assessment of Breast Lesions

BACKGROUND

Diffusion-weighted imaging (DWI)-based virtual MR elastography (DWI-vMRE) in the assessment of breast lesions is still in the research stage.

PURPOSE

To investigate the usefulness of elasticity values on DWI-vMRE in the evaluation of breast lesions, and the correlation with the values calculated from shear-wave elastography (SWE).

STUDY TYPE

Prospective.

POPULATION/SUBJECTS

153 patients (mean age ± standard deviation: 55 ± 12 years) with 153 pathological confirmed breast lesions (24 benign and 129 malignant lesions).

FIELD STRENGTH/SEQUENCE

1.5-T MRI, multi-b readout segmented echo planar imaging (b-values of 0, 200, 800, and 1000 sec/mm2 ).

ASSESSMENT

For DWI-vMRE assessment, lesions were manually segmented using apparent diffusion coefficient (ADC0-1000 ) map, then the region of interests were copied to the map of shifted-ADC (sADC200-800 , sADC 200-1500 ). For SWE assessment, the shear modulus of the lesions was measured by US elastic modulus (μUSE ). Intraclass/interclass kappa coefficients were calculated to measure the consistency.

STATISTICAL TESTS

Pearson's correlation was used to assess the relationship between sADC and μUSE . A receiver operating characteristic analysis with the area under the curve (AUC) was performed to compare the diagnostic accuracy between benign and malignant breast lesions of sADC and μUSE . A P value <0.05 was considered statistically significant.

RESULTS

There were significant differences between benign and malignant breast lesions of μUSE (24.17 ± 10.64 vs. 37.20 ± 12.61), sADC200-800 (1.38 ± 0.31 vs. 0.97 ± 0.18 × 10-3  mm2 /sec), and sADC200-1500 (1.14 ± 0.30 vs. 0.78 ± 0.13 × 10-3  mm2 /sec). In all breast lesions, a moderate but significant correlation was observed between μUSE and sADC200-800 /sADC200-1500 (r = -0.49/-0.44). AUC values to differentiate benign from malignant lesions were as follows: μUSE , 0.78; sADC200-800 , 0.89; sADC200-1500 , 0.89.

DATA CONCLUSIONS

Both SWE and DWI-vMRE could be used for the differentiation of benign versus malignant breast lesions. Furthermore, DWI-vMRE with the use of sADC show relatively higher AUC values than SWE.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

In plane quantification ofin vivomuscle elastic anisotropy factor by steered ultrasound pushing beams

Objective.Skeletal muscles are organized into distinct layers and exhibit anisotropic characteristics across various scales. Assessing the arrangement of skeletal muscles may provide valuable biomarkers for diagnosing muscle-related pathologies and evaluating the efficacy of clinical interventions.Approach. In this study, we propose a novel ultrafast ultrasound sequence constituted of steered pushing beams was proposed for ultrasound elastography applications in transverse isotropic muscle. Based on the propagation of the shear wave vertical mode, it is possible to fit the experimental results to retrieve in the same imaging plane, the shear modulus parallel to fibers as well as the elastic anisotropy factor (ratio of Young's moduli times the shear modulus perpendicular to fibers).Main results. The technique was demonstratedin vitroin phantoms andex vivoin fusiform beef muscles. At last, the technique was appliedin vivoon fusiform muscles (biceps brachii) and mono-pennate muscles (gastrocnemius medialis) during stretching and contraction.Significance. This novel sequence provides access to new structural and mechanical biomarkers of muscle tissue, including the elastic anisotropy factor, within the same imaging plane. Additionally, it enables the investigation of multiples parameters during muscle active and passive length changes.

Unravelling anisotropic nonlinear shear elasticity in muscles: Towards a non-invasive assessment of stress in living organisms

Acoustoelasticity theory describes propagation of shear waves in uniaxially stressed medium and allows the retrieval of nonlinear elastic coefficients of tissues. In transverse isotropic medium such as muscles the theory leads to 9 different configurations of propagating shear waves (stress axis vs. fibers axis vs. shear wave polarization axis vs. shear wave propagation axis). In this work we propose to use 4 configurations to quantify these nonlinear parameters ex vivo and in vivo. Ex vivo experiments combining ultrasound shear wave elastography and mechanical testing were conducted on iliopsoas pig muscles to quantify three third-order nonlinear coefficients A, H and K that are possibly linked to the architectural structure of muscles. In vivo experiments were performed with human volunteers on biceps brachii during a stretching exercise on an ergometer. A combination of the third order nonlinear elastic parameters was assessed. The knowledge of this nonlinear elastic parameters paves the way to quantify in vivo the local forces produced by muscle during exercise, contraction or movements.

On the Role of Coherent Plane Wave Compounding in Shear Wave Elasticity Imaging: The Convolution Effect and Its Implications

OBJECTIVE

The clinical applicability of shear wave elasticity imaging (SWEI) has been confounded by its appreciable inter-system variability and unsatisfactory sensitivity. While SWEI relies on plane wave imaging (PWI) to achieve real-time rendering, it has been rarely noticed that PWI can affect SWEI's performance. This work is aimed at demonstrating that the use of coherent plane wave compounding (CPWC) can be a factor causing SWEI's underperformance.

METHODS

We presented a model to formally describe the slow-time behavior of CPWC in motion tracking. This model reveals that CPWC introduces temporal convolution on the observed motion, making the motion sampling process a low-pass filter (LPF). For validation, shear waves were produced in a phantom in the same way but sampled via PWI using different compounding numbers (CN) and pulse repetition frequencies (PRF), with the obtained signals compared with the inferences drawn from our model. Similar experiments were performed to reconstruct two small targets in the phantom in order to appraise the impact of CPWC on SWEI's sensitivity.

DISCUSSION

The validation experiment shows that the measurements match well with the model inferences, which verifies the LPF nature of CPWC. The phantom study also shows that either increasing CN or decreasing PRF can cause the loss of high-frequency motion information, leading to blurred target delineation by SWEI.

CONCLUSION

The convolution effect can help understand the variability of SWEI. Researchers should beware this effect when working on SWEI standardization. Clinicians using SWEI should also be cautious because this effect makes it harder to identify small lesions.

Evaluation of standard breast ultrasonography by adding two-dimensional and three-dimensional shear wave elastography: a prospective, multicenter trial

OBJECTIVE

To reduce the number of biopsies performed on benign breast lesions categorized as BI-RADS 4-5, we investigated the diagnostic performance of combined two-dimensional and three-dimensional shear wave elastography (2D + 3D SWE) with standard breast ultrasonography (US) for the BI-RADS assessment of breast lesions.

METHODS

A total of 897 breast lesions, categorized as BI-RADS 3-5, were subjected to standard breast US and supplemented by 2D SWE only and 2D + 3D SWE analysis. Based on the malignancy rate of less than 2% for BI-RADS 3, lesions assessed by standard breast US were reclassified with SWE assessment.

RESULTS

After standard breast US evaluation, 268 (46.1%) participants underwent benign biopsies in BI-RADS 4-5 lesions. By using separated cutoffs for upstaging BI-RADS 3 at 120 kPa and downstaging BI-RADS 4a at 90 kPa in 2D + 3D SWE reclassification, 123 (21.2%) participants underwent benign biopsy, resulting in a 54.1% reduction (123 versus 268).

CONCLUSION

Combining 2D + 3D SWE with standard breast US for reclassification of BI-RADS lesions may achieve a reduction in benign biopsies in BI-RADS 4-5 lesions without sacrificing sensitivity unacceptably.

CLINICAL RELEVANCE STATEMENT

Combining 2D + 3D SWE with US effectively reduces benign biopsies in breast lesions with categories 4-5, potentially improving diagnostic accuracy of BI-RADS assessment for patients with breast lesions.

TRIAL REGISTRATION

ChiCTR1900026556 KEY POINTS: • Reduce benign biopsy is necessary in breast lesions with BI-RADS 4-5 category. • A reduction of 54.1% on benign biopsies in BI-RADS 4-5 lesions was achieved using 2D + 3D SWE reclassification. • Adding 2D + 3D SWE to standard breast US improved the diagnostic performance of BI-RADS assessment on breast lesions: specificity increased from 54 to 79%, and PPV increased from 54 to 71%, with slight loss in sensitivity (97.2% versus 98.7%) and NPV (98.1% versus 98.7%).

Unveiling the future of breast cancer assessment: a critical review on generative adversarial networks in elastography ultrasound

Elastography Ultrasound provides elasticity information of the tissues, which is crucial for understanding the density and texture, allowing for the diagnosis of different medical conditions such as fibrosis and cancer. In the current medical imaging scenario, elastograms for B-mode Ultrasound are restricted to well-equipped hospitals, making the modality unavailable for pocket ultrasound. To highlight the recent progress in elastogram synthesis, this article performs a critical review of generative adversarial network (GAN) methodology for elastogram generation from B-mode Ultrasound images. Along with a brief overview of cutting-edge medical image synthesis, the article highlights the contribution of the GAN framework in light of its impact and thoroughly analyzes the results to validate whether the existing challenges have been effectively addressed. Specifically, This article highlights that GANs can successfully generate accurate elastograms for deep-seated breast tumors (without having artifacts) and improve diagnostic effectiveness for pocket US. Furthermore, the results of the GAN framework are thoroughly analyzed by considering the quantitative metrics, visual evaluations, and cancer diagnostic accuracy. Finally, essential unaddressed challenges that lie at the intersection of elastography and GANs are presented, and a few future directions are shared for the elastogram synthesis research.

Comparative analysis of conventional ultrasound and shear wave elastography features in primary breast diffuse large B-cell lymphoma

BACKGROUND

Primary breast diffuse large B-cell lymphoma (PB-DLBCL) is a rare subtype of non-Hodgkin lymphoma that accounts for < 3% of extranodal lymphomas and 1% of breast tumors. Its diagnosis and management are challenging because of its rarity, heterogeneity, and aggressive behavior. Conventional ultrasound (US) is the first-line imaging modality for breast lesions; however, it has limited specificity and accuracy for PB-DLBCL. Shear wave elastography (SWE) is a novel US technique that measures tissue stiffness and may reflect the histological characteristics and biological behavior of breast lesions.

AIM

To compare the conventional US and SWE features of PB-DLBCL and evaluate their diagnostic performance and prognostic value.

METHODS

We retrospectively reviewed the clinical data and US images of 32 patients with pathologically confirmed PB-DLBCL who underwent conventional US and SWE before treatment. We analyzed conventional US features (shape, margin, orientation, echo, posterior acoustic features, calcification, and vascularity) and SWE features (mean elasticity value, standard deviation, minimum elasticity value, maximum elasticity value, and lesion-to-fat ratio) of the PB-DLBCL lesions. Using receiver operating characteristic curve analysis, we determined the optimal cutoff values and diagnostic performance of conventional US and SWE features. We also performed a survival analysis to assess the prognostic value of conventional US and SWE features.

RESULTS

The results showed that the PB-DLBCL lesions were mostly irregular in shape (84.4%), microlobulated or spiculated in margins (75%), parallel in orientation (65.6%), hypoechoic in echo (87.5%), and had posterior acoustic enhancement (65.6%). Calcification was rare (6.3%) and vascularity was variable (31.3% avascular, 37.5% hypovascular, and 31.3% hypervascular). The mean elasticity value of PB-DLBCL lesions was significantly higher than that of benign breast lesions (113.4 ± 46.9 kPa vs 27.8 ± 16.4 kPa, P < 0.001). The optimal cutoff value of the mean elasticity for distinguishing PB-DLBCL from benign breast lesions was 54.5 kPa, with a sensitivity of 93.8%, specificity of 92.9%, positive predictive value of 93.8%, negative predictive value of 92.9%, and accuracy of 93.3%. The mean elasticity value was also significantly correlated with Ki-67 expression level (r = 0.612, P < 0.001), which is a marker of tumor proliferation and aggressiveness. Survival analysis showed that patients with higher mean elasticity values (> 54.5 kPa) had worse overall survival (OS) and progression-free survival (PFS) than those with lower mean elasticity values (< 54.5 kPa) (P = 0.038 for OS and P = 0.027 for PFS).

CONCLUSION

Conventional US and SWE provide useful information for diagnosing and forecasting PB-DLBCL. SWE excels in distinguishing PB-DLBCL from benign breast lesions, reflects tumor proliferation and aggressiveness, and improves disease management.

Biophysics in tumor growth and progression: from single mechano-sensitive molecules to mechanomedicine

Evidence from physical sciences in oncology increasingly suggests that the interplay between the biophysical tumor microenvironment and genetic regulation has significant impact on tumor progression. Especially, tumor cells and the associated stromal cells not only alter their own cytoskeleton and physical properties but also remodel the microenvironment with anomalous physical properties. Together, these altered mechano-omics of tumor tissues and their constituents fundamentally shift the mechanotransduction paradigms in tumorous and stromal cells and activate oncogenic signaling within the neoplastic niche to facilitate tumor progression. However, current findings on tumor biophysics are limited, scattered, and often contradictory in multiple contexts. Systematic understanding of how biophysical cues influence tumor pathophysiology is still lacking. This review discusses recent different schools of findings in tumor biophysics that have arisen from multi-scale mechanobiology and the cutting-edge technologies. These findings range from the molecular and cellular to the whole tissue level and feature functional crosstalk between mechanotransduction and oncogenic signaling. We highlight the potential of these anomalous physical alterations as new therapeutic targets for cancer mechanomedicine. This framework reconciles opposing opinions in the field, proposes new directions for future cancer research, and conceptualizes novel mechanomedicine landscape to overcome the inherent shortcomings of conventional cancer diagnosis and therapies.

Comparison of ultrasound elastography, magnetic resonance elastography and finite element model to quantify nonlinear shear modulus

Objective. The aim of this study is to validate the estimation of the nonlinear shear modulus (A) from the acoustoelasticity theory with two experimental methods, ultrasound (US) elastography and magnetic resonance elastography (MRE), and a finite element method.Approach. Experiments were performed on agar (2%)-gelatin (8%) phantom considered as homogeneous, elastic and isotropic. Two specific setups were built to ensure a uniaxial stress step by step on the phantom, one for US and a nonmagnetic version for MRE. The stress was controlled identically in both imaging techniques, with a water tank placed on the top of the phantom and filled with increasing masses of water during the experiment. In US, the supersonic shear wave elastography was implemented on an ultrafast US device, driving a 6 MHz linear array to measure shear wave speed. In MRE, a gradient-echo sequence was used in which the three spatial directions of a 40 Hz continuous wave displacement generated with an external driver were encoded successively. Numerically, a finite element method was developed to simulate the propagation of the shear wave in a uniaxially stressed soft medium.Main results. Similar shear moduli were estimated at zero stress using experimental methods,μ0US= 12.3 ± 0.3 kPa andμ0MRE= 11.5 ± 0.7 kPa. Numerical simulations were set with a shear modulus of 12 kPa and the resulting nonlinear shear modulus was found to be -58.1 ± 0.7 kPa. A very good agreement between the finite element model and the experimental models (AUS= -58.9 ± 9.9 kPa andAMRE= -52.8 ± 6.5 kPa) was obtained.Significance. These results show the validity of such nonlinear shear modulus measurement quantification in shear wave elastography. This work paves the way to develop nonlinear elastography technique to get a new biomarker for medical diagnosis.

A nomogram incorporating clinical, conventional ultrasound and shear wave elastography findings for distinguishing pleomorphic adenoma from Warthin's tumor of the major salivary glands

OBJECTIVE

Pre-operative differentiation between pleomorphic adenoma (PA) and Warthin's tumor (WT) of the major salivary glands is crucial for treatment decisions. The purpose of this study was to develop and validate a nomogram incorporating clinical, conventional ultrasound (CUS) and shear wave elastography (SWE) features to differentiate PA from WT.

METHODS

A total of 113 patients with histological diagnosis of PA or WT of the major salivary glands treated at Fujian Medical University Union Hospital were enrolled in training cohort (n = 75; PA = 41, WT = 34) and validation cohort (n = 38; PA = 22, WT = 16). The least absolute shrinkage and selection operator (LASSO) regression algorithm was used for screening the most optimal clinical, CUS, and SWE features. Different models, including the nomogram model, clinic-CUS (Clin+CUS) and SWE model, were built using logistic regression. The performance levels of the models were evaluated and validated on the training and validation cohorts, and then compared among the three models.

RESULTS

The nomogram incorporating the clinical, CUS and SWE features showed favorable predictive value for differentiating PA from WT, with the area under the curves (AUCs) of 0.947 and 0.903 for the training cohort and validation cohort, respectively. Decision curve analysis showed that the nomogram model outperformed the Clin+CUS model and SWE model in terms of clinical usefulness.

CONCLUSIONS

The nomogram had good performance in distinguishing major salivary PA from WT and held potential for optimizing the clinical decision-making process.

Best Practice Guideline - DEGUM Recommendations on Breast Ultrasound

Alongside mammography, breast ultrasound is an important and well-established method in assessment of breast lesions. With the "Best Practice Guideline", the DEGUM Breast Ultrasound (in German, "Mammasonografie") working group, intends to describe the additional and optional application modalities for the diagnostic confirmation of breast findings and to express DEGUM recommendations in this Part II, in addition to the current dignity criteria and assessment categories published in Part I, in order to facilitate the differential diagnosis of ambiguous lesions.The present "Best Practice Guideline" has set itself the goal of meeting the requirements for quality assurance and ensuring quality-controlled performance of breast ultrasound. The most important aspects of quality assurance are explained in this Part II of the Best Practice Guideline.

Improved Breast 2D SWE Algorithm to Eliminate False-Negative Cases

OBJECTIVES

Two-dimensional shear wave elastography (SWE) has been limited in breast lesion characterization due to false-negative results from artifacts. The aim of this study was to evaluate an updated Food and Drug Administration-approved breast 2D-SWE algorithm and compare with the standard algorithm (SA).

MATERIALS AND METHODS

This prospective, single-center study was approved by our local institutional review board and Health Insurance Portability and Accountability Act compliant. From April 25, 2019 to May 2, 2022, raw shear wave data were saved on patients having screening or diagnostic breast ultrasound on a Siemens Sequoia US. After removing duplicate images and those without biopsy diagnosis or stability over 2 years, there were 298 patients with 394 lesions with biopsy-proven pathology or >2-year follow-up. Raw data were processed using the SA and a new algorithm (NA). Five-millimeter regions of interest were placed in the highest stiffness in the lesion or adjacent 3 mm on the SA. Stiffness values (shear wave speed, max) in this location from both algorithms were recorded. Statistics were calculated for comparing the 2 algorithms.

RESULTS

The mean patient age was 56.3 ± 16.1 years (range, 21-93 years). The mean benign lesion size was 10.7 ± 8.0 mm (range, 2-46 mm), whereas the mean malignant lesion size was 14.9 ± 7.8 mm (range, 4-36 mm). There were 201 benign (>2-year follow-up) and 193 biopsied lesions (65 benign; 128 malignant). The mean maximum stiffness for benign lesions was 2.37 m/s (SD 1.26 m/s) for SA and 3.51 m/s (SD 2.05 m/s) for NA. For malignant lesions, the mean maximum stiffness was 4.73 m/s (SD, 1.71 m/s) for SA and 8.45 m/s (SD, 1.42 m/s) for NA. The area under the receiver operating characteristic curve was 0.87 SA and 0.95 NA when using the optimal cutoff value. Using a threshold value of 5.0 m/s for NA and comparing to SA, the sensitivity increased from 0.45 to 1.00 and the specificity decreased from 0.94 to 0.81; the positive predictive value was 0.72, the negative predictive value was 1.00, and the negative likelihood ratio was 0.00.

CONCLUSIONS

Using a new breast SWE algorithm significantly improves the sensitivity of the technique with a small decrease in specificity, virtually eliminating the "soft" cancer artifact. The new 2D-SWE algorithm significantly increases the sensitivity and negative predictive value in characterizing breast lesions as benign or malignant and allows for downgrading all BI-RADS 4 lesions.

Clinical applications of shear wave dispersion imaging for breast lesions: a pictorial essay

Shear wave dispersion (SWD) imaging is a newly developed ultrasound technology designed to evaluate the dispersion slope of shear waves, which is related to tissue viscosity. This advanced imaging technique holds potential for distinguishing malignant lesions from benign lesions and normal breast tissue. The SWD slope, as determined by shear wave elastography (SWE), could offer crucial insights into the characterization of breast lesions. This article presents SWE and SWD images of both malignant and benign breast lesions, in addition to normal breast tissue.

Linear Regression Modeling Based Scoring System to Reduce Benign Breast Biopsies Using Multi-parametric US with Color Doppler and SWE

RATIONALE AND OBJECTIVES

To develop a simple ultrasound (US) based scoring system to reduce benign breast biopsies.

MATERIALS AND METHODS

Women with BI-RADS 4 or 5 breast lesions underwent shear-wave elastography (SWE) imaging before biopsy. Standard US and color Doppler US (CDUS) parameters were recorded, and the size ratio (SzR=longest/shortest diameter) was calculated. Measured/calculated SWE parameters were minimum (SWVMin) and maximum (SWVMax) shear velocity, velocity heterogeneity (SWVH=SWVMax-SWVMin), velocity ratio (SWVR=SWVMin/SWVMax), and normalized SWVR (SWVRn=(SWVMax-SWVMin)/SWVMin). Linear regression analysis was performed by converting continuous parameters into categorical corresponding equivalents using decision tree analyses. Linear regression models were fitted using stepwise regression analysis and optimal coefficients for the predictors in the models were determined. A scoring model was devised from the results and validated using a different data set from another center consisting of 187 cases with BI-RADS 3, 4, and 5 lesions.

RESULTS

A total of 418 lesions (238 benign, 180 malignant) were analyzed. US and CDUS parameters exhibited poor (AUC=0.592-0.696), SWE parameters exhibited poor-good (AUC=0.607-0.816) diagnostic performance in benign/malignant discrimination. Linear regression models of US+CDUS and US+SWE parameters revealed an AUC of 0.819 and 0.882, respectively. The developed scoring system could have avoided biopsy in 37.8% of benign lesions while missing 1.1% of malignant lesions. The scoring system was validated with a 100% NPV rate with a specificity of 74.6%.

CONCLUSION

The linear regression model using US+SWE parameters performed better than any single parameter alone. The developed scoring method could lead to a significant decrease in benign biopsies.

Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer

RATIONALE AND OBJECTIVES

To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elastography (SWE) to predict response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

MATERIALS AND METHODS

In this prospective study, 255 breast cancer patients who received NAC between September 2016 and December 2021 were included. Radiomics models were designed using a support vector machine classifier based on US images obtained before treatment, including BUS and SWE. And CNN models also were developed using ResNet architecture. The final predictive model was developed by combining the dual-modal US and independently associated clinicopathologic characteristics. The predictive performances of the models were assessed with five-fold cross-validation.

RESULTS

Pretreatment SWE performed better than BUS in predicting the response to NAC for breast cancer for both the CNN and radiomics models (P < 0.001). The predictive results of the CNN models were significantly better than the radiomics models, with AUCs of 0.72 versus 0.69 for BUS and 0.80 versus 0.77 for SWE, respectively (P = 0.003). The CNN model based on the dual-modal US and molecular data exhibited outstanding performance in predicting NAC response, with an accuracy of 83.60% ± 2.63%, a sensitivity of 87.76% ± 6.44%, and a specificity of 77.45% ± 4.38%.

CONCLUSION

The pretreatment CNN model based on the dual-modal US and molecular data achieved excellent performance for predicting the response to chemotherapy in breast cancer. Therefore, this model has the potential to serve as a non-invasive objective biomarker to predict NAC response and aid clinicians with individual treatments.

Application of noninvasive test (acoustic attenuation imaging and ultrasonic shear wave elastography) to grade nonalcoholic fatty liver disease: An observational study

The aim of this study was to validate the diagnostic efficacy of acoustic attenuation imaging (ATI) and ultrasonic shear wave elastography (SWE) in classifying nonalcoholic fatty liver disease (NAFLD). A total of 100 patients with NAFLD were recruited from our hospital between January 2021 and December 2022. Patient demographics and clinical data were collected, and 2-dimensional ultrasound was used to screen patients based on liver echo characteristics. Patients without liver space-occupying lesions underwent routine ultrasound examinations. Imaging or serology was used to confirm the presence of fatty liver in patients or healthy individuals. Patients with alcoholic liver disease (alcohol equivalent content < 20 g/day for women, <30 g/day for men), as well as those with lenticular degeneration, total parenteral nutrition, autoimmune liver disease, drug-induced hepatitis, and viral hepatitis, were excluded from the study. Out of the 100 included patients, 24 had normal liver, 21 had mild fatty liver, 30 had moderate fatty liver, and 25 had severe fatty liver. There were age differences between the normal group and patients with mild fatty liver, and the average body mass index (BMI) varied across the 4 groups. As the severity of the disease increased, the average BMI also increased (P < .05). The ATI scores and SWE scores differed significantly among the different groups (P < .05), with both scores showing an upward trend as the fatty liver condition worsened. Correlation analysis revealed positive correlations between ATI and SWE scores and the degree of fatty liver (P < .05), positive correlations with BMI (P < .05), and negative correlations with high-density lipoprotein cholesterol expression (P < .05). The area under the curve (AUC) for the ATI score in diagnosing different degrees of fatty liver was > 0.750, and the AUC for the SWE score was also > 0.750. The AUC for SWE score in diagnosing different degrees of fatty liver ranged from 1.01 to 4.57, while the combined AUC for ATI and SWE scores was > 0.850, with respective cutoff values of 3.62, 5.72, and 7.57 based on the maximum approximate entry index. The combination of ATI and SWE has a significant impact on the grading diagnosis of NAFLD, and its application can be extended to clinical practice.

Comparison of sound touch elastography and quantification for assessing the renal pathologic changes in patients with proteinuria

OBJECTIVE

Sound touch elastography (STE) and sound touch quantification (STQ) are novel imaging methods to evaluate tissue stiffness. This study aims to investigate renal stiffness in patients with chronic kidney disease (CKD) by STE and STQ, using renal biopsy as 'gold standard'.

METHODS

Between 2019 January and 2022 June, 60 patients who underwent renal biopsy for proteinuria (cases) and 45 healthy volunteers (controls) at our hospital were included in this study. The maximum and mean elastic modulus (Emax, Emean) of region of interest in right kidney were measured by STE and STQ techniques. Biochemical profiles and renal biopsy findings were recorded.

RESULTS

Both Emax and Emean measured by STE were significantly different between cases and controls. ROC analysis of STE measurements revealed using a cutoff of 13.53 kPa for Emax and 10.16 kPa for Emean, the area under the curve (AUC) to distinguish nephropathy from healthy was 0.718 and 0.744. Analysis of ROC for STQ measurements showed that using a cutoff value of 15.87 kPa for Emax and 9.95 kPa for Emean, the AUC for the nephropathy was 0.612 and 0.569. Emax and Emean values were significantly different among CKD patients with mild, moderate and severe pathological stage. The Emax value for STE was positively related to Scr, β2-MG (r = 0.257, 0.292, p < 0.05).

CONCLUSION

Both STE and STQ are non-invasive, feasible methods to quantitatively evaluate renal stiffness. STE is more effective than STQ in the diagnosis of CKD patients with proteinuria.

CRITICAL RELEVANCE STATEMENT

Sound touch elastography is more effective than sound touch quantification in the diagnosis of chronic kidney disease patients with proteinuria.

KEY POINTS

• Emax and Emean measured by STE were different between cases and controls. • Emax and Emean were different among CKD patients with different pathological stages. • The Emax value for STE was positively related to serum creatinine, β2-microglobulin.

Correlation of shear-wave elastography parameters with the molecular subtype and axillary lymph node status in breast cancer

PURPOSE

To examine correlations between shear-wave elastography (SWE) parameters with molecular subtype and axillary lymph node (LN) status of breast cancer.

METHODS

We retrospectively analyzed 545 consecutive women (mean age, 52.7 ± 10.7 years; range, 26-83) with breast cancer who underwent preoperative breast ultrasound with SWE between December 2019 and January 2021. SWE parameters (E_max, E_mean, and E_ratio) and the histopathologic information from surgical specimens including histologic type, histologic grade, size of invasive cancer, hormone receptor and HER2 status, Ki-67 proliferation index, and axillary LN status were analyzed. The relationships between SWE parameters and histopathologic findings were analyzed using an independent sample t-test, one-way ANOVA test with Tukey's post hoc test, and logistic regression analyses.

RESULTS

Higher stiffness values of SWE were associated with larger lesion size (>20 mm) on ultrasound, high histologic grade, larger invasive cancer size (>20 mm), high Ki-67, and axillary LN metastasis. E_max and E_mean were the lowest in the luminal A-like subtype, and all three parameters were the highest in the triple-negative subtype. Lower value of E_max was independently associated with the luminal A-like subtype (P = 0.04). Higher value of E_mean was independently associated with axillary LN metastasis for tumors ≤ 20 mm (P = 0.03).

CONCLUSION

Increases in the tumor stiffness values on SWE were significantly associated with aggressive histopathologic features of breast cancer. Lower stiffness values were associated with the luminal A-like subtype, and tumors with higher stiffness values were associated with axillary LN metastasis in small breast cancers.

The Utility of Quantitative Parameters of Shear-Wave Elastography to Predict Prognostic Histologic Features of Breast Cancer

ABSTRACT

In this study, we aimed to investigate the correlation of stiffness values of shear-wave elastography (SWE) and histopathological prognostic factors in patients with breast cancer. Between January 2021 and June 2022, SWE images of 138 core-biopsy proven breast cancer lesions from 132 patients were retrospectively reviewed. Histopathogic prognostic factors, including tumor size, histologic grade, histologic type, hormone receptor positivity, human epidermal growth factor receptor (HER2) status, immunohistochemical subtype and Ki-67 index were documented. Elasticity values including mean and maximum elasticity ( Emean and Emax ) and lesion-to-fat ratio ( Eratio ) were recorded. The association between histopathological prognostic factors and elasticity values were assessed using Mann-Whitney U and Kruskal-Wallis test, and multiple linear regression analysis. Tumor size, histological grade, and Ki-67 index were significantly associated with the Eratio ( P < 0.05). Larger tumor size and higher Ki-67 index also showed significantly higher Emean and Emax values ( P < 0.05). However, hormone receptor positivity, HER2 status, and immunohistochemical subtype were not significantly associated with elasticity values ( P > 0.05). Multivariate logistic regression analysis revealed that tumor size was significantly associated with Emean , Emax , and Eratio values ( P < 0.05). A high Ki-67 index was also significantly associated with high Eratio values. Larger tumor size and higher Ki-67 index are independently associated with high Eratio values. Preoperative SWE may improve the performance of conventional ultrasound in predicting prognosis and treatment planning.

Clinical Application of Shear Wave Elastography With Shear Wave Dispersion Imaging in the Preoperative Evaluation of Hepatic Parenchyma in Patients With Liver Tumors

OBJECTIVES

This study aimed to compare the diagnostic accuracy of shear wave elastography (SWE) with that of shear wave dispersion (SWD) in evaluation of hepatic parenchyma in patients with liver tumors before resection.

METHODS

A total of 174 patients with liver tumors were prospectively enrolled. SWE and SWD examinations were performed. Fibrosis stage and necroinflammatory activity were determined histopathologically according to the Scheuer standard. We compared the diagnostic accuracy of SWE and SWD.

RESULTS

Both SWE and SWD values of the liver were highly correlated with liver fibrosis stage (P < .05, respectively). Both SWE and SWD values of the liver were moderately correlated with necroinflammatory activity (P < .05, respectively). Both SWE and SWD values of the liver were not correlated with steatosis (P > .05, respectively). Both SWE and SWD values were significantly different among the patients with different stages of liver fibrosis (P < .001, respectively). The area under the receiver operating characteristic (ROC) curve of SWE value was 0.982, 0.977, 0.969, and 0.984 for predicting S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The optimal cutoff SWE values were 6.9, 7.9, 8.7, and 10.6 kPa for S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The area under the ROC curve of SWD value was 0.967, 0.960, 0.925, and 0.954 for predicting S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The optimal cutoff SWD values were 11.2, 12.0, 13.2, and 16.0 m/s/kHz for S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively.

CONCLUSIONS

SWE and SWD could be noninvasive and accurate for predicting the stage of liver fibrosis in patients with liver tumors before surgery. SWE was more accurate than SWD in predicting severe fibrosis (S ≥ 3) and cirrhosis (S = 4).

Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study

OBJECTIVES

To establish a breast lesion risk stratification system using ultrasound images to predict breast malignancy and assess Breast Imaging Reporting and Data System (BI-RADS) categories simultaneously.

METHODS

This multicenter study prospectively collected a dataset of ultrasound images for 5012 patients at thirty-two hospitals from December 2018 to December 2020. A deep learning (DL) model was developed to conduct binary categorization (benign and malignant) and BI-RADS categories (2, 3, 4a, 4b, 4c, and 5) simultaneously. The training set of 4212 patients and the internal test set of 416 patients were from thirty hospitals. The remaining two hospitals with 384 patients were used as an external test set. Three experienced radiologists performed a reader study on 324 patients randomly selected from the test sets. We compared the performance of the DL model with that of three radiologists and the consensus of the three radiologists.

RESULTS

In the external test set, the DL model achieved areas under the receiver operating characteristic curve (AUCs) of 0.980 and 0.945 for the binary categorization and six-way categorizations, respectively. In the reader study set, the DL BI-RADS categories achieved a similar AUC (0.901 vs. 0.933, p = 0.0632), sensitivity (90.98% vs. 95.90%, p = 0.1094), and accuracy (83.33% vs. 79.01%, p = 0.0541), but higher specificity (78.71% vs. 68.81%, p = 0.0012) than those of the consensus of the three radiologists.

CONCLUSIONS

The DL model performed well in distinguishing benign from malignant breast lesions and yielded outcomes similar to experienced radiologists. This indicates the potential applicability of the DL model in clinical diagnosis.

KEY POINTS

• The DL model can achieve binary categorization for benign and malignant breast lesions and six-way BI-RADS categorizations for categories 2, 3, 4a, 4b, 4c, and 5, simultaneously. • The DL model showed acceptable agreement with radiologists for the classification of breast lesions. • The DL model performed well in distinguishing benign from malignant breast lesions and had promise in helping reduce unnecessary biopsies of BI-RADS 4a lesions.

The Potential of Shear Wave Elastography to Reduce Unnecessary Biopsies in Breast Cancer Diagnosis: An International, Diagnostic, Multicenter Trial

PURPOSE

 In this prospective, multicenter trial we evaluated whether additional shear wave elastography (SWE) for patients with BI-RADS 3 or 4 lesions on breast ultrasound could further refine the assessment with B-mode breast ultrasound for breast cancer diagnosis.

MATERIALS AND METHODS

 We analyzed prospective, multicenter, international data from 1288 women with breast lesions rated by conventional 2 D B-mode ultrasound as BI-RADS 3 to 4c and undergoing 2D-SWE. After reclassification with SWE the proportion of undetected malignancies should be < 2 %. All patients underwent histopathologic evaluation (reference standard).

RESULTS

 Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6 %). The assessment with B-mode breast ultrasound resulted in 1.39 % (6 of 431) undetected malignancies (malignant lesions in BI-RADS 3) and 53.80 % (495 of 920) unnecessary biopsies (biopsies in benign lesions). Re-classifying BI-RADS 4a patients with a SWE cutoff of 2.55 m/s resulted in 1.98 % (11 of 556) undetected malignancies and a reduction of 24.24 % (375 vs. 495) of unnecessary biopsies.

CONCLUSION

 A SWE value below 2.55 m/s for BI-RADS 4a lesions could be used to downstage these lesions to follow-up, and therefore reduce the number of unnecessary biopsies by 24.24 %. However, this would come at the expense of some additionally missed cancers compared to B-mode breast ultrasound (rate of undetected malignancies 1.98 %, 11 of 556, versus 1.39 %, 6 of 431) which would, however, still be in line with the ACR BI-RADS 3 definition (< 2 % of undetected malignancies).

Reconstructing the Spatial Distribution of the Relative Shear Modulus in Quasi-static Ultrasound Elastography: Plane Stress Analysis

Quasi-static ultrasound elastography (QSUE) is an imaging technique that mainly provides axial strain maps of tissues when the latter are subjected to compression. In this article, a method for reconstructing the relative shear modulus distribution within a linear elastic and isotropic medium, in QSUE, is introduced. More specifically, the plane stress inverse problem is considered. The proposed method is based on the variational formulation of the equilibrium equations and on the choice of adapted discretization spaces, and only requires displacement fields in the analyzed media to be determined. Results from plane stress and 3-D numerical simulations, as well as from phantom experiments, showed that the method is able to reconstruct the different regions within a medium, with shear modulus contrasts that unambiguously reveal whether inclusions are stiffer or softer than the surrounding material. More specifically, for the plane stress simulations, inclusion-to-background modulus ratios were found to be very accurately estimated, with an error lower than 3%. For the 3-D simulations, for which the plane stress conditions are no longer satisfied, these ratios were, as expected, less accurate, with an error that remained lower than 10% for two of the three cases analyzed but was around 34% for the last case. Concerning the phantom experiments, a comparison with a shear wave elastography technique from a clinical ultrasound scanner was also made. Overall, the inclusion-to-background shear modulus ratios obtained with our approach were found to be closer to those given by the phantom manufacturer than the ratios provided by the clinical system.

Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions

OBJECTIVES

We evaluated whether lesion-to-fat ratio measured by shear wave elastography in patients with Breast Imaging Reporting and Data System (BI-RADS) 3 or 4 lesions has the potential to further refine the assessment of B-mode ultrasound alone in breast cancer diagnostics.

METHODS

This was a secondary analysis of an international diagnostic multicenter trial (NCT02638935). Data from 1288 women with breast lesions categorized as BI-RADS 3 and 4a-c by conventional B-mode ultrasound were analyzed, whereby the focus was placed on differentiating lesions categorized as BI-RADS 3 and BI-RADS 4a. All women underwent shear wave elastography and histopathologic evaluation functioning as reference standard. Reduction of benign biopsies as well as the number of missed malignancies after reclassification using lesion-to-fat ratio measured by shear wave elastography were evaluated.

RESULTS

Breast cancer was diagnosed in 368 (28.6%) of 1288 lesions. The assessment with conventional B-mode ultrasound resulted in 53.8% (495 of 1288) pathologically benign lesions categorized as BI-RADS 4 and therefore false positives as well as in 1.39% (6 of 431) undetected malignancies categorized as BI-RADS 3. Additional lesion-to-fat ratio in BI-RADS 4a lesions with a cutoff value of 1.85 resulted in 30.11% biopsies of benign lesions which correspond to a reduction of 44.04% of false positives.

CONCLUSIONS

Adding lesion-to-fat ratio measured by shear wave elastography to conventional B-mode ultrasound in BI-RADS 4a breast lesions could help reduce the number of benign biopsies by 44.04%. At the same time, however, 1.98% of malignancies were missed, which would still be in line with American College of Radiology BI-RADS 3 definition of <2% of undetected malignancies.