Monitoring structural changes in cells with high-frequency ultrasound signal statistics

Tunis, Adam S.; Czarnota, G.J.; Giles, Anoja; Sherar, Michael D.; Hunt, J.W.; Kolios, Michael C.

doi:10.1016/j.ultrasmedbio.2005.04.020

Cited by 111 publications

(110 citation statements)

References 27 publications

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“…Ultrasound radiofrequency data analysis was conducted using linear regression analysis of the normalized power spectrum (7)(8)(9)(10)(11)(12)(13)(14)(15)(17)(18)(19)(20). Ultrasound data was analyzed across all acquired planes through the scan volume which included identifiable tumor regions.…”

Section: Discussionmentioning

confidence: 99%

“…This was carried out to more accurately account for the effects of attenuation and beam diffraction across the ROI especially in larger tumors. Statistical analysis was carried out on parametric images via probability density function estimation of histogram of the MBF intensity by fitting a generalized gamma distribution (10).…”

Section: Discussionmentioning

confidence: 99%

“…Patients 1,4,5,7,8,10,13,14,15,16,18,19,20,21,23, and 24 had either a complete pathologic response or had substantial reductions in their tumor size along with decreases in tumor cellularity and were categorized as responders. In the case of patients 2 and 17, the reduction in physical tumor or mass size was less than 30%; however, residual tumor cellularity was very low and these patients were clinically/pathologically classified as responders.…”

Section: Patient Characteristics and Clinical/pathologic Treatment Rementioning

confidence: 99%

“…Research into the potential of ultrasound to monitor noninvasively the effects of cancer therapy administration was initially conducted using high-frequency ultrasound and showed its capacity to detect changes in tissue microstructure associated with a variety of cancer therapies in in vitro, in situ, and in vivo models (7)(8)(9)(10)(11)(12)(13)(14). Initial in vitro observations indicated increases in tissue echogenicity in acute myeloid leukemia cells exposed to the chemotherapeutic agent cisplatin (7,8).…”

Section: Introductionmentioning

confidence: 99%

“…Initial in vitro observations indicated increases in tissue echogenicity in acute myeloid leukemia cells exposed to the chemotherapeutic agent cisplatin (7,8). Further research used quantitative ultrasound techniques such as spectroscopic analysis of radiofrequency data and statistical analysis of the signal envelope to quantify the effects of treatment in a variety of concentration and exposure-dependent experiments (9,10). To date, high-frequency ultrasound has been used to detect apoptotic cell death resulting from photodynamic, X-ray radiation, and ultrasonically activated antivascular microbubble therapies in a variety of in vivo mouse models (12)(13)(14).…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Ultrasound Evaluation of Tumor Cell Death Response in Locally Advanced Breast Cancer Patients Receiving Chemotherapy

Sadeghi‐Naini

Papanicolau

Falou

et al. 2013

Clinical Cancer Research

113

114

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Purpose: Quantitative ultrasound techniques have been recently shown to be capable of detecting cell death through studies conducted on in vitro and in vivo models. This study investigates for the first time the potential of early detection of tumor cell death in response to clinical cancer therapy administration in patients using quantitative ultrasound spectroscopic methods.Experimental Design: Patients (n ¼ 24) with locally advanced breast cancer received neoadjuvant chemotherapy treatments. Ultrasound data were collected before treatment onset and at 4 times during treatment (weeks 1, 4, and 8, and preoperatively). Quantitative ultrasound parameters were evaluated for clinically responsive and nonresponding patients.Results: Results indicated that quantitative ultrasound parameters showed significant changes for patients who responded to treatment, and no similar alteration was observed in treatment-refractory patients. Such differences between clinically and pathologically determined responding and nonresponding patients were statistically significant (P < 0.05) after 4 weeks of chemotherapy. Responding patients showed changes in parameters related to cell death with, on average, an increase in mid-band fit and 0-MHz intercept of 9.1 AE 1.2 dBr and 8.9 AE 1.9 dBr , respectively, whereas spectral slope was invariant. Linear discriminant analysis revealed a sensitivity of 100% and a specificity of 83.3% for distinguishing nonresponding patients by the fourth week into a course of chemotherapy lasting several months.Conclusion: This study reports for the first time that quantitative ultrasound spectroscopic methods can be applied clinically to evaluate cancer treatment responses noninvasively. The results form a basis for monitoring chemotherapy effects and facilitating the personalization of cancer treatment.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Patient Characteristics and Clinical/pathologic Treatment Rementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quantitative Ultrasound Evaluation of Tumor Cell Death Response in Locally Advanced Breast Cancer Patients Receiving Chemotherapy

Sadeghi‐Naini

Papanicolau

Falou

et al. 2013

Clinical Cancer Research

113

114

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Clinical Feasibility of Quantitative Ultrasound Texture Analysis: A Robustness Study Using Fetal Lung Ultrasound Images

Perez‐Moreno

Domínguez

Gratacós

et al. 2018

J of Ultrasound Medicine

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Objectives To compare the robustness of several methods based on quantitative ultrasound (US) texture analysis to evaluate its feasibility for extracting features from US images to use as a clinical diagnostic tool. Methods We compared, ranked, and validated the robustness of 5 texture‐based methods for extracting textural features from US images acquired under different conditions. For comparison and ranking purposes, we used 13,171 non‐US images from widely known available databases (OUTEX [University of Oulu, Oulu, Finland] and PHOTEX [Texture Lab, Heriot‐Watt University, Edinburgh, Scotland]), which were specifically acquired under different controlled parameters (illumination, resolution, and rotation) from 103 textures. The robustness of those methods with better results from the non‐US images was validated by using 666 fetal lung US images acquired from singleton pregnancies. In this study, 2 similarity measurements (correlation and Chebyshev distances) were used to evaluate the repeatability of the features extracted from the same tissue images. Results Three of the 5 methods (gray‐level co‐occurrence matrix, local binary patterns, and rotation‐invariant local phase quantization) had favorably robust performance when using the non‐US database. In fact, these methods showed similarity values close to 0 for the acquisition variations and delineations. Results from the US database confirmed robustness for all of the evaluated methods (gray‐level co‐occurrence matrix, local binary patterns, and rotation‐invariant local phase quantization) when comparing the same texture obtained from different regions of the image (proximal/distal lungs and US machine brand stratification). Conclusions Our results confirmed that texture analysis can be robust (high similarity for different condition acquisitions) with potential to be included as a clinical tool.

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Preclinical Liver Metastases: Three-Dimensional High-Frequency Ultrasound Imaging

Graham¹,

Wirtzfeld²,

Lacefield³

et al. 2009

Liver Cancer

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Monitoring structural changes in cells with high-frequency ultrasound signal statistics

Cited by 111 publications

References 27 publications

Quantitative Ultrasound Evaluation of Tumor Cell Death Response in Locally Advanced Breast Cancer Patients Receiving Chemotherapy

Quantitative Ultrasound Evaluation of Tumor Cell Death Response in Locally Advanced Breast Cancer Patients Receiving Chemotherapy

Clinical Feasibility of Quantitative Ultrasound Texture Analysis: A Robustness Study Using Fetal Lung Ultrasound Images

Preclinical Liver Metastases: Three-Dimensional High-Frequency Ultrasound Imaging

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