Measures of divergence of oriented patterns for the detection of architectural distortion in prior mammograms

Purpose We propose a method for the detection of architectural distortion in prior mammograms of interval-cancer cases based on the expected orientation of breast tissue patterns in mammograms. Methods The expected orientation of the breast tissue at each pixel was derived by using automatically detected landmarks including the breast boundary, the nipple, and the pectoral muscle (in mediolateral-oblique views). We hypothesize that the presence of architectural distortion changes the normal expected orientation of breast tissue patterns in a mammographic image. The angular deviation of the oriented structures in a given mammogram as compared to the expected orientation was analyzed to detect potential sites of architectural distortion using a measure of divergence of oriented patterns. Each potential site of architectural distortion was then characterized using measures of spicularity and angular dispersion specifically designed to represent spiculating patterns. The novel features for the characterization of spiculating patterns include an index of divergence of spicules computed from the intensity image and Gabor magnitude response using the Gabor angle response; radially weighted difference and angle-weighted difference (AWD) measures of the intensity, Gabor magnitude, and Gabor angle response; and AWD in the entropy of spicules computed from the intensity, Gabor magnitude, and Gabor angle response. Results Using the newly proposed features with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases, through feature selection and pattern classification with an artificial neural network, an area under the receiver operating characteristic curve of 0.75 was obtained. Free-response receiver operating characteristic analysis indicated a sensitivity of 0.80 at 5.3 false positives (FPs) per patient. Combining the features proposed in the present paper with others described in our previous works led to significant improvement with a sensitivity of 0.80 at 3.7 FPs per patient. Conclusion The proposed methods can detect architectural distortion in prior mammograms taken 15 months (on the average) before clinical diagnosis of breast cancer, but the FP rate needs to be reduced.     

Detection of architectural distortion in prior screening mammograms using Gabor filters, phase portraits, fractal dimension, and texture analysis

Objective Mammography is a widely used screening tool for the early detection of breast cancer. One of the commonly missed signs of breast cancer is architectural distortion. The purpose of this study is to explore the application of fractal analysis and texture measures for the detection of architectural distortion in screening mammograms taken prior to the detection of breast cancer. Materials and methods A method based on Gabor filters and phase portrait analysis was used to detect initial candidates for sites of architectural distortion. A total of 386 regions of interest (ROIs) were automatically obtained from 14 “prior mammograms”, including 21 ROIs related to architectural distortion. From the corresponding set of 14 “detection mammograms”, 398 ROIs were obtained, including 18 related to breast cancer. For each ROI, the fractal dimension and Haralick’s texture features were computed. The fractal dimension of the ROIs was calculated using the circular average power spectrum technique. Results The average fractal dimension of the normal (false-positive) ROIs was significantly higher than that of the ROIs with architectural distortion (p = 0.006). For the “prior mammograms”, the best receiver operating characteristics (ROC) performance achieved, in terms of the area under the ROC curve, was 0.80 with a Bayesian classifier using four features including fractal dimension, entropy, sum entropy, and inverse difference moment. Analysis of the performance of the methods with free-response receiver operating characteristics indicated a sensitivity of 0.79 at 8.4 false positives per image in the detection of sites of architectural distortion in the “prior mammograms”. Conclusion Fractal dimension offers a promising way to detect the presence of architectural distortion in prior mammograms.     

Simulation of mammographic breast compression in 3D MR images using ICP-based B-spline deformation for multimodality breast cancer diagnosis

Purpose

   Multimodality mammography using conventional 2D mammography and dynamic contrast-enhanced 3D magnetic resonance imaging (DCE-MRI) is frequently performed for breast cancer detection and diagnosis. Combination of both imaging modalities requires superimposition of corresponding structures in mammograms and MR images. This task is challenging due to large differences in (1) dimensionality and spatial resolution, (2) variations in tissue contrast, as well as (3) differences in breast orientation and deformation during the image acquisition. A new method for multimodality breast image registration was developed and tested.

Methods

   Combined diagnosis of mammograms and MRI datasets was achieved by simulation of mammographic breast compression to overcome large differences in breast deformation. Surface information was extracted from the 3D MR image, and back-projection of the 2D breast contour in the mammogram was done. B-spline-based 3D/3D surface-based registration was then used to approximate mammographic breast compression. This breast deformation simulation was performed on 14 MRI datasets with 19 corresponding mammograms. The results were evaluated by comparison with distances between corresponding structures identified by an expert observer.

Results

   The evaluation revealed an average distance of 6.46 mm between corresponding structures, when an optimized initial alignment between both image datasets is performed. Without the optimization, the accuracy is 9.12 mm.

Conclusion

   A new surface-based method that approximates the mammographic deformation due to breast compression without using a specific complex model needed for finite-element-based methods was developed and tested with favorable results. The simulated compression can serve as foundation for a point-to-line correspondence between 2D mammograms and 3D MR image data.     

Computer-aided-detection marker value and breast density in the detection of invasive lobular carcinoma

Purpose

Invasive Lobular Carcinoma (ILC) is frequently a mammographic and diagnostic dilemma; thus any additional information that CAD (Computer-Aided Detection) systems can give radiologists may be helpful. Our study was to evaluate the role of CAD numeric values as indicators of malignancy and the effect of breast density in the diagnosis of ILC.

Materials and methods

Eighty consecutive biopsy-proven ILC cases with CAD (ImageChecker^®, Hologic | R2, Santa Clara, CA, versions 2.3, 3.1, 3.2, 5.0, 5.2) diagnosed between June 2002 and December 2004 were retrospectively reviewed. Data included: BIRADS^® breast density, whether CAD marked the cancer at diagnosis year or years prior, and lesion type. Study mammograms underwent additional CAD scans (Image Checker^® V5.3, V8.0, V8.1) to obtain a numeric value associated with each marker, low values represent increasingly suspicious features.

Results

CAD correctly marked 65% (52/80) of ILC cases, detection was found to decrease with increased breast density. Numeric values of CAD marks at sites of carcinoma showed median score of 171 (range 0 – 1121).

Conclusion

The CAD marker may potentially be used as an additional indicator of suspicious lesion features in all breast densities and higher likelihood that an area on the mammogram requires further investigation.     

Reduction of false positives in the detection of architectural distortion in mammograms by using a geometrically constrained phase portrait model

Objective One of the commonly missed signs of breast cancer is architectural distortion. We have developed techniques for the detection of architectural distortion in mammograms, based on the analysis of oriented texture through the application of Gabor filters and a linear phase portrait model. In this paper, we propose constraining the shape of the general phase portrait model as a means to reduce the false-positive rate in the detection of architectural distortion. Material and methods The methods were tested with one set of 19 cases of architectural distortion and 41 normal mammograms, and with another set of 37 cases of architectural distortion. Results Sensitivity rates of 84% with 4.5 false positives per image and 81% with 10 false positives per image were obtained for the two sets of images. Conclusion The adoption of a constrained phase portrait model with a symmetric matrix and the incorporation of its condition number in the analysis resulted in a reduction in the false-positive rate in the detection of architectural distortion. The proposed techniques, dedicated for the detection and localization of architectural distortion, should lead to efficient detection of early signs of breast cancer.     

Reducing the semantic gap in content-based image retrieval in mammography with relevance feedback and inclusion of expert knowledge

Object

We investigate the use of relevance feedback (RFb) and the inclusion of expert knowledge to reduce the semantic gap in content-based image retrieval (CBIR) of mammograms.

Materials and methods

Tests were conducted with radiologists, in which their judgment of the relevance of the retrieved images was used with techniques of query-point movement to incorporate RFb. The measures of similarity of images used for CBIR were based upon textural characteristics and the distribution of density of fibroglandular tissue in the breast. The features used include statistics of the gray-level histogram, texture features based upon the gray-level co-occurrence matrix, moment-based features, measures computed in the Radon domain, and granulometric measures. Queries for CBIR with RFb were executed by three radiologists. The performance of CBIR was measured in terms of precision of retrieval and a measure of relevance-weighted precision (RWP) of retrieval.

Results

The results indicate improvement due to RFb of up to 62% in precision and 39% in RWP.

Conclusion

The gain in performance of CBIR with RFb depended upon the BI-RADS breast density index of the query mammographic image, with greater improvement in cases of mammograms with higher density.     

Identification of distinct subgroups of breast cancer patients based on self-reported changes in sleep disturbance

Purpose

The purposes of this study were to identify distinct subgroups of patients based on self-reported sleep disturbance prior to through 6 months after breast cancer surgery and evaluate for differences in demographic, clinical, and symptom characteristics among these latent classes.

Methods

Women (n?=?398) who underwent unilateral breast cancer surgery were enrolled prior to surgery. Patients completed measures of functional status, sleep disturbance (i.e., General Sleep Disturbance Scale (GSDS); higher scores indicate higher levels of sleep disturbance), fatigue, attentional fatigue, depressive symptoms, and anxiety prior to surgery and monthly for 6 months.

Results

Three distinct classes of sleep disturbance trajectories were identified using growth mixture modeling. The high sustained class (55.0%) had high and the low sustained class (39.7%) had low GSDS scores prior to surgery that persisted for 6 months. The decreasing class (5.3%) had high GSDS score prior to surgery that decreased over time. Women in the high sustained class were significantly younger, had more comorbidity and poorer function, and were more likely to report hot flashes compared to the low sustained class. More women who underwent mastectomy or breast reconstruction were in the decreasing class. Decreasing and high sustained classes reported higher levels of physical fatigue, attentional fatigue, depressive symptoms, and anxiety compared to the low sustained class.

Conclusions

A high percentage of women has significant sleep disturbance prior to surgery that persists during subsequent treatments (i.e., radiation therapy and chemotherapy). Clinicians need to perform routine assessments and initiate appropriate interventions to improve sleep prior to and following surgery.     

Awareness,concern, and communication between physicians and patients on bone health in cancer

Purpose

This study aims to explore physician–patient communications about bone metastases and cancer treatment-induced bone loss (CTIBL).

Methods

The study utilizes online survey of patients with breast cancer, prostate cancer, and multiple myeloma, and the physicians who treat them.

Results

Even though 69 and 48 % of patients with nonmetastatic breast and prostate cancer aware of treatment-induced bone loss, only 39 and 23 %, respectively, were concerned about bone loss. Yet, 62 and 71 % of oncologists treating breast and prostate cancer felt that their patients were concerned. Among patients with metastatic breast and prostate cancer, two thirds had not discussed treatment for bone metastases with their doctor; when discussed, 88 and 91 % of discussions were initiated by the doctor, usually prior to initiating treatment. Most myeloma patients (77 %) had discussed treatment options with their physicians; 99 % of hematologists reported discussing treatment of bone disease with patients.

Conclusions

Physicians are primary sources of information to patients regarding bone health. There is a gap between what physicians assume their patients know about bone health and the patients’ perceptions, presenting a need for systematic awareness and education.     

Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model

Purpose

Improving radiologists’ performance in classification between malignant and benign breast lesions is important to increase cancer detection sensitivity and reduce false-positive recalls. For this purpose, developing computer-aided diagnosis schemes has been attracting research interest in recent years. In this study, we investigated a new feature selection method for the task of breast mass classification.

Methods

We initially computed 181 image features based on mass shape, spiculation, contrast, presence of fat or calcifications, texture, isodensity, and other morphological features. From this large image feature pool, we used a sequential forward floating selection (SFFS)-based feature selection method to select relevant features and analyzed their performance using a support vector machine (SVM) model trained for the classification task. On a database of 600 benign and 600 malignant mass regions of interest, we performed the study using a tenfold cross-validation method. Feature selection and optimization of the SVM parameters were conducted on the training subsets only.

Results

The area under the receiver operating characteristic curve \((\hbox {AUC}) = 0.805\pm 0.012\) was obtained for the classification task. The results also showed that the most frequently selected features by the SFFS-based algorithm in tenfold iterations were those related to mass shape, isodensity, and presence of fat, which are consistent with the image features frequently used by radiologists in the clinical environment for mass classification. The study also indicated that accurately computing mass spiculation features from the projection mammograms was difficult, and failed to perform well for the mass classification task due to tissue overlap within the benign mass regions.

Conclusion

In conclusion, this comprehensive feature analysis study provided new and valuable information for optimizing computerized mass classification schemes that may have potential to be useful as a “second reader” in future clinical practice.     

Validation and feasibility of a caloric expenditure measuring device in women with early-stage breast cancer

Purpose

The purpose of this study is to validate the Bodybugg (BB), a caloric expenditure measuring device, in breast cancer patients undergoing adjuvant and neoadjuvant chemotherapy for early-stage breast cancer.

Methods

Twenty-five women with stages I–III breast cancer who were to receive adjuvant dose-dense doxorubicin/cyclophosphamide were recruited. Participants were asked to wear the BB and record activity logs for seven pretreatment days (prior to commencing chemotherapy) and seven posttreatment days (upon completing cycle 4 of chemotherapy). The BB’s caloric expenditure measurements were used to calculate metabolic equivalent (MET) values of patients’ recorded activities. BB-calculated METs were compared with matching METs from the 2011 Compendium of Physical Activities Tracking Guide to assess accuracy of the device.

Results

The overall patient sample wore the device for an average of 5.32 (SD 1.75) pre- and 4.88 (SD 2.01) posttreatment days. The mean pairwise difference between BB and Compendium METs was 0.043 (SD 0.77) for 308 pretreatment activities recorded by 12 patients and 0.065 (SD 0.61) for 108 posttreatment activities recorded by 6 patients, indicating close to zero bias between the BB’s and Compendium’s measurements. Hierarchical linear modeling showed that Compendium METs strongly predict for BB METs (P?<?0.00001).

Conclusions

The BB is feasible to use in study designs involving defined time periods of measurement and provides accurate and objective measurements of caloric expenditure in breast cancer patients.     

Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction

Purpose

How to optimally detect bilateral mammographic asymmetry and improve risk prediction accuracy remains a difficult and unsolved issue. Our aim was to find an effective mammographic density segmentation method to improve accuracy of breast cancer risk prediction.

Methods

A dataset including 168 negative mammography screening cases was used. We applied a mutual threshold to bilateral mammograms of left and right breasts to segment the dense breast regions. The mutual threshold was determined by the median grayscale value of all pixels in both left and right breast regions. For each case, we then computed three types of image features representing asymmetry, mean and the maximum of the image features, respectively. A two-stage classification scheme was developed to fuse the three types of features. The risk prediction performance was tested using a leave-one-case-out cross-validation method.

Results

By using the new density segmentation method, the computed area under the receiver operating characteristic curve was 0.830 ± 0.033 and overall prediction accuracy was 81.0%, significantly higher than those of 0.633 ± 0.043 and 57.1% achieved by using the previous density segmentation method (\(p<0.01\), t-test).

Conclusions

A new mammographic density segmentation method based on a bilateral mutual threshold can be used to more effectively detect bilateral mammographic density asymmetry and help significantly improve accuracy of near-term breast cancer risk prediction.

     

Gustatory and olfactory function in breast cancer patients

Purpose

Loss of appetite is a common complaint in cancer patients. There is still no overall conclusion whether this symptom might be caused by distorted taste/smell function or by tumor byproducts. This knowledge would be important for adequate patient counseling as well as symptom relief. Several studies investigated taste function, but to our knowledge, only one studied olfactory function in cancer patients.

Materials and methods

Sixty-nine breast cancer patients were investigated by a validated taste (taste strips) and smell test (Sniffin' Sticks) prior to chemotherapy.

Results

Compared to normative data, breast cancer patients showed no significant difference in odor threshold, but better scores for odor identification and odor discrimination. For taste, breast cancer patients showed a significantly lower value for the quality sour compared to healthy controls only on left side of the tongue; there was no difference in the qualities sweet, salty, and bitter. An increase in tumor size was associated with a significant decrease in olfactory function, but not in gustatory function. Different histology or graduation of breast cancer, resection status, or metastasis to the lung and liver had no influence on taste and smell. There was no correlation between taste and smell to estrogen or progesterone receptor status. There was no correlation between smell and human epidermal growth factor receptor 2 (Her2 status), but there was a significant correlation between bitter taste and Her2 status.

Conclusion

Taste/smell did not seem substantially altered in breast cancer patients compared to normative data. Nevertheless, increasing tumor burden resulted in decreased olfactory function, but not in taste changes.     

Investigating physical symptom burden and personal goal interference in early-stage breast cancer patients

Purpose

Physical symptoms associated with breast cancer and its treatment can substantially interfere with functional outcomes and quality of life. The present study seeks to delineate the relationship between physical symptom burden and cancer-related goal interference in early-stage breast cancer patients.

Methods

Self-report questionnaires were administered to 43 eligible female patients at four time-points in the 6 months following surgery for early-stage breast cancer. Physical symptoms, cancer-related goal interference, and psychological distress were assessed at each time-point. K-means cluster analysis and independent sample t tests evaluated the relationships of interest.

Results

Women with a higher physical symptom burden experienced significantly higher goal interference and psychological distress than those with a lower burden at multiple time-points following surgery.

Conclusions

This study provides preliminary evidence that physical symptom burden can interfere with important goal pursuit in early-stage breast cancer patients. Breast cancer survivors with ongoing challenging symptoms may require targeted psychosocial support to cope with possible goal interference and associated distress.     

Deep-Tissue Reporter-Gene Imaging with Fluorescence and Optoacoustic Tomography: A Performance Overview

Purpose

A primary enabling feature of near-infrared fluorescent proteins (FPs) and fluorescent probes is the ability to visualize deeper in tissues than in the visible. The purpose of this work is to find which is the optimal visualization method that can exploit the advantages of this novel class of FPs in full-scale pre-clinical molecular imaging studies.

Procedures

Nude mice were stereotactically implanted with near-infrared FP expressing glioma cells to from brain tumors. The feasibility and performance metrics of FPs were compared between planar epi-illumination and trans-illumination fluorescence imaging, as well as to hybrid Fluorescence Molecular Tomography (FMT) system combined with X-ray CT and Multispectral Optoacoustic (or Photoacoustic) Tomography (MSOT).

Results

It is shown that deep-seated glioma brain tumors are possible to visualize both with fluorescence and optoacoustic imaging. Fluorescence imaging is straightforward and has good sensitivity; however, it lacks resolution. FMT-XCT can provide an improved rough resolution of ～1 mm in deep tissue, while MSOT achieves 0.1 mm resolution in deep tissue and has comparable sensitivity.

Conclusions

We show imaging capacity that can shift the visualization paradigm in biological discovery. The results are relevant not only to reporter gene imaging, but stand as cross-platform comparison for all methods imaging near infrared fluorescent contrast agents.     

A Novel Fluorescent Imaging Agent for Diffuse Optical Tomography of the Breast: First Clinical Experience in Patients

Purpose

This is the first clinical evaluation of a novel fluorescent imaging agent (Omocianine) for breast cancer detection with diffuse optical tomography (DOT).

Procedures

Eleven women suspected of breast cancer were imaged with DOT at multiple time points (up to 24 h) after receiving an intravenous injection of Omocianine (doses 0.01 to 0.1 mg/kg bodyweight). Breast MRI was obtained for comparison.

Results

Histopathology showed invasive cancer in ten patients and fibroadenoma in one patient. With the lowest dose of Omocianine, two of three lesions were detected; with the second dose, three of three lesions were detected; with the two highest doses, none of five lesions were detected. Lesion location on DOT showed excellent agreement with MRI. Optimal lesion-to-background signals were obtained after 8 h. No adverse events occurred.

Conclusions

Lowest doses of Omocianine performed best in lesion detection; DOT using a low-dose fluorescent agent is feasible and safe for breast cancer visualization in patients.     

Pilot randomised controlled trial of a radiation therapist-led educational intervention for breast cancer patients prior to commencing radiotherapy

Purpose

Although patients receive information prior to commencing radiotherapy, they often experience anxiety and distress. We conducted a pilot randomised controlled trial to determine whether a radiation therapist led psycho-educational intervention for breast cancer patients prior to radiotherapy is likely to be effective in reducing radiotherapy-related concerns, patient anxiety and depression.

Methods

The intervention comprised two face-to-face consultations with a radiation therapist (one prior to radiation planning and the other prior to treatment). Patients completed surveys at baseline, prior to treatment planning and on the first day of treatment. Outcome measures included the Hospital Anxiety and Depression Scale, Radiation Therapy Related Patient Concerns and Radiation Therapy Knowledge Scales.

Results

One hundred and twenty two patients completed baseline measures. Fifty-eight patients received usual care, and 64 received the intervention. After the first consultation, patient anxiety was significantly lower in the intervention group (p?=?0.048), as were concerns about radiotherapy (p?=?0.001). There were no differences between groups for depression. Patient knowledge for the intervention group was higher after the first consultation (p?<?0.001).

Conclusion

This intervention is likely to be effective in reducing patient anxiety and concerns and increasing knowledge. Future research is required to test this intervention with a larger population.