Biomedical subjects

M A Helvie

Publications and source records attributed to M A Helvie.

At least 37 records · Page 2Linked to original sources

PubMed1998

Design of a high-sensitivity classifier based on a genetic algorithm: application to computer-aided diagnosis.

A genetic algorithm (GA) based feature selection method was developed for the design of high-sensitivity classifiers, which were tailored to yield high sensitivity with high specificity. The fitness function of the GA was based on the receiver operating characteristic (ROC) partial area index, which is defined as the average specificity above a given sensitivity threshold. The designed GA evolved towards the selection of feature combinations which yielded high specificity in the high-sensitivity region of the ROC curve, regardless of the performance at low sensitivity. This is a desirable quality of a classifier used for breast lesion characterization, since the focus in breast lesion characterization is to diagnose correctly as many benign lesions as possible without missing malignancies. The high-sensitivity classifier, formulated as the Fisher's linear discriminant using GA-selected feature variables, was employed to classify 255 biopsy-proven mammographic masses as malignant or benign. The mammograms were digitized at a pixel size of 0.1 mm x 0.1 mm, and regions of interest (ROIs) containing the biopsied masses were extracted by an experienced radiologist. A recently developed image transformation technique, referred to as the rubber-band straightening transform, was applied to the ROIs. Texture features extracted from the spatial grey-level dependence and run-length statistics matrices of the transformed ROIs were used to distinguish malignant and benign masses. The classification accuracy of the high-sensitivity classifier was compared with that of linear discriminant analysis with stepwise feature selection (LDAsfs). With proper GA training, the ROC partial area of the high-sensitivity classifier above a true-positive fraction of 0.95 was significantly larger than that of LDAsfs, although the latter provided a higher total area (Az) under the ROC curve. By setting an appropriate decision threshold, the high-sensitivity classifier and LDAsfs correctly identified 61% and 34% of the benign masses respectively without missing any malignant masses. Our results show that the choice of the feature selection technique is important in computer-aided diagnosis, and that the GA may be a useful tool for designing classifiers for lesion characterization.

Algorithms↗

PubMed1998

Computerized characterization of masses on mammograms: the rubber band straightening transform and texture analysis.

A new rubber band straightening transform (RBST) is introduced for characterization of mammographic masses as malignant or benign. The RBST transforms a band of pixels surrounding a segmented mass onto the Cartesian plane (the RBST image). The border of a mammographic mass appears approximately as a horizontal line, and possible speculations resemble vertical lines in the RBST image. In this study, the effectiveness of a set of directional textures extracted from the images before the RBST. A database of 168 mammograms containing biopsy-proven malignant and benign breast masses was digitized at a pixel size of 100 microns x 100 microns. Regions of interest (ROIs) containing the biopsied mass were extracted from each mammogram by an experienced radiologist. A clustering algorithm was employed for automated segmentation of each ROI into a mass object and background tissue. Texture features extracted from spatial gray-level dependence matrices and run-length statistics matrices were evaluated for three different regions and representations: (i) the entire ROI; (ii) a band of pixels surrounding the segmented mass object in the ROI; and (iii) the RBST image. Linear discriminant analysis was used for classification, and receiver operating characteristic (ROC) analysis was used to evaluate the classification accuracy. Using the ROC curves as the performance measure, features extracted from the RBST images were found to be significantly more effective than those extracted from the original images. Features extracted from the RBST images yielded an area (Az) of 0.94 under the ROC curve for classification of mammographic masses as malignant and benign.

Biopsy↗

PubMed1998

Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces.

We are developing computerized feature extraction and classification methods to analyze malignant and benign microcalcifications on digitized mammograms. Morphological features that described the size, contrast, and shape of microcalcifications and their variations within a cluster were designed to characterize microcalcifications segmented from the mammographic background. Texture features were derived from the spatial gray-level dependence (SGLD) matrices constructed at multiple distances and directions from tissue regions containing microcalcifications. A genetic algorithm (GA) based feature selection technique was used to select the best feature subset from the multi-dimensional feature spaces. The GA-based method was compared to the commonly used feature selection method based on the stepwise linear discriminant analysis (LDA) procedure. Linear discriminant classifiers using the selected features as input predictor variables were formulated for the classification task. The discriminant scores output from the classifiers were analyzed by receiver operating characteristic (ROC) methodology and the classification accuracy was quantified by the area, Az, under the ROC curve. We analyzed a data set of 145 mammographic microcalcification clusters in this study. It was found that the feature subsets selected by the GA-based method are comparable to or slightly better than those selected by the stepwise LDA method. The texture features (Az = 0.84) were more effective than morphological features (Az = 0.79) in distinguishing malignant and benign microcalcifications. The highest classification accuracy (Az = 0.89) was obtained in the combined texture and morphological feature space. The improvement was statistically significant in comparison to classification in either the morphological (p = 0.002) or the texture (p = 0.04) feature space alone. The classifier using the best feature subset from the combined feature space and an appropriate decision threshold could correctly identify 35% of the benign clusters without missing a malignant cluster. When the average discriminant score from all views of the same cluster was used for classification, the Az value increased to 0.93 and the classifier could identify 50% of the benign clusters at 100% sensitivity for malignancy. Alternatively, if the minimum discriminant score from all views of the same cluster was used, the Az value would be 0.90 and a specificity of 32% would be obtained at 100% sensitivity. The results of this study indicate the potential of using combined morphological and texture features for computer-aided classification of microcalcifications.

Algorithms↗

PubMed1998

Breast cancer in women who undergo screening mammography: relationship of hormone replacement therapy to stage and detection method.

PURPOSE: To compare the breast cancer stages and detection methods in screened women who receive hormone replacement therapy (HRT) with those in screened women who do not receive HRT to determine whether HRT affects the stage or mammographic detection of malignancy. MATERIALS AND METHODS: One hundred fifteen cases of breast cancer in women (age range, 55-65 years) in whom at least one screening mammogram had been obtained at least 24 months before diagnosis and in whom the history regarding HRT could be determined were reviewed retrospectively. Statistical analysis was performed with CHI-2 analysis and the Fischer exact test. RESULTS: The cancer stages in the 58 women who received HRT were stage 0 in 15 (26%), stage I in 28 (48%), stage II in 13 (22%), and stage III in two (3%) women. The stages in the 57 women who did not receive HRT were stage 0 in 19 (33%), stage I in 24 (42%), stage II in 11 (19%), stage III in two (4%), and stage IV in one (2%) woman. Cancers in 38 (67%) of the women who did not receive HRT and in 38 (66%) of those who did receive HRT were detected with mammography alone; false-negative mammograms were obtained in five (9%) women in the non-HRT group and in four (7%) women in the HRT group (P = .89). CONCLUSION: Among screened women who developed breast cancer, there were no significant differences in cancer stages or in the number of mammographically detected cancers or false-negative mammograms between the HRT group and the non-HRT group.

Breast Neoplasms↗

PubMed1998

Mammographic appearance of recurrent breast carcinoma in six patients with TRAM flap breast reconstructions.

PURPOSE: To determine the mammographic appearance of locally recurrent cancer in patients with breast reconstructions with transverse rectus abdominis musculocutaneous (TRAM) flaps after mastectomy for primary breast cancer. MATERIALS AND METHODS: The mammograms and records of women treated for breast cancer with mastectomy and TRAM flap reconstruction who developed local recurrences from 1995 to 1997 were reviewed retrospectively. Eight cancers were identified in six women. Five women had palpable abnormalities, and the sixth had cancer detected at screening mammography at another institution. Mean age at recurrence was 48 years. RESULTS: All eight cancers were visible on mammograms: four masses, two pleomorphic microcalcifications, and two masses with calcifications. Four of the eight were in the upper central portion of the breast. Before reconstruction, the original histologic diagnosis for all cases had been multifocal ductal carcinoma in situ. All recurrences were invasive cancer. Median time from the original diagnosis of breast cancer to diagnosis of recurrence was 42 months. Two of four patients who subsequently underwent axillary node dissection had metastatic disease in the lymph nodes. The single patient who underwent mammographic screening (elsewhere) had negative axillary lymph nodes. CONCLUSION: The mammographic appearance of recurrent carcinoma in TRAM flap reconstructions is similar to that of primary breast cancer.

Adult↗

PubMed1998

Mammographic screening in women more than 64 years old: a comparison of 1- and 2-year intervals.

OBJECTIVE: The purpose of our study was to determine if annual mammographic screening was superior to biennial screening in women more than 64 years old by examining differences in various prognostic indicators. MATERIALS AND METHODS: We reviewed the records of 119 consecutive women 65 years old and older with 120 cases of breast cancer who had a previous normal screening evaluation for breast cancer that included mammography and physical examination 8-30 months before diagnosis. A search of the computerized tumor registry, clinical records, and breast imaging records from November 1988 to April 1995 provided our cases. Screening intervals were defined as 6-18 months (annual) and 19-30 months (biennial). Mammographic, histologic, and clinical features were reviewed. Disease severity (DS) levels were assigned to each tumor as follows: DS-1 included minimal disease (ductal carcinoma in situ [TisNO], T1aN0, and T1bN0 tumors), DS-2 included all T1cN0 tumors, DS-3 included tumors larger than 2 cm in diameter with lymph nodes that were negative for cancer, and DS-4 included all metastatic disease. Statistically significant differences were calculated using the Wilcoxon rank sum test, Fisher's exact test, and the chi-square test. RESULTS: Ninety-three tumors were found in the group of patients who were annually screened, and 27 were found in the group of patients who were screened biennially. The women who underwent yearly screening mammography had significantly smaller invasive tumors (average, 10.7 mm; median, 9.5 mm versus 16.5 mm and 15.0 mm, respectively; p = .0086). The women who were screened annually also had significantly less advanced disease than women screened biennially (annually screened patients versus biennially screened patients: DS-1, 72% versus 44%; DS-2, 23% versus 37%; DS-3, 2% versus 11%; DS-4, 3% versus 7%; p = .0071). The group of patients screened annually had fewer cases of lymph node metastases (3% versus 8%; p = .12) and three times as many cases of ductal carcinoma in situ (22% versus 7%, p = .10). CONCLUSION: Annual screening mammography revealed significantly smaller tumors and less advanced cases of cancer than biennial screening, providing inferential support for annual mammographic screening of women more than 64 years old.

Age Factors↗

PubMed1997

Computerized classification of malignant and benign microcalcifications on mammograms: texture analysis using an artificial neural network.

We investigated the feasibility of using texture features extracted from mammograms to predict whether the presence of microcalcifications is associated with malignant or benign pathology. Eighty-six mammograms from 54 cases (26 benign and 28 malignant) were used as case samples. All lesions had been recommended for surgical biopsy by specialists in breast imaging. A region of interest (ROI) containing the microcalcifications was first corrected for the low-frequency background density variation. Spatial grey level dependence (SGLD) matrices at ten different pixel distances in both the axial and diagonal directions were constructed from the background-corrected ROI. Thirteen texture measures were extracted from each SGLD matrix. Using a stepwise feature selection technique, which maximized the separation of the two class distributions, subsets of texture features were selected from the multi-dimensional feature space. A backpropagation artificial neural network (ANN) classifier was trained and tested with a leave-one-case-out method to recognize the malignant or benign microcalcification clusters. The performance of the ANN was analysed with receiver operating characteristic (ROC) methodology. It was found that a subset of six texture features provided the highest classification accuracy among the feature sets studied. The ANN classifier achieved an area under the ROC curve of 0.88. By setting an appropriate decision threshold, 11 of the 28 benign cases were correctly identified (39% specificity) without missing any malignant cases (100% sensitivity) for patients who had undergone biopsy. This preliminary result indicates that computerized texture analysis can extract mammographic information that is not apparent by visual inspection. The computer-extracted texture information may be used to assist in mammographic interpretation, with the potential to reduce biopsies of benign cases and improve the positive predictive value of mammography.

Breast Diseases↗

PubMed1997

False-positive reduction technique for detection of masses on digital mammograms: global and local multiresolution texture analysis.

We investigated the application of multiresolution global and local texture features to reduce false-positive detection in a computerized mass detection program. One hundred and sixty-eight digitized mammograms were randomly and equally divided into training and test groups. From these mammograms, two datasets were formed. The first dataset (manual) contained four regions of interest (ROIs) selected manually from each of the mammograms. One of the four ROIs contained a biopsy-proven mass and the other three contained normal parenchyma, including dense, mixed dense/fatty, and fatty tissues. The second dataset (hybrid) contained the manually extracted mass ROIs, along with normal tissue ROIs extracted by an automated Density-Weighted Contrast Enhancement (DWCE) algorithm as false-positive detections. A wavelet transform was used to decompose an ROI into several scales. Global texture features were derived from the low-pass coefficients in the wavelet transformed images. Local texture features were calculated from the suspicious object and the peripheral subregions. Linear discriminant models using effective features selected from the global, local, or combined feature spaces were established to maximize the separation between masses and normal tissue. Receiver Operating Characteristic (ROC) analysis was conducted to evaluate the classifier performance. The classification accuracy using global features were comparable to that using local features. With both global and local features, the average area, Az, under the test ROC curve, reached 0.92 for the manual dataset and 0.96 for the hybrid dataset, demonstrating statistically significant improvement over those obtained with global or local features alone. The results indicated the effectiveness of the combined global and local features in the classification of masses and normal tissue for false-positive reduction.

Biophysical Phenomena↗

PubMed1997

Women with breast cancer: histologic findings in the contralateral breast.

PURPOSE: To investigate contralateral breast biopsy histologic findings in women with breast cancer. MATERIALS AND METHODS: Histologic findings in 237 patients with breast cancer who underwent contralateral breast biopsy for clinically or mammographically detected abnormalities were retrospectively reviewed. Malignant findings were categorized by histologic type. Benign findings were categorized by risk of breast cancer. Comparison was made with mammographically guided breast biopsy results in 1,294 patients without breast cancer. RESULTS: Of the 237 patients, 168 (70.9%) had either malignancy or high-risk histologic findings. One hundred thirty-nine patients (58.6%) had malignant findings; 98 (41.4%) had benign findings. Of the 98 with benign findings, 29 (30%) had high-risk histologic findings. Thirty (33%) of the 91 patients with invasive cancer had invasive lobular carcinoma. Forty-seven (45.6%) of the 103 patients with malignant lesions at mammographically guided biopsies had ductal carcinoma in situ alone. CONCLUSION: Compared with biopsy in women without breast cancer, contralateral biopsy in women with breast cancer was more likely to show malignancy, invasive lobular carcinoma, or ductal carcinoma in situ alone (P < .001) or to show high-risk histologic benign findings (P < .001). Mammographic and clinical findings in the contralateral breast should be regarded as more suspicious than those in patients without known breast cancer.

Adult↗

PubMed1997

Breast cancer in women 65-74 years old: earlier detection by mammographic screening.

OBJECTIVE: Our objective was to investigate the value of screening mammography in 65- to 74-year-old women by determining differences in various prognostic indicators in screened and nonscreened groups. MATERIALS AND METHODS: We reviewed 103 malignant breast tumors detected in 102 women 65-74 years old over a period of 73 consecutive months (February 1988-March 1994). A screening interval of less than 18 months was chosen to separate the screened from the nonscreened populations. Mammographic, histologic, and clinical features were reviewed. Statistically significant differences were calculated using Fisher's exact test and Wilcoxon's rank sum test. RESULTS: Thirty-two patients were in the screened population; 70 patients were in the nonscreened population. Ninety-nine percent (102/103) of the carcinomas were apparent mammographically. We found significant differences between the screened and the non-screened groups with respect to the size of lesions revealed by mammography (11 mm versus 21 mm; p = .0002) and the incidence of minimal tumors (20/32 (63%) versus 26/70 (37%), p = .0198). The incidence of lymph node metastases was 3/27 (11%) for the screened group versus 14/47 (30%) for the nonscreened group (p = .0875). The overall positive predictive value of mammography for the 65- to 75-year-old patients was higher than in our general population, 47% versus 28%. CONCLUSION: Screening mammography revealed significantly smaller and earlier stage tumors in 65- to 74-year-old women. This finding inferentially supports the efficacy of screening in this age population.

Aged↗

PubMed1997

Mammography of breast carcinoma in women who have mutations of the breast cancer gene BRCA1: initial experience.

OBJECTIVE: We describe for the first time (to our knowledge) the mammographic appearance of breast cancer and breast density in carriers of the breast cancer gene BRCA1. CONCLUSION: The mammographic appearance of breast cancer in BRCA1 carriers was similar to that in the general population. All mammographic densities were observed. Appropriate mammographic management of these extremely high-risk patients is yet to be determined.

Adult↗

PubMed1997

Metaplastic carcinoma of the breast: mammographic appearance with pathologic correlation.

OBJECTIVE: The objective of this study was to describe the mammographic appearance with pathologic correlation of metaplastic carcinoma of the breast. CONCLUSION: Metaplastic carcinomas of the breast are masses with mammographic characteristics of low suspicion because of their histologic appearance. Metaplastic carcinoma should be included in the differential assessment of predominately circumscribed, noncalcified masses revealed on mammography. One salient feature that may distinguish metaplastic carcinomas is the occurrence of a circumscribed portion with a spiculated portion, which is seen in carcinomas that have a significant mixture of metaplastic and invasive carcinoma growth patterns.

Adult↗

PubMed1996

Diagnosis of silicone gel breast implant rupture by ultrasonography.

To prospectively evaluate the efficacy of ultrasonography in the diagnosis of ruptured silicone gel breast implants, 98 patients (192 implants) underwent preoperative breast ultrasonography prior to silicone gel breast implant removal. The prevalence of implant rupture confirmed at surgery in this group of patients was 62 of the 192 implants (32 percent). Of the 60 implants diagnosed as ruptured by ultrasonography, 46 were confirmed as having visible defects at surgery (true positive) for a positive predictive value of 77 percent. Of the 132 implants diagnosed as intact by ultrasonography, 116 were confirmed as intact at surgery (true negative) for a negative predictive value of 88 percent. Overall, the sensitivity of ultrasonography for implant rupture was 74 percent, and the specificity was 89 percent. These findings demonstrate that ultrasonography is an effective imaging modality for the diagnosis of silicone gel breast implant rupture. Compared with mammography, ultrasonography appears to offer superior sensitivity and specificity without radiation exposure or discomfort. Although magnetic resonance imaging has shown considerable promise in the diagnosis of implant rupture, ultrasonography provides comparable sensitivity at a fraction of MRI's cost.

Breast↗

PubMed1996

Automated detection of breast masses on mammograms using adaptive contrast enhancement and texture classification.

This paper presents segmentation and classification results of an automated algorithm for the detection of breast masses on digitized mammograms. Potential mass regions were first identified using density-weighted contrast enhancement (DWCE) segmentation applied to single-view mammograms. Once the potential mass regions had been identified, multiresolution texture features extracted from wavelet coefficients were calculated, and linear discriminant analysis (LDA) was used to classify the regions as breast masses or normal tissue. In this article the overall detection results for two independent sets of 84 mammograms used alternately for training and test were evaluated by free-response receiver operating characteristics (FROC) analysis. The test results indicate that this new algorithm produced approximately 4.4 false positive per image at a true positive detection rate of 90% and 2.3 false positives per image at a true positive rate of 80%.

Automation↗

PubMed1996

Image feature selection by a genetic algorithm: application to classification of mass and normal breast tissue.

We investigated a new approach to feature selection, and demonstrated its application in the task of differentiating regions of interest (ROIs) on mammograms as either mass or normal tissue. The classifier included a genetic algorithm (GA) for image feature selection, and a linear discriminant classifier or a backpropagation neural network (BPN) for formulation of the classifier outputs. The GA-based feature selection was guided by higher probabilities of survival for fitter combinations of features, where the fitness measure was the area Az under the receiver operating characteristic (ROC) curve. We studied the effect of different GA parameters on classification accuracy, and compared the results to those obtained with stepwise feature selection. The data set used in this study consisted of 168 ROIs containing biopsy-proven masses and 504 ROIs containing normal tissue. From each ROI, a total of 587 features were extracted, of which 572 were texture features and 15 were morphological features. The GA was trained and tested with several different partitionings of the ROIs into training and testing sets. With the best combination of the GA parameters, the average test Az value using a linear discriminant classifier reached 0.90, as compared to 0.89 for stepwise feature selection. Test Az values with a BPN classifier and a more limited feature pool were 0.90 with GA-based feature selection, and 0.89 for stepwise feature selection. The use of a GA in tailoring classifiers with specific design characteristics was also discussed. This study indicates that a GA can provide versatility in the design of linear or nonlinear classifiers without a trade-off in the effectiveness of the selected features.

Algorithms↗

PubMed1996

Locally advanced breast carcinoma: accuracy of mammography versus clinical examination in the prediction of residual disease after chemotherapy.

PURPOSE: To determine the mammographic features of locally advanced breast carcinoma treated with neoadjuvant chemotherapy and to evaluate the accuracy of mammography in the prediction of residual carcinoma. MATERIALS AND METHODS: Of 90 women treated with hormonally synchronized cytotoxic therapy before mastectomy or lumpectomy for advanced breast carcinoma, 56 were selected because they had undergone mammography before and after neo-adjuvant therapy. Mammographic and clinical opinion on the presence of residual disease was compared with histologic results. RESULTS: Fifty-four (96%) of 56 women had a complete (n = 34 [61%]) or partial (n = 20 [36%]) clinical response. Thirteen (23%) of 56 women had no residual tumor. Sensitivity of mammography in the prediction of residual carcinoma was greater than that of clinical examination (79% vs 49%), but specificity was lower (77% vs 92%). In 24 women with inflammatory carcinoma, sensitivity of mammography was 78% while that of clinical examination was 39%; specificity was equal (83%). CONCLUSION: Mammography was more sensitive than clinical examination in the prediction of residual carcinoma; it was not accurate enough to obviate surgical biopsy.

Antineoplastic Agents↗

PubMed1996

Normal mammograms and the practice of obtaining previous mammograms: usefulness and costs.

PURPOSE: To determine the usefulness and cost of acquiring and comparing mammograms previously obtained at a different facility with normal mammograms. MATERIALS AND METHODS: Comparison mammographic reports obtained within 52 months in 1,297 consecutive women (aged 33-82 years; mean age, 53 years) were retrospectively reviewed. Mammograms in which a normal interpretation was altered after comparison were reviewed. The clinical importance and the cost of obtaining previous mammograms were determined. RESULTS: Initially, interpretation was normal in 756 (58%) comparison mammograms and abnormal in 541 (42%). Of the 756 normal mammograms, 197 (26%) were not compared with previous mammograms. Of the remaining 559, 551 (98%) had no change. In eight of the 559 (1%), the original interpretation was altered. Seven of these eight mammograms were available for review: In one, a developing density was detected; in three, differences were attributable to technique; and in three, radiologists had different interpretations. No malignancies were detected. The average labor and postage cost was $21.49. CONCLUSION: Considering the cost and low diagnostic yield, obtaining previous mammograms is of limited usefulness.

Adult↗

PubMed1996

Mammographic appearance of cancer in the opposite breast: comparison with the first cancer.

OBJECTIVE: Patients who have had cancer in one breast are at high risk for cancer in the contralateral breast. These bilateral cancers may be synchronous or metachronous. If the manifestations on mammography were similar in both breasts, an aggressive search for the mammographic findings of the first breast cancer might lead to early detection of the contralateral cancer. The purpose of this study was to evaluate mammograms for patients with bilateral cancers to determine whether the mammographic appearance of the contralateral cancer is likely to be the same as that of the first cancer. MATERIALS AND METHODS: We retrospectively reviewed the pathologic and mammographic records of 69 patients with surgically proven bilateral primary breast cancer. Thirty four of 69 (49%) had synchronous cancer, and 35 (51%) had metachronous cancer. Mammographic appearances were classified as microcalcifications, spiculated mass, nonspiculated mass (whether circumscribed or poorly defined), asymmetric or developing density, architectural distortion, and normal. Multiple findings were subclassified as major and minor findings. All findings were compared between both breast cancers, and statistical significance was determined by the two-sample Z test. RESULTS: Forty six (67%) of 69 patients had different major mammographic findings in the contralateral cancer. Of 30 patients whose first cancers had microcalcifications, 20 (67%) had microcalcifications in the contralateral cancer. Of 39 patients whose first cancers lacked microcalcifications, 17 (44%) had microcalcifications in the contralateral cancer. This difference was statistically significant (p = .02). Of 26 patients whose first cancers had spiculated masses, 9 (35%) had a contralateral spiculated mass. Of 43 patients whose first cancers lacked spiculated masses, 12 (28%) had a contralateral spiculated mass. This difference was not statistically significant (p = .22). CONCLUSION: Our results show that contralateral tumors usually have major mammographic findings different from those of the first cancer, and the mammographic signs of the first cancer do not indicate the most likely appearance of cancer in the contralateral breast. Evaluation of a contralateral mammogram should be performed without regard for the mammographic findings for the first cancer.

Adult↗