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Predicting breast cancer with ultrasound and mammography
ABSTRACTS OF NIH GRANTS
Academic Radiology, Vol 10, No 10, October 2003
and may reduce the cost and morbidity of unnecessary surgical biopsies.
nostic accuracy for these cases of microcalcification clusters will thus have an important and immediate impact.
Thesaurus Terms: artificial intelligence, biomedical equipment development, breast neoplasm/cancer diagnosis, diagnosis design/evaluation, diagnosis quality/standard, mammography, neoplasm/cancer invasiveness case history, computer human interaction, health care cost/financing, noninvasive diagnosis, prognosis bioimaging/biomedical imaging, clinical research, human data
Thesaurus Terms: breast neoplasm, calcification, computer assisted diagnosis, diagnosis design/evaluation, mammography computer simulation, computer system design/evaluation, model design/development biopsy, human data
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Duke University Durham, NC 27706 2002 Radiology 01-Jul-1998 30-Jun-2003 National Cancer Institute RNM
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Duke University Durham, NC 27706 2002 Radiology 01-Jul-2001 30-Jun-2003 National Cancer Institute DMG
PREDICTING BREAST CANCER WITH ULTRASOUND AND MAMMOGRAPHY
IMPROVED DIAGNOSIS OF BREAST MICROCALCIFICATION CLUSTERS
Grant Number: PI Name:
Grant Number: PI Name:
Abstract: Description (Provided by Applicant): The purpose of this study is to increase the specificity of breast biopsy by building computer models which combine both mammography and breast ultrasound (US) findings to identify probably benign breast masses. In current clinical practice, breast US is used only to distinguish between fluid-filled cysts vs. solid masses. The proposed artificial neural network (ANN) model would go one step further and quantitatively identify probably benign cases, which may undergo short-term follow-up in lieu of biopsy. The hypothesis is that by combining information from both modalities, the model will be more robust and more accurate than those based upon either modality alone, and be able to improve upon the performance of the radiologists. In preliminary studies, ANN models successfully identified probably benign breast masses using just mammographic findings or just US findings. The specific aims of the proposed study are to: 1. Prospectively collect data for 300 cases of biopsy-proven breast lesions for which mammography and ultrasound (US) data are both available. 2. Optimize artificial neural network (ANN) models to identify probably lesions based on US findings only. 3. Develop unified models to identify probably benign lesions using both US and mammography findings. 4. Perform statistical analysis to evaluate contribution of US findings to the diagnostic performances of radiologists and ANN models. The immediate benefit of this proposal is a computer-based decision aid to improve the specificity of breast biopsy and thus reduce the cost associated with benign biopsies. This proposal has the potential to reduce significantly the number of unnecessary breast biopsies and their associated cost, physical pain, and emotional distress to the patient.
5R21CA092573-02 Lo, Joseph Y.
Abstract: the purpose of this study is to develop computer models to increase the specificity of breast biopsy by improving the diagnosis of microcalcifications in mammograms. Probably benign cases may undergo short-term follow-up in lieu of biopsy. To accomplish these goals, computer models will merge together three complementary sources of diagnostic information: radiologist-extracted mammographic findings, patient history data, and computer-extracted I features from local histogram thresholding applied to digitized mammograms. The specific aims of the proposed study are to: (1) Optimize predictive models to identify probably benign microcalcification clusters based upon radiologist-extracted findings and history data. (2) Design new predictive models based upon computer-extracted features from local histogram analysis. (3) Construct and evaluate a unified malignancy predictor which combines the different information provided by the separate models. In preliminary studies, an ANN identified probably benign cases of clustered microcalcifications using BI-RADS findings and history data as inputs to the model. In addition, a local histogram thresholding technique was used to segment microcalcification clusters, and a rule- based system eliminated typically benign clusters. The immediate benefit of this proposal is a computer-based decision aid for the diagnosis of mammographically suspicious lesions with microcalcification clusters. These cases account for 40% of breast biopsies and are arguably the most difficult category to characterize for radiologists and computer models alike. Improvements in diag-
1R21CA093461-01 Lo, Joseph Y.
1209
NCI
Academic Radiology, Vol 10, No 10, October 2003
Thesaurus Terms: breast neoplasm, breast neoplasm/cancer diagnosis, computer assisted diagnosis, computer system design/evaluation, diagnosis design/evaluation artificial intelligence, mammography, mathematical model, model design/ development, ultrasonography female, human data, women’s health
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Duke University Durham, NC 27706 2002 Radiology 01-Mar-2002 29-Feb-2004 National Cancer Institute DMG
SPECKLE-FREE TRANSMISSION ULTRASOUND FOR BREAST IMAGING Grant Number: PI Name:
1R21CA091803-01A1 Lo, Shih-Chung B.
Abstract: Description (provided by applicant): It is known that the inability to correctly identify breast cancer in women with glandular and dense breasts is in part due to the overlap in tissues at different depths that conceal contained masses. Dense breasts are most common in younger women. In this group the sensitivity of mammography is less. We propose to adapt a newly invented C-scan ultrasound technology to develop a tomographic system that potentially can improve the visualization of cancerous masses and abnormalities in dense breast tissues. The system proposed is a real-time Cscan transmission ultrasound camera. Unlike conventional ultrasound, the proposed system produces speckle-free images striking for their radiographic appearance. Conventional ultrasound creates images based on the speed of sound transmission through tissues. The proposed system creates its images based on the tissue attenuation of sound, a separate physical parameter that can provide new information about the breast since sound transmission speed and attenuation of sound are not closely correlated. In addition, the proposed system combines the advantages of traditional mammogram imaging with the ability of ultrasound to resolve soft tissue layers. Evaluation of the proposed system will be performed on three levels: a technical system evaluation using breast phantoms, in-vitro study using breast specimens, and an invivo study involving a population of a minimum of 50 patients. This project aims at the development of a novel clinically viable system tailored to imaging human breasts for screening, diagnostic, and biopsy procedures. We believe that the high quality, high-resolution images coupled with tomographic capability will decrease the number of breast cancers that are currently missed. Specific tasks completed as
1210
a part of R21 are (1) evaluation of the existing laboratory system with recommendations for adaptation to breast imaging and (2) fabrication of a clinical prototype suitable for use by clinical personnel. Tasks completed as a part of R33 are (1) verification of clinical viability through breast phantom, in-vitro, and in-vivo studies, (2) definition of clinical protocols for breast cancer screening and diagnosis, and (3) verification of suitability in image-guided breast tissue biopsy procedures. Thesaurus Terms: image enhancement, mammary gland, technology/technique development, tomography, ultrasound imaging/scanning biopsy, breast neoplasm/cancer diagnosis, calcification, fine needle aspiration, fluoroscopy, imaging/ visualization/scanning, mammography, tissue bioimaging/ biomedical imaging, clinical research, female, human subject, women’s health
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Georgetown University Washington, DC 20057 2002 Radiology 01-May-2002 30-Apr-2004 National Cancer Institute ZCA1
IMRT FOR GYNECOLOGICAL MALIGNANCIES Grant Number: PI Name:
5R01CA084409-03 Low, Daniel A.
Abstract: A therapy protocol, applicator guided intensity modulated radiation therapy (AGIMRT), is proposed for locally advanced cervical cancers (LACC). This novel radiation therapy modality can provide highly conformal and accurately localized external beam therapy as an alternative to high-dose rate (HDR) brachytherapy treatments. A brachytherapy applicator substitute is designed which provides an accurate, reproducible method for determining the tumor and critical structure locations relative to the applicator. Magnetic resonance imaging techniques will be modified to minimize spatial distortions and used to accurately map the applicator and surrounding soft tissues. The applicator substitute allows alignment of the tumor and organs to an IMRT treatment device, which can generate dose distributions superior to those produced using sealed-source intracavitary brachytherapy. AGIMRT treatment plans will have customized concave dose distributions that simultaneously deliver optimal tumor coverage and critical structure sparing. Two multidimensional dosimeters, Radiochromic film and BANG (Bis, Acrylamide, Nitrogen, and Gelatin) gel, will be benchmarked and calibrated to measure the expected steep dose gradients
Academic Radiology, Vol 10, No 10, October 2003
and may reduce the cost and morbidity of unnecessary surgical biopsies.
nostic accuracy for these cases of microcalcification clusters will thus have an important and immediate impact.
Thesaurus Terms: artificial intelligence, biomedical equipment development, breast neoplasm/cancer diagnosis, diagnosis design/evaluation, diagnosis quality/standard, mammography, neoplasm/cancer invasiveness case history, computer human interaction, health care cost/financing, noninvasive diagnosis, prognosis bioimaging/biomedical imaging, clinical research, human data
Thesaurus Terms: breast neoplasm, calcification, computer assisted diagnosis, diagnosis design/evaluation, mammography computer simulation, computer system design/evaluation, model design/development biopsy, human data
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Duke University Durham, NC 27706 2002 Radiology 01-Jul-1998 30-Jun-2003 National Cancer Institute RNM
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Duke University Durham, NC 27706 2002 Radiology 01-Jul-2001 30-Jun-2003 National Cancer Institute DMG
PREDICTING BREAST CANCER WITH ULTRASOUND AND MAMMOGRAPHY
IMPROVED DIAGNOSIS OF BREAST MICROCALCIFICATION CLUSTERS
Grant Number: PI Name:
Grant Number: PI Name:
Abstract: Description (Provided by Applicant): The purpose of this study is to increase the specificity of breast biopsy by building computer models which combine both mammography and breast ultrasound (US) findings to identify probably benign breast masses. In current clinical practice, breast US is used only to distinguish between fluid-filled cysts vs. solid masses. The proposed artificial neural network (ANN) model would go one step further and quantitatively identify probably benign cases, which may undergo short-term follow-up in lieu of biopsy. The hypothesis is that by combining information from both modalities, the model will be more robust and more accurate than those based upon either modality alone, and be able to improve upon the performance of the radiologists. In preliminary studies, ANN models successfully identified probably benign breast masses using just mammographic findings or just US findings. The specific aims of the proposed study are to: 1. Prospectively collect data for 300 cases of biopsy-proven breast lesions for which mammography and ultrasound (US) data are both available. 2. Optimize artificial neural network (ANN) models to identify probably lesions based on US findings only. 3. Develop unified models to identify probably benign lesions using both US and mammography findings. 4. Perform statistical analysis to evaluate contribution of US findings to the diagnostic performances of radiologists and ANN models. The immediate benefit of this proposal is a computer-based decision aid to improve the specificity of breast biopsy and thus reduce the cost associated with benign biopsies. This proposal has the potential to reduce significantly the number of unnecessary breast biopsies and their associated cost, physical pain, and emotional distress to the patient.
5R21CA092573-02 Lo, Joseph Y.
Abstract: the purpose of this study is to develop computer models to increase the specificity of breast biopsy by improving the diagnosis of microcalcifications in mammograms. Probably benign cases may undergo short-term follow-up in lieu of biopsy. To accomplish these goals, computer models will merge together three complementary sources of diagnostic information: radiologist-extracted mammographic findings, patient history data, and computer-extracted I features from local histogram thresholding applied to digitized mammograms. The specific aims of the proposed study are to: (1) Optimize predictive models to identify probably benign microcalcification clusters based upon radiologist-extracted findings and history data. (2) Design new predictive models based upon computer-extracted features from local histogram analysis. (3) Construct and evaluate a unified malignancy predictor which combines the different information provided by the separate models. In preliminary studies, an ANN identified probably benign cases of clustered microcalcifications using BI-RADS findings and history data as inputs to the model. In addition, a local histogram thresholding technique was used to segment microcalcification clusters, and a rule- based system eliminated typically benign clusters. The immediate benefit of this proposal is a computer-based decision aid for the diagnosis of mammographically suspicious lesions with microcalcification clusters. These cases account for 40% of breast biopsies and are arguably the most difficult category to characterize for radiologists and computer models alike. Improvements in diag-
1R21CA093461-01 Lo, Joseph Y.
1209
NCI
Academic Radiology, Vol 10, No 10, October 2003
Thesaurus Terms: breast neoplasm, breast neoplasm/cancer diagnosis, computer assisted diagnosis, computer system design/evaluation, diagnosis design/evaluation artificial intelligence, mammography, mathematical model, model design/ development, ultrasonography female, human data, women’s health
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Duke University Durham, NC 27706 2002 Radiology 01-Mar-2002 29-Feb-2004 National Cancer Institute DMG
SPECKLE-FREE TRANSMISSION ULTRASOUND FOR BREAST IMAGING Grant Number: PI Name:
1R21CA091803-01A1 Lo, Shih-Chung B.
Abstract: Description (provided by applicant): It is known that the inability to correctly identify breast cancer in women with glandular and dense breasts is in part due to the overlap in tissues at different depths that conceal contained masses. Dense breasts are most common in younger women. In this group the sensitivity of mammography is less. We propose to adapt a newly invented C-scan ultrasound technology to develop a tomographic system that potentially can improve the visualization of cancerous masses and abnormalities in dense breast tissues. The system proposed is a real-time Cscan transmission ultrasound camera. Unlike conventional ultrasound, the proposed system produces speckle-free images striking for their radiographic appearance. Conventional ultrasound creates images based on the speed of sound transmission through tissues. The proposed system creates its images based on the tissue attenuation of sound, a separate physical parameter that can provide new information about the breast since sound transmission speed and attenuation of sound are not closely correlated. In addition, the proposed system combines the advantages of traditional mammogram imaging with the ability of ultrasound to resolve soft tissue layers. Evaluation of the proposed system will be performed on three levels: a technical system evaluation using breast phantoms, in-vitro study using breast specimens, and an invivo study involving a population of a minimum of 50 patients. This project aims at the development of a novel clinically viable system tailored to imaging human breasts for screening, diagnostic, and biopsy procedures. We believe that the high quality, high-resolution images coupled with tomographic capability will decrease the number of breast cancers that are currently missed. Specific tasks completed as
1210
a part of R21 are (1) evaluation of the existing laboratory system with recommendations for adaptation to breast imaging and (2) fabrication of a clinical prototype suitable for use by clinical personnel. Tasks completed as a part of R33 are (1) verification of clinical viability through breast phantom, in-vitro, and in-vivo studies, (2) definition of clinical protocols for breast cancer screening and diagnosis, and (3) verification of suitability in image-guided breast tissue biopsy procedures. Thesaurus Terms: image enhancement, mammary gland, technology/technique development, tomography, ultrasound imaging/scanning biopsy, breast neoplasm/cancer diagnosis, calcification, fine needle aspiration, fluoroscopy, imaging/ visualization/scanning, mammography, tissue bioimaging/ biomedical imaging, clinical research, female, human subject, women’s health
Institution: Fiscal Year: Department: Project Start: Project End: ICD: IRG:
Georgetown University Washington, DC 20057 2002 Radiology 01-May-2002 30-Apr-2004 National Cancer Institute ZCA1
IMRT FOR GYNECOLOGICAL MALIGNANCIES Grant Number: PI Name:
5R01CA084409-03 Low, Daniel A.
Abstract: A therapy protocol, applicator guided intensity modulated radiation therapy (AGIMRT), is proposed for locally advanced cervical cancers (LACC). This novel radiation therapy modality can provide highly conformal and accurately localized external beam therapy as an alternative to high-dose rate (HDR) brachytherapy treatments. A brachytherapy applicator substitute is designed which provides an accurate, reproducible method for determining the tumor and critical structure locations relative to the applicator. Magnetic resonance imaging techniques will be modified to minimize spatial distortions and used to accurately map the applicator and surrounding soft tissues. The applicator substitute allows alignment of the tumor and organs to an IMRT treatment device, which can generate dose distributions superior to those produced using sealed-source intracavitary brachytherapy. AGIMRT treatment plans will have customized concave dose distributions that simultaneously deliver optimal tumor coverage and critical structure sparing. Two multidimensional dosimeters, Radiochromic film and BANG (Bis, Acrylamide, Nitrogen, and Gelatin) gel, will be benchmarked and calibrated to measure the expected steep dose gradients