Monitoring Progression of Ductal Carcinoma In Situ Using Photoacoustics and Contrast-Enhanced Ultrasound.

Breast cancer is the leading form of cancer in women, accounting for approximately 41,400 deaths in 2018. While a variety of risk factors have been identified, physical exercise has been linked to reducing both the risk and aggressiveness of breast cancer. Within breast cancer, ductal carcinoma in situ (DCIS) is a common finding. However, less than 25% of DCIS tumors actually progress into invasive breast cancer, resulting in overtreatment. This overtreatment is due to a lack of predictive precursors to assess aggressiveness and development of DCIS. We hypothesize that tissue oxygenation and perfusion measured by photoacoustic and contrast-enhanced ultrasound imaging, respectively, can predict DCIS aggressiveness. To test this, 20 FVB/NJ and 20 SV40Tag mice that genetically develop DCIS-like breast cancers were divided evenly into exercise and control groups and imaged over the course of 6 weeks. Tissue oxygenation was a predictive precursor to invasive breast cancer for FVB/NJ mice (P = 0.015) in the early stages of tumor development. Meanwhile, perfusion results were inconclusive (P \u3e 0.2) as a marker for disease progression. Moreover, voluntary physical exercise resulted in lower weekly tumor growth and significantly improved median survival (P = 0.014)

Evaluation of Hepatocellular Carcinoma Transarterial Chemoembolization using Quantitative Analysis of 2D and 3D Real-time Contrast Enhanced Ultrasound.

Quantitative 2D and 3D contrast-enhanced ultrasound (CEUS) was assessed to evaluate early transarterial chemoembolization (TACE) treatment response. Seventeen patients scheduled for TACE for the treatment of hepatocellular carcinoma participated in the study. 2D and 3D CEUS were performed for each patient at three time points: Prior to TACE, 1-2 weeks post TACE, and 1 month post TACE. Peak-intensities of the tumor and surrounding liver tissue were calculated from 2D and 3D data before and after TACE and used to evaluate tumor treatment response. Residual tumor percentages were calculated from 2D and 3D CEUS acquired 1-2 weeks and 1 month post TACE and compared with results from MRI 1 month post TACE. Nine subjects had complete response while 8 had incomplete response. Peak-intensities of the tumor from 3D CEUS prior to TACE were similar between the complete and incomplete treatment groups (p = 0.70), while 1-2 weeks (p \u3c 0.01) and 1 month post treatment (p \u3c 0.01) were significantly lower in the complete treatment group than in the incomplete treatment group. For 2D CEUS, only the peak-intensity values of the tumor from 1 month post TACE were significantly different (p \u3c 0.01). The correlation coefficients between 2D and 3D residual tumor estimates 1-2 weeks post TACE and the estimates from MRI were 0.73 and 0.94, respectively, while those from 2D and 3D CEUS 1 month post TACE were 0.66 and 0.91, respectively. Quantitative analysis on 2D and 3D CEUS shows potential to differentiate patients with complete versus incomplete response to TACE as early as 1-2 weeks post treatment

Ultrasound Quantitative Assessment of Ventral Finger Microvasculopathy in Systemic Sclerosis With Raynaud’s Phenomena: A Comparative Study

Objective: To assess the finger vascularity of systemic sclerosis patients with Raynaud\u27s phenomenon (RP-SSc) using various ultrasound techniques. Methods: All fingers (except thumbs) of 18 RP-SSc patients and 18 controls were imaged at room temperature using four ultrasound vascular imaging techniques. The percent vascular area was quantified by counting blood flow pixels in a 25 mm2 square centred at the nail fold for the dorsal side and in 25 mm2 and 100 mm2 square from the fingertip for the ventral side. The mean vascular intensity was calculated from the corresponding areas for dorsal and ventral sides. Results: The percent vascular areas and mean vascular intensities in RP-SSc were significantly lower than those in controls for both dorsal and ventral sides (p\u3c0.01). The mean vascular intensities showed slightly higher area under the curve (AUC) than the percent vascular areas (0.53-0.91 vs 0.53-0.90) regardless of imaging technique and assessment side. For each imaging technique, the ventral side vascularity showed a higher AUC (0.74-0.91) compared with the dorsal side (0.53-0.81). Moreover, ventral side abnormalities were associated with a history of digital ulcers. Conclusions: Ultrasound demonstrated potential to quantify finger vascularity of RP-SSc. The ventral side of the fingers showed a higher accuracy in detecting RP-SSc than the dorsal side

Characterization of indeterminate breast lesions on B-mode ultrasound using automated machine learning models

Purpose: While mammography has excellent sensitivity for the detection of breast lesions, its specificity is limited. Adjunct screening with ultrasound may partially alleviate this issue, but also increases false positives, resulting in unnecessary biopsies. This study investigated the use of Google AutoML Vision (Mountain View, CA), a commercially available machine learning service, to both identify and characterize indeterminate breast lesions on ultrasound. Methods: B-mode images from 253 independent cases of indeterminate breast lesions scheduled for core biopsy were used for model creation and validation. The performances of two sub-models from AutoML Vision, the image classification model and object detection model were evaluated, while also investigating training strategies to enhance model performances. Pathology from the patient’s biopsy were used as a reference standard. Results: The image classification models trained under different conditions demonstrated areas under the precision recall curve (AUC) ranging from 0.85 to 0.96 during internal validation. Once deployed, the model with highest internal performance demonstrated a sensitivity of 100% (95% confidence interval (CI) of 73.5-100%), specificity of 83.3% (CI=51.6-97.9%), positive predictive value (PPV) of 85.7% (CI=62.9-95.5%), and negative predictive value (NPV) of 100% (CI non-evaluable) in an independent dataset. The object detection model demonstrated lower performance internally during development (AUC=0.67) and during prediction in the independent dataset (sensitivity=75.0% (CI=42.8-94.5), specificity=80.0% (CI=51.9-95.7), PPV=75.0% (CI=50.8-90.0), NPV=80.0% (CI=59.3-91.7%)), but was able to demonstrate the location of the lesion within the image. Conclusions: Two models appear to be useful tools for identifying and classifying suspicious areas on B-mode images of indeterminate breast lesions

Cross-imaging system comparison of backscatter coefficient estimates from a tissue-mimicking material

A key step toward implementing quantitative ultrasound techniques in a clinical setting is demonstrating that parameters such as the ultrasonic backscatter coefficient (BSC) can be accurately estimated independent of the clinical imaging system used. In previous studies, agreement in BSC estimates for well characterized phantoms was demonstrated across different laboratory systems. The goal of this study was to compare the BSC estimates of a tissue mimicking sample measured using four clinical scanners, each providing RF echo data in the 1-15 MHz frequency range. The sample was previously described and characterized with single-element transducer systems. Using a reference phantom for analysis, excellent quantitative agreement was observed across the four array-based imaging systems for BSC estimates. Additionally, the estimates from data acquired with the clinical systems agreed with theoretical predictions and with estimates from laboratory measurements using single-element transducers

Four-Dimensional (4D) Subharmonic Aided Pressure Estimation for Monitoring Neoadjuvant Chemotherapy Response of Breast Cancer

Introduction Neoadjuvant chemotherapy is a well-established treatment option for patients with non-metastatic breast cancer. The patient response is correlated with survival. However, the optimal method for monitoring neoadjuvant therapy response has not been established. One factor that may affect the response of neoadjuvant therapy is the interstitial fluid pressure (IFP). Increased IFP prevents an effective delivery of therapeutic agents and reduces the efficacy of the therapy. Recently, subharmonic-aided pressure estimation (SHAPE) using contrast-enhanced ultrasound (CEUS) has been developed and its potential was demonstrated in animals as a non-invasive technique for IFP measurements. The SHAPE method estimates IFP based on the inverse relationship between the subharmonic signal magnitude from CEUS and IFP. The purpose of this study was to determine if 4D SHAPE can predict the response of breast cancer to neoadjuvant chemotherapy. Poster presented at International Ultrasonics Symposium in Tours France.https://jdc.jefferson.edu/radiologyposters/1001/thumbnail.jp

Ultrasonic Attenuation and Backscatter Coefficient Estimates of Rodent-Tumor-Mimicking Structures: Comparison of Results among Clinical Scanners

In vivo estimations of the frequency-dependent acoustic attenuation (α) and backscatter (η) coefficients using radiofrequency (rf) echoes acquired with clinical ultrasound systems must be independent of the data acquisition setup and the estimation procedures. In a recent in vivo assessment of these parameters in rodent mammary tumors, overall agreement was observed among α and η estimates using data from four clinical imaging systems. In some cases, particularly in highly-attenuating heterogeneous tumors, multisystem variability was observed. This paper compares α and η estimates of a well-characterized rodent-tumor-mimicking homogeneous phantom scanned using seven transducers with the same four clinical imaging systems: a Siemens Acuson S2000, an Ultrasonix RP, a Zonare Z.one and a VisualSonics Vevo2100. α and η estimates of lesion-mimicking spheres in the phantom were independently assessed by three research groups, who analyzed their system's rf echo signals. Imaging-system-based estimates of α and η of both lesion-mimicking spheres were comparable to through-transmission laboratory estimates and to predictions using Faran's theory, respectively. A few notable variations in results among the clinical systems were observed but the average and maximum percent difference between α estimates and laboratory-assessed values was 11% and 29%, respectively. Excluding a single outlier dataset, the average and maximum average difference between η estimates for the clinical systems and values predicted from scattering theory was 16% and 33%, respectively. These results were an improvement over previous interlaboratory comparisons of attenuation and backscatter estimates. Although the standardization of our estimation methodologies can be further improved, this study validates our results from previous rodent breast-tumor model studies.This is an accepted author's manuscript of an article from Ultrasonic Imaging 33 (2011): 233–250, doi:10.1177/016173461103300403. Posted with permission.</p

Cross-imaging system comparison of backscatter coefficient estimates from a tissue-mimicking material

A key step toward implementing quantitative ultrasound techniques in a clinical setting is demonstrating that parameters such as the ultrasonic backscatter coefficient (BSC) can be accurately estimated independent of the clinical imaging system used. In previous studies, agreement in BSC estimates for well characterized phantoms was demonstrated across different laboratory systems. The goal of this study was to compare the BSC estimates of a tissue mimicking sample measured using four clinical scanners, each providing RF echo data in the 1-15 MHz frequency range. The sample was previously described and characterized with single-element transducer systems. Using a reference phantom for analysis, excellent quantitative agreement was observed across the four array-based imaging systems for BSC estimates. Additionally, the estimates from data acquired with the clinical systems agreed with theoretical predictions and with estimates from laboratory measurements using single-element transducers.This article is from Journal of the Acoustical Society of America 132 (2012): 1319–1324, doi:10.1121/1.4742725. Posted with permission.</p