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Study to Evaluate the Role of Computer aided Detection Using Full Field Digital Mammography in Breast Cancer Imaging

Background: Mammography is acknowledged as the single most effective method of screening for breast cancer and is credited with helping to reduce breast cancer mortality by approximately 30%. CAD systems are a new tool in detecting breast cancers on screening mammograms and in detecting potentially suspicious abnormalities on a mammogram. The aim & objective is to main aim of the present study to evaluate the performance of Computer Aided Detection using Full Field Digital Mammography in Breast Cancer imaging. Subjects and Methods: In the present study, Cases with lump breast with clinical suspicion of breast cancer and post op recurrence of breast cancer were imaged with FFDM and images were read on the viewing monitor without and with the aid of CAD software. The present study confirms that the diagnosis of breast cancer is made only following histopathology of respected specimen. Results: The maximum incidence was in 41-50 years and 51-60 years which was 13 cases in each group (30 %). There were 25 cases out of 40 (62.5%) in which the lesion was marked by CAD. Out of which in 20 cases (50%) only one lesion was marked by CAD and in 4 cases (10%) two lesions were marked by CAD. The total number of lesions marked by CAD was 25 (62.5%). Majority of patients had scattered fibro glandular density of breast. This was present in 19 patients (47.5%). 10 patients (20%) had heterogeneously dense breast, 07 patients (17.5%) had fatty breast and 04 patients (10%) had extremely dense breast. In majority of cases the lesion type was mass alone which was present in 26 cases (60%). While 10 cases (25%) presented as mass with microcalcifications and 4 cases (10%) presented with microcalcifications alone. In 24 cases there was no spread of cluster of micro calcification (60%). In 7 cases (17.5%) the spread of cluster of micro calcification was <10mm, in 4 cases (10%) the spread of cluster of micro calcification was 21-30 mm and in 5 cases ( 12.5%) the spread of cluster of micro calcification was > 40mm. In majority of cases the HPE revealed DCIS which was seen in 22 cases (55%), 08 cases (20%) were invasive ductal carcinoma and 02 cases was invasive lobular carcinoma. In 22 cases (55%) the BIRADS for the breast affected with cancer was BIRADS-V. While in 14 cases (35%) the score was BIRADS-IV, 04 cases (10%) the score was BIRADS-VI and in 02 case (5%) the score was BIRADS-III. The sensitivity, specificity and accuracy of CAD for detection of mass were 70%, 100% and 85% respectively and for detection of cluster of microcalcification were 100% respectively. Conclusion: CAD with FFDM is good at detection of Microcalcifications. Detection of masses is better without the aid of CAD as compared to CAD. However detection of lesion improves if reading of mammogram is done both with and without CAD. This study was done to evaluate the performance of CAD in FFDM in detecting mass and micro calcifications in cases of breast cancer. The final diagnosis was based on histopathological (FNAC The


Introduction
Mammography is presently the best existing tool for detecting symptoms of breast cancer early on. It is alsocapable of revealing obvious distinctive physical aberrations, such as masses and calcifications, as well as subtle signs such as bilateral asymmetry and architectural distortion (Rangayyan et al., 2007). [1] The prompt detection of breast cancer is of paramount significance since early detection of benign cancer leads to a 5 years survival rate of 97.5%, whereas malignant cancer has a 5 years survival rate of only 20.4% (Jemal et al., 2004). [2] Mammography is an exceptional type of X-ray imaging that provides detailed visual images of the breast using intrinsic advanced features such as low dose X-ray, high contrast, high-resolution film and an X-ray system designed purposely for imaging the breasts (Helms et al., 2008). [3] Computer-Aided Detection (CAD) is a technique that combines diagnostic imaging with computer science, image processing, pattern recognition and artificial intelligence tech-nologies (Rangayyan et al., 2007). [1] It is a diagnostic tool (Giger, 2000), [4] developed in radiology to utilize the output of computerized analysis of medical images as a secondary opinion in the detection of lesions and making diagnostic assessments. In recent times, CAD systems have garnered several interests from both research scientists and radiologists because of the related complex research subjects and prospective clinical applications. The incorporation of computer processing in biomedical image analyses provides a more precise diagnosis since humans are prone to making errors and their analysis is generally biased and qualitative rather than quantitative. Improved biomedical image analysis using CAD leads to a more accurate diagnostic decision by the physician (Rangayyan and Ferrari, 2004). [5] Thus this study was undertaken to evaluate the accuracy of CAD in detecting the breast cancers based on lesion type, lesion size, breast density, microcalcifications, BIRADS classification, histopathology and stage of cancer in Full Field Digital Mammography.  2) was also used to detect mass and microcalcifications in these cases. CAD sensitivity was assessed in relation to breast density, mammographic presentation, histopathology results, and lesion size.

Data Collection
a. As per proforma b. MS database.

Statistical Analysis
1. Comparison was done in all the cases of masses and microcalcifications without the aid of CAD and with the aid of CAD. 2. Sensitivity, specificity and accuracy of CAD in detecting breast cancers using full field digital mammography as an imaging modality were calculated with histopatholgical examination as the gold standard. 3. In this study sensitivity, specificity and accuracy were calculated with presumption that if a mass / microcalcification is not detected on FFDM with / without use of CAD, then there is no breast cancer. 4. Also if a mass / microcalcification is detected with / without CAD on FFDM, then the mass / micro calcification is present and the diagnosis of breast cancer is made only following histopathology of resected specimen.

Age Distribution of Study Population
In present study, the age range was 38-80 years. The maximum incidence was in 41-50 years and 51-60 years which was 13

Clinical Background of Patients
The most common symptom was lump alone which was present in 35 patients (87.5%). 03 patient (7.5%) presented with nipple retraction, 01 patient (2.5%) presented with pus and blood stained nipple discharge and 01 patient (2.5%) had lump in breast with Ca cervix.

Lesion Detected Without the Aid of CAD
The number of cases in which lesions were detected without the aid of CAD was 38 (95%), out of which 32 (75%) cases had only single lesion and 04 (15%) cases had two lesions. The total number of lesions detected without the aid of CAD was 38 (95%).

Lesions marked by CAD
There were 25 cases out of 40 (62.5%) in which the lesion was marked by CAD. Out of which in 20 cases (50%) only one lesion was marked by CAD and in 4 cases (10%) two lesions were marked by CAD. The total number of lesions marked by CAD was 25 (62.5%)

Lesion Distribution in Quadrants of Breast
In majority of cases the distribution of lesion was in the upper outer quadrant of breast, which was seen in 18 cases (45%). In 14 cases (35%) the lesion was in lower inner, 04 cases (10%)  the lesion was retroareolar, 02 case (5%) the lesion was lower outer and 01 case (5%) the lesion was in upper inner quadrant of breast.

Lesion Type
In majority of cases the lesion type was mass alone which was present in 26 cases (60%). While 10 cases (25%) presented as mass with microcalcifications and 4 cases (10%) presented with microcalcifications alone.

Size of Mass
In majority of cases the size of lesion was more than 20mm, the number of cases which presented with lesion size more than 20mm were 28 (70%). The number of cases which presented with lesion size of 10-20 mm was 7 (17.5%). The number of cases which presented with microcalcifications alone and no mass were 5 (12.5%). While no case presented with a lesion size of 21-30 mm.

Spread of Cluster of Microcalcifications
In 24 cases there was no spread of cluster of microcalcification (60%). In 7 cases (17.5%) the spread of cluster of micro calcification was <10mm, in 4 cases (10%) the spread of cluster of micro calcification was 21-30 mm and in 5 cases ( 12.5%) the spread of cluster of micro calcification was > 40mm.

Architectural Distortion
In 18 cases there was no architectural distortion (60%). While in 12 cases (40%) there was architectural distortion.

Histopathological Examination
Both FNAC and excision biopsy were performed in all the cases. On FNAC, in 06 cases reported as ductal hyperplasia with atypia and 02 case reported as fibromyxoid stroma with no epithelial cells the biopsy report confirmed a carcinoma. In majority of cases the HPE revealed DCIS which was seen in 22 cases (55%), 08 cases (20%) were invasive ductal carcinoma and 02 case was invasive lobular carcinoma.

Stage of Breast Cancer
Both TNM and pathological stage of cancer was determined in all 30 cases.

Comparison of detecting breast cancer with CAD and without the aid of CAD and correlation with lesion type
In the lesion type mass alone there were 18 cases and 22 lesions. In 16 cases there was solitary mass and in 04 cases there were two masses. All these 22 lesions (100%) were detected without the aid of CAD. There were 12 lesions (54.5%) marked by CAD while 10 lesions were not marked by CAD.

Discussion
Breast cancer begins in breast tissue, which is made up of glands for milk production, called lobules, and the ducts that connect the lobules to the nipple. The remainder of the breast is made up of fatty, connective, and lymphatic tissue. Most masses are benign; that is, they are not cancerous and are not life-threatening.
Breast cancer is the most common female malignancy and the second leading cause of cancer deaths. The incidence of breast cancer is rising in most countries of the world. India is a low resource country, where the healthcare workforce and infrastructure available for cancer care is limited or nonexistent. In the past decade there has been a dramatic increase in the incidence of breast cancer in India like the rest of the world.
The radiological examination of breast is an integral part of modern multidisciplinary approach for effective management of breast disease. The aim of breast imaging is to assess the probability of a lesion being benign or malignant. While multiple screening trials have shown the benefits of screening mammography, there are limitations to X-ray mammography.
The overall sensitivity of X-ray mammography is only 85%. The sensitivity of the mammography varies with the breast density. In the fatty breast the sensitivity has been reported in the high nineties. In the dense breast however, the sensitivity has been reported to be much less, closer to 50%.
Detecting cancers using mammography when they are at a smaller size and earlier stage has been shown to reduce or delay mortality from breast cancer.
In the past two decades, mammography has become the most sensitive technique for detecting non-palpable lesions and characterizing palpable masses. It is a technique that utilizes low x-rays for examination of the breast tissues.
Mammography is acknowledged as the single most effective method of screening for breast cancer and is credited with helping to reduce breast cancer mortality by approximately 30%.
Methods suggested to decrease the number of missed cancers include training, experience, continuing education, prospective double reading, retrospective evaluation of missed cases, and computer-aided detection (CAD). CAD systems have proven to be quite sensitive in detecting breast cancers on screening mammograms. CAD programs are commercially available systems that use computer software to assist the mammographer in detecting or identifying potentially suspicious abnormalities on a mammogram. The CAD program identifies potential abnormalities on the images and marks areas on the study that the computer considers to be suspicious.
In the present study, 40 cases who presented with clinical features related to breast cancer were evaluated by Full Field Digital Mammography. Screening and diagnostic mammograms were performed with four standard views per case using Full Field Digital Mammography (Siemens Mammomat DS). Each case included a craniocaudal (CC) and mediolateral oblique (MLO) view of the breasts.

Symptoms of Patients
We observed the most common symptom was lump alone which was present in 35 patients (87.5%). 03 patients (7.5%) presented with nipple retraction, 01 patients (2.5%) presented with pus and blood stained nipple discharge and 01 patients (2.5%) had lump in breast with Ca cervix.

Age Distribution In Patients
In present study, the age range was 38-80 years. The maximum incidence was in 41-50 years and 51-60 years which was 13 cases in each group (30 %). The incidence was minimum in < 40years.

Breast Density
In this study, Majority of patients had scattered fibro glandular density of breast. This was present in 19 patients (47.5%). 10 patients (20%) had heterogeneously dense breast, 07 patients (17.5%) had fatty breast and 04 patients (10%) had extremely dense breast.
In the category of extremely dense breast there were 02 cases and 03 lesions. One case had solitary lesion while another breast had two lesions. 02 lesions (66.7%) were detected without the aid of CAD and 01 lesion was not detected without the aid CAD. In this category, CAD marked 01 lesion (33.3%) while 02 lesions were not marked.
In a study conducted by Bern, the CAD sensitivity with FFDM was six of six (100%) fatty breasts, in 63 of 66 (95%) breasts containing scattered fibroglandular densities, and in 43 of 46 (93%) heterogeneously dense breasts. Sensitivity in extremely dense breasts was only 60% (3/5). [6,7] Lesion Size In majority of cases the lesion type was mass alone which was present in 26 cases (60%). While 10 cases (25%) presented The number of cases in which lesions were detected without the aid of CAD was 38 (95%), out of which 32 (75%) cases had only single lesion and 04 (15%) cases had two lesions. The total number of lesions detected without the aid of CAD was 38 (95%).
There were 25 cases out of 40 (62.5%) in which the lesion was marked by CAD. Out of which in 20 cases (50%) only one lesion was marked by CAD and in 4 cases (10%) two lesions were marked by CAD. The total number of lesions marked by CAD was 25 (62.5%) In majority of cases the size of lesion was more than 20mm, the number of cases which presented with lesion size more than 20mm were 28 (70%). The number of cases which presented with lesion size of 10-20 mm was 7 (17.5%). The number of cases which presented with microcalcifications alone and no mass were 5 (12.5%). While no case presented with a lesion size of 21-30 mm.
In a study by Giger, [4] CAD with FFDM enhanced earlier detection by showing 89% of tumors that were 1-10 mm. Moreover, detection was fairly consistent among moderate to large tumors despite the fact that CAD systems are generally not designed to identify them, because large tumors are more readily identifiable by the radiologist without CAD. In this study, 93% (14/15) of tumors > 30 mm were detected by CAD. [6] Lesion Type In majority of cases the lesion type was mass alone which was present in 26 cases (60%). While 10 cases (25%) presented as mass with micro calcifications and 4 cases (10%) presented with microcalcifications alone.

Architectural Distortion
In the present study, in 18 cases there was no architectural distortion (60%). While in 12 cases (40%) there was architectural distortion.

Histopathological Examination
In the present study, both FNAC and excision biopsy were performed in all the cases. On FNAC, in 06 cases reported as ductal hyperplasia with atypia and 02 case reported as fibromyxoid stroma with no epithelial cells the biopsy report confirmed a carcinoma. In majority of cases the HPE revealed DCIS which was seen in 22 cases (55%), 08 cases (20%) were invasive ductal carcinoma and 02 case was invasive lobular carcinoma.
Brem and colleagues found that CAD sensitivity for invasive ductal carcinoma, invasive lobular carcinoma, and mixed and various invasive carcinomas and DCIS varied from 85% to 95%. [7] Malich et al, [8] reported a sensitivity range of 90-97% for invasive ductal carcinoma, invasive lobular carcinoma, invasive tubular carcinoma and DCIS, whereas less common histopathologies with five or fewer cases in that study such as mucinoid and other invasive cancers showed CAD sensitivities of 75% and 80%,respectively.

Birads Score of the Breast
In 22 cases (55%) the BIRADS for the breast affected with cancer was BIRADS-V. While in 14 cases (35%) the score was BIRADS-IV, 04 cases (10%) the score was BIRADS-VI and in 02 case (5%) the score was BIRADS-III.

Pahological Stage of Breast Cancer
In this study, there were 12 cases of stage IIA, 08 cases of stage IIB, 10 cases of stage IIIA, 06 cases of stage IIIC and 04 cases of stage IV.
In the category of Stage IIA, there were 12 cases and 10 lesions. 07 cases had solitary lesion while one case had two lesions. There were 08 lesions (88.9%) detected without the aid of CAD and one lesion was not detected. CAD marked 04 lesions (44.4%) and 05 lesions were not marked by CAD.

Conclusion
This study was done to evaluate the performance of CAD in FFDM in detecting mass and micro calcifications in cases of breast cancer. The final diagnosis was based on histopathological examination (FNAC and Biopsy). The sensitivity, specificity and accuracy of FFDM without the aid of CAD for detection of mass were 100% respectively. Detection of lesion on FFDM was better without the aid of CAD as compared to detection of lesion with CAD alone. However detection of lesion improves if reading of mammogram is done both with and without CAD. Detection of masses on FFDM is better on FFDM without CAD than with CAD. Detection of microcalcification in FFDM is better with CAD than without CAD. Detection of lesion on FFDM is better both with and without CAD in less dense breast as compared to dense breast and detection of lesion is better in dense breast without CAD than with CAD.