Detection of masses and microcalcifications of breast cancer on digital mammograms: comparison among hard-copy film, 3-megapixel liquid crystal display (LCD) monitors and 5-megapixel LCD monitors: an observer performance study

The purpose of the study was to compare observer performance in the detection of masses and microcalcifications of breast cancer among hard-copy reading and soft-copy readings using 3-megapixel (3M) and 5-megapixel (5M) liquid crystal display (LCD) monitors. For the microcalcification detection test, we prepared 100 mammograms: 40 surgically verified cancer cases and 60 normal cases. For the mass detection test, we prepared 100 mammograms: 50 cancer cases and 50 normal cases. After six readers assessed both microcalcifications and masses set for each modality, receiver operating characteristic (ROC) analysis was performed. The average A_zs for mass detection using a hard copy and 3M and 5M LCD monitors were 0.923, 0.927 and 0.920, respectively; there were no significant differences. The average A_z for microcalcification detection using hard copy, 3M and 5M LCD monitors was 0.977, 0.954 and 0.972, respectively. There were no significant differences, but the P-values between the hard copy and 3M LCD monitor and that between the 3M and 5M LCD monitor were 0.08 and 0.09, respectively. In conclusion, the observer performances for detecting masses of breast cancers were comparable among the hard copy and two LCD monitors; however, soft-copy reading with a 3M LCD monitor showed slightly lower observer performance for detecting microcalcifications of breast cancers than hard-copy or 5M LCD monitor reading.     

Observer variability in screen-film mammography versus full-field digital mammography with soft-copy reading

Full-field digital mammography (FFDM) with soft-copy reading is more complex than screen-film mammography (SFM) with hard-copy reading. The aim of this study was to compare inter- and intraobserver variability in SFM versus FFDM of paired mammograms from a breast cancer screening program. Six radiologists interpreted mammograms of 232 cases obtained with both techniques, including 46 cancers, 88 benign lesions, and 98 normals. Image interpretation included BI-RADS categories. A case consisted of standard two-view mammograms of one breast. Images were scored in two sessions separated by 5 weeks. Observer variability was substantial for SFM as well as for FFDM, but overall there was no significant difference between the observer variability at SFM and FFDM. Mean kappa values were lower, indicating less agreement, for microcalcifications compared with masses. The lower observer agreement for microcalcifications, and especially the low intraobserver concordance between the two imaging techniques for three readers, was noticeable. The level of observer agreement might be an indicator of radiologist performance and could confound studies designed to separate diagnostic differences between the two imaging techniques. The results of our study confirm the need for proper training for radiologists starting FFDM with soft-copy reading in breast cancer screening. Presented at ECR, Wien 2006.     

Evaluation of computer-aided detection of lesions in mammograms obtained with a digital phase-contrast mammography system

A computer-aided detection (CAD) system was evaluated for its ability to detect microcalcifications and masses on images obtained with a digital phase-contrast mammography (PCM) system, a system characterised by the sharp images provided by phase contrast and by the high resolution of 25-μm-pixel mammograms. Fifty abnormal and 50 normal mammograms were collected from about 3,500 mammograms and printed on film for reading on a light box. Seven qualified radiologists participated in an observer study based on receiver operating characteristic (ROC) analysis. The average of the areas under ROC curve (AUC) values for the ROC analysis with and without CAD were 0.927 and 0.897 respectively (P?=?0.015). The AUC values improved from 0.840 to 0.888 for microcalcifications (P?=?0.034) and from 0.947 to 0.962 for masses (P?=?0.025) respectively. The application of CAD to the PCM system is a promising approach for the detection of breast cancer in its early stages.     

Effect of soft-copy display supported by CAD on mammography screening performance

Diagnostic performance and reading speed for conventional mammography film reading is compared to reading digitized mammograms on a dedicated workstation. A series of mammograms judged negative at screening and corresponding priors were collected. Half were diagnosed as cancer at the next screening, or earlier for interval cancers. The others were normal. Original films were read by fifteen experienced screening radiologists. The readers annotated potential abnormalities and estimated their likelihood of malignancy. More than 1 year later, five radiologists reread a subset of 271 cases (88 cancer cases having visible signs in retrospect and 183 normals) on a mammography workstation after film digitization. Markers from a computer-aided detection (CAD) system for microcalcifications were available to the readers. Performance was evaluated by comparison of A_z-scores based on ROC and multiple-Reader multiple-case (MRMC) analysis, and localized receiver operating characteristic (LROC) analysis for the 271 cases. Reading speed was also determined. No significant difference in diagnostic performance was observed between conventional and soft-copy reading. Average A_z-scores were 0.83 and 0.84 respectively. Soft-copy reading was only slightly slower than conventional reading. Using a mammography workstation including CAD for detection of microcalcifications, soft-copy reading is possible without loss of quality or efficiency.     

Diagnostic performance of detecting breast cancer on computed radiographic (CR) mammograms: comparison of hard copy film, 3-megapixel liquid-crystal-display (LCD) monitor and 5-megapixel LCD monitor

The purpose was to compare observer performance in the detection of breast cancer using hard-copy film, and 3-megapixel (3-MP) and 5-megapixel (5-MP) liquid crystal display (LCD) monitors in a simulated screening setting. We amassed 100 sample sets, including 32 patients with surgically proven breast cancer (masses present, N = 12; microcalcifications, N = 10; other types, N = 10) and 68 normal controls. All the mammograms were obtained using computed radiography (CR; sampling pitch of 50 μm). Twelve mammographers independently assessed CR mammograms presented in random order for hard-copy and soft-copy reading at minimal 4-week intervals. Observers rated the images on seven-point (1 to 7) and continuous (0 to 100) malignancy scales. Receiver-operating-characteristics analysis was performed, and the average area under the curve (AUC) was calculated for each modality. The jackknife method with the Bonferroni correction was applied to multireader/multicase analysis. The average AUC values for the 3-MP LCD, 5-MP LCD, and hard-copy film were 0.954, 0.947, and 0.956 on the seven-point scale and 0.943, 0.923, and 0.944 on the continuous scale, respectively. There were no significant differences among the three modalities on either scale. Soft-copy reading using 3-MP and 5-MP LCDs is comparable to hard-copy reading for detecting breast cancer.     

Comparing the performance of mammographic enhancement algorithms: a preference study

OBJECTIVE: The objective of this study was to compare the performance of four image enhancement algorithms on secondarily digitized (i.e., digitized from film) mammograms containing masses and microcalcifications of known pathology in a clinical soft-copy display setting. MATERIALS AND METHODS: Four different image processing algorithms (adaptive unsharp masking, contrast-limited adaptive histogram equalization, adaptive neighborhood contrast enhancement, and wavelet-based enhancement) were applied to one image of secondarily digitized mammograms of forty cases (10 each of benign and malignant masses and 10 each of benign and malignant microcalcifications). The four enhanced images and the one unenhanced image were displayed randomly across three high-resolution monitors. Four expert mammographers ranked the unenhanced and the four enhanced images from 1 (best) to 5 (worst). RESULTS: For microcalcifications, the adaptive neighborhood contrast enhancement algorithm was the most preferred in 49% of the interpretations, the wavelet-based enhancement in 28%, and the unenhanced image in 13%. For masses, the unenhanced image was the most preferred in 58% of cases, followed by the unsharp masking algorithm (28%). CONCLUSION: Appropriate image enhancement improves the visibility of microcalcifications. Among the different algorithms, the adaptive neighborhood contrast enhancement algorithm was preferred most often. For masses, no significant improvement was observed with any of these image processing approaches compared with the unenhanced image. Different image processing approaches may need to be used, depending on the type of lesion. This study has implications for the practice of digital mammography.     

Improved interpretation of digitized mammography with wavelet processing: a localization response operating characteristic study

OBJECTIVE: Our objective was the implementation and evaluation of a novel enhancement technique for improved interpretation of high-resolution digitized mammograms from computer monitors. MATERIALS AND METHODS: A wavelet algorithm was designed to attenuate the image spectral characteristics responsible for the long-range image correlation that often interferes with digital display. The algorithm was evaluated with a localization response operating characteristic (LROC) experiment with 500 negative, benign, and cancer cases with masses and calcification clusters. Three observers reviewed the original and wavelet-enhanced images on a 5-Mpixel monitor using a custom-made workstation user interface. RESULTS: Performance indexes were estimated for four different case combinations, each observer, and each interpretation mode. Wavelet enhancement improved the performance of all observers in all case combinations. Detection accuracy ranged from 0.678 to 0.827 for the unprocessed original data and 0.709-0.871 for the enhanced cases. Localization accuracy ranged from 0.547 to 0.785 for the original images and 0.568-0.847 for the enhanced cases, yielding increases of 5-15%. The difference between enhanced and original performances was statistically significant at the 0.10 level and in a few combinations at the 0.05 level. CONCLUSION: Soft-copy digitized mammography could replace standard film mammography under appropriate display parameters and conditions. The optimization of the soft-copy quality is expected to require more advanced processing techniques than standard gray-scale adjustments. Wavelet-based algorithms, such as the one proposed here, offer better soft-copy quality than the originals and a better starting point for additional manual gray-scale adjustments or automated postprocessing.     

Interpretation of digital mammograms: comparison of speed and accuracy of soft-copy versus printed-film display

PURPOSE: To compare the speed and accuracy of the interpretations of digital mammograms by radiologists by using printed-film versus soft-copy display. MATERIALS AND METHODS: After being trained in interpretation of digital mammograms, eight radiologists interpreted 63 digital mammograms, all with old studies for comparison. All studies were interpreted by all readers in soft-copy and printed-film display, with interpretations of images in the same cases at least 1 month apart. Mammograms were interpreted in cases that included six biopsy-proved cancers and 20 biopsy-proved benign lesions, 20 cases of probably benign findings in patients who underwent 6-month follow-up, and 17 cases without apparent findings. Area under the receiver operating characteristic curve (A(z)), sensitivity, and specificity were calculated for soft-copy and printed-film display. RESULTS: There was no significant difference in the speed of interpretation, but interpretations with soft-copy display were slightly faster. The differences in A(z), sensitivity, and specificity were not significantly different; A(z) and sensitivity were slightly better for interpretations with printed film, and specificity was slightly better for interpretations with soft copy. CONCLUSION: Interpretation with soft-copy display is likely to be useful with digital mammography and is unlikely to significantly change accuracy or speed.     

Soft-copy reading in digital mammography of microcalcifications: diagnostic performance of a 5-megapixel cathode ray tube monitor versus a 3-megapixel liquid crystal display monitor in a clinical setting

BACKGROUND: A recent study using dedicated contrast-detail phantoms showed that the image quality of a 3-megapixel (M) monitor can approach that of a 5M monitor in digital mammography. PURPOSE: To compare a 5M cathode ray tube (CRT) monitor with a 3M liquid crystal display (LCD) monitor for soft-copy reading of digital mammography of microcalcifications in a clinical setting. MATERIAL AND METHODS: 100 screen-detected microcalcification lesions (34 malignant and 66 benign) without mass that had been evaluated with 11-gauge stereotactic vacuum-assisted breast biopsy or definitive surgery were recruited into the study. One radiologist analyzed the soft-copy mammograms on a 5M CRT monitor and a 3M LCD monitor with 5 months between interpretations and scored the likelihood of malignancy and calcification distribution on a five-point scale. Calcification morphology and breast density were scored on a four-point scale. Positive predictive value (PPV) and negative predictive value (NPV) were calculated on the basis of a Breast Imaging Reporting and Data System. The interpretation time was also measured. RESULTS: There was no significant difference in the likelihood of malignancy (P = 0.655), calcification morphology (P = 0.168), calcification distribution (P = 0.11), and breast density (P = 0.0608). The PPV and NPV of soft-copy reading on the 5M CRT monitor was 57% (30/53) and 91% (43/47), respectively, identical to the results using the 3M LCD monitor. The total interpretation time averaged 88 s for the 5M CRT monitor and 67 s for the 3M LCD monitor (P<0.0001). CONCLUSION: Soft-copy reading of a digital mammography of microcalcifications with a 3M LCD monitor was similar in diagnostic performance to a 5M CRT monitor in this study.     

Digital mammography. ROC studies of the effects of pixel size and unsharp-mask filtering on the detection of subtle microcalcifications

We investigated the spatial resolution requirement and the effect of unsharp-mask filtering on the detectability of subtle microcalcifications in digital mammography. Digital images were obtained by digitizing conventional screen-film mammograms with a 0.1 X 0.1 mm2 pixel size, processed with unsharp masking, and then reconstituted on film with a Fuji image processing/simulation system (Fuji Photo Film Co., Tokyo, Japan). Twenty normal cases and 12 cases with subtle microcalcifications were included. Observer performance experiments were conducted to assess the detectability of subtle microcalcifications in the conventional, the unprocessed digital, and the unsharp-masked mammograms. The observer response data were evaluated using receiver operating characteristic (ROC) and LROC (ROC with localization) analyses. Our results indicate that digital mammograms obtained with 0.1 X 0.1 mm2 pixels provide lower detectability than the conventional screen-film mammograms. The detectability of microcalcifications in the digital mammograms is improved by unsharp-mask filtering; the processed mammograms still provide lower accuracy than the conventional mammograms, however, chiefly because of increased false-positive detection rates for the processed images at each subjective confidence level. Viewing unprocessed digital and unsharp-masked images in pairs resulted in approximately the same detectability as that obtained with the unsharp-masked images alone. However, this result may be influenced by the fact that the same limited viewing time was necessarily divided between the two images.     

Can computer-aided detection with double reading of screening mammograms help decrease the false-negative rate? Initial experience

PURPOSE: To retrospectively evaluate the role of computer-aided detection (CAD) in reducing the rate of false-negative (FN) findings on screening mammograms considered normal at initial double reading. MATERIALS AND METHODS: At the authors' institution, independent prospective double readings in which the second reader is not blinded to results of the first reading are performed routinely for all mammograms. When cancer is diagnosed, prior mammograms also are reviewed with double reading to determine cancer visibility. Findings are categorized as (a) no evidence of cancer on any prior screening mammogram and patient presents more than 1 year after prior screening, (b) no evidence of cancer on any prior screening mammogram and patient presents with symptoms within 1 year after prior screening (year-interval occult false-negative), or (c) cancer visible. The clinical director separately evaluates each case in the same way. In 2000, 519 histologically proved breast cancers were diagnosed, including 132 for which patients sought a second opinion and FN findings were not tracked. Prior screening mammograms were available in 318 of the other 387 cases. Five radiologists in two reading sessions independently reviewed current and prior mammograms to categorize visible cancers as either threshold or actionable FN findings. Visible cancers deemed actionable by at least three of five readers were analyzed with a commercially available CAD system. FN rates were calculated prior to and after CAD analysis. RESULTS: Twenty-seven occult and 71 visible cancers were found (total FN findings, 98). Three of five readers considered 52 (73%) of 71 visible cancers actionable. The CAD system correctly marked 37 (71%) of these 52 on prior screening mammograms (19 [65%] of 29 masses, seven [88%] of eight microcalcifications, seven [78%] of nine architectural distortions, and four [67%] of six masses with microcalcifications). The FN rate was 98 (31%) of 318 before CAD and 61 (19%) of 318 after CAD. CONCLUSION: In this retrospective review of this small subset of cancers, it appears that CAD has the potential to decrease the FN rate at double reading by more than one-third (from 31% to 19%). The CAD system correctly marked 37 (71%) of 52 actionable findings read as negative in previous screening years.     

Evaluation of a wavelet-based computer-assisted detection system for identifying microcalcifications in digital full-field mammography

PURPOSE: To evaluate a new wavelet-based computer-assisted detection (CAD) system for detecting and enhancing microcalcifications. MATERIAL AND METHODS: A total of 280 mammograms acquired by full-field digital mammography (Senographe 2000D; G.E. Medical Systems Milwaukee, Wisc., USA) were analyzed with and without a new wavelet-based CAD system for detecting and enhancing microcalcifications. The mammograms comprised roughly equal numbers of cases from each of the BIRADS (Breast Imaging, Reporting and Data System, according to the American College of Roentgenology) categories 1-5. Histologic confirmation was available for all of the 180 cases assigned BIRADS categories 3-5. Four readers interpreted all 280 images for suspicious microcalcifications using a scale of 1-5. The readers alternately assessed 5 images with and 5 without CAD. In a second reading immediately following the first, the readers had to reassess the 280 mammograms. The images that had already been interpreted without CAD were now presented with CAD and vice versa. The images were interpreted as soft copies on a diagnostic mammography workstation (Image Diagnost GmbH, Neufahrn/Munich, Germany). All images interpreted with CAD were presented with enhancement of microcalcifications by wavelet algorithms and prompting of microcalcifications. ROC (receiver operating characteristic) analyses were performed, and image interpretation time with and without CAD was measured. RESULTS: The overall time for interpretation required by all 4 readers together was 483 min with CAD compared to 580 min without CAD. ROC analysis revealed no significant advantage of CAD for the individual readers. Readers 3 (0.811/0.817) and 4 (0.799/0.843) had a slightly improved AUC (area under the curve) with CAD. Readers 1 and 2 had a slightly lower AUC with CAD (0.832 versus 0.861 and 0.818 versus 0.849). CONCLUSION: The CAD system significantly (P<0.05, t test) speeded up image interpretation with respect to the identification of microcalcifications, while the diagnostic quality remained almost identical under the study conditions.     

Breast lesion detection and classification: comparison of screen-film mammography and full-field digital mammography with soft-copy reading--observer performance study

PURPOSE: To retrospectively compare screen-film and full-field digital mammography with soft-copy interpretation for reader performance in detection and classification of breast lesions in women in a screening program. MATERIALS AND METHODS: Regional ethics committee approved the study; signed patient consents were obtained. Two-view mammograms were obtained with digital and screen-film systems at previous screening studies. Six readers interpreted images. Interpretation included Breast Imaging Reporting and Data System (BI-RADS) and five-level probability-of-malignancy scores. A case was one breast, with two standard views acquired with both screen-film mammography and digital mammography. The standard for an examination with normal findings was classification of normal (category 1) assigned by two independent readers; for cases with benign findings, the standard was benign results at diagnostic work-up in patients who were recalled. Cases with normal or benign findings that manifested as neither interval cancer nor as cancer at subsequent screening were considered the standard. All cancers were confirmed histologically. Images were interpreted by readers in two sessions 5 weeks apart; the same case was not seen twice in any session. Receiver operating characteristic (ROC) analysis and, for a given true-positive fraction, 2 x 2 table analysis and the McNemar test were used. For binary outcome, classification of BI-RADS category 3 or higher was defined as positive for cancer. RESULTS: Cases with proved findings (n = 232) were displayed: 46 with cancers, 88 with benign findings, and 98 with normal findings. ROC analysis for all readers and all cases revealed a higher area under ROC curve (A(z)) for digital mammography (0.916) than for screen-film mammography (0.887) (P = .22). Five of six readers had a higher performance rating with digital mammography; one of five demonstrated a significant difference in favor of digital mammography with A(z) values; two showed a significant difference in favor of digital mammography with ROC analysis for a given false-positive fraction (P = .01 and .03, respectively). For cases with cancer, digital mammography resulted in correct classification of an average of three additional cancers per reader. For digital versus screen-film mammography, 2 x 2 table analysis for cancers revealed a higher true-positive rate; for benign masses, a higher true-negative rate. Neither of these differences nor any others from analysis of subgroups between the modalities were significant. CONCLUSION: Digital mammography allowed correct classification of more breast cancers than did screen-film mammography. A(z) value was higher for digital mammography; this difference was not significant.     

Comparison of LCD and CRT displays based on efficacy for digital mammography

RATIONALE AND OBJECTIVES: To compare two display technologies, cathode ray tube (CRT) and liquid crystal display (LCD), in terms of diagnostic accuracy for several common clinical tasks in digital mammography. MATERIALS AND METHODS: Simulated masses and microcalcifications were inserted into normal digital mammograms to produce an image set of 400 images. Images were viewed on one CRT and one LCD medical-quality display device by five experienced breast-imaging radiologists who rated the images using a categorical rating paradigm. The observer data were analyzed to determine overall classification accuracy, overall lesion detection accuracy, and accuracy for four specific diagnostic tasks: detection of benign masses, malignant masses, and microcalcifications, and discrimination of benign and malignant masses. RESULTS: Radiologists had similar overall classification accuracy (LCD: 0.83 +/- 0.01, CRT: 0.82 +/- 0.01) and lesion detection accuracy (LCD: 0.87 +/- 0.01, CRT: 0.85 +/- 0.01) on both displays. The difference in accuracy between LCD and CRT for the detection of benign masses, malignant masses, and microcalcifications, and discrimination of benign and malignant masses was -0.019 +/- 0.009, 0.020 +/- 0.008, 0.012 +/- 0.013, and 0.0094 +/- 0.011, respectively. Overall, the two displays did not exhibit any statistically significant difference (P > .05). CONCLUSION: This study explored the suitability of two different soft-copy displays for the viewing of mammographic images. It found that LCD and CRT displays offer similar clinical utility for mammographic tasks.     

Computer-aided diagnosis in full digital mammography

RATIONALE AND OBJECTIVES: The authors clarify the detection rates for breast cancerous tumors and clustered microcalcifications with computer-aided diagnosis (CAD) based on Fuji Computed Radiography. The authors also determine whether mammographic reading with CAD contributes to the discovery of breast cancer. METHODS: Data acquired by Fuji Computed Radiography 9000, which consisted of 4148 digital mammograms including 267 cases of breast cancer, was transferred directly to an analysis workstation where an original software program determined extraction rates for breast tumors and clustered microcalcifications. Furthermore, using another 344 mammograms from 86 women, observer performance studies were conducted on five doctors for receiver operating characteristic (ROC) analysis. RESULTS: Sensitivity to breast cancerous tumors and clustered microcalcifications were 89.9% and 92.8%, respectively false-positive rates were 1.35 and 0.40 per image, respectively. The observer performance studies indicate that an average Az value for the five doctors was greater with the CAD system than with a film-only reading without CAD, and that a reading with CAD was significantly superior at P < 0.022. CONCLUSIONS: It has been shown that CAD based on Fuji Computed Radiography offers good detection rates for both breast cancerous tumors and clustered microcalcifications, and that the reading of mammograms with this CAD system would provide potential improvement in diagnostic accuracy for breast cancer.     

Spectral phase based medical image processing

RATIONALE AND OBJECTIVES: To exploit the spectral phase characteristics of digital or digitized mammograms for early detection of microcalcifications, shape, and sizes of suspected lesions and to demonstrate its use for training radiologists to discriminate signal features in different spatially varying backgrounds. MATERIALS AND METHODS: We propose two algorithms: in the phase-only image (POI) reconstruction algorithm the spectral phase of the digital mammogram is extracted from its Fourier spectrum. This is coupled with unit magnitude and inverse Fourier transformed to reconstruct the POI thus enhancing the features of interest such as microcalcifications, shape, and sizes of suspected lesions. In the algorithm for image reconstruction from a priori phase-only information, spectral phase is used to extract signal features of the digital mammogram and then this is combined with spectral magnitude that is extracted and averaged over an ensemble of unrelated digital mammograms. RESULTS: The results for several digital phantoms and mammograms show that POI reconstructs only high spatial frequencies related to the features such as microcalcifications, shape, and size of masses like cysts and tumors. The results on image reconstruction from a priori phase-only information demonstrate the changes in the visibility of signal features when buried in a wide variety of real world mammogram backgrounds with different densities. CONCLUSION: The POI can aid radiologists in early detection of microcalcifications, lesions, and other masses of interest in digital mammograms. This reconstruction method is self-adaptive to changes in the background. The image reconstruction from a priori phase-only information can help the radiologist as a training tool in his decision-making process. Preliminary experiments indicate the potential of the techniques for early diagnosis of breast cancer. Clinical studies on these algorithm procedures are in progress for application as a diagnostic CAD tool in digital mammography. These methods can in general be applied to other medical images such as CT and MRI images.     

Value of CAD systems

PURPOSE: Early detection of breast cancer enables for the reduction of mortality. The purpose of this article is to describe commercially available systems for computer-aided diagnosis (CAD) for mammograms and to analyze their diagnostic potential and utility. MATERIALS AND METHODS: Up to now, there are three CAD-systems available, the Image Checker M 1000 (R2-Technology, USA), the Second Look-system (CADx Medical Systems) and the Mammex TR (Scanis Inc., USA). Most of the present studies are done with the R2-system. The mammographies have been digitalized secondarily. Different algorithms recognized microcalcifications and masses. The connection between full field digital mammography systems and DICOM-networks is possible. RESULTS: In retrospective and one large prospective study with 12.860 patients it could be shown that sensitivity of the investigator with CAD could be improved up to 19%, microcalcifications are yielded with CAD in 100%, masses in up to 80%. CONCLUSION: Double-reading with CAD-systems can increase early breast cancer detection effectively. Regarding the development of full field digital mammography we are looking forward to further innovations.     

Reproducibility of Computer-Aided Detection Marks in Digital Mammography

Objective

To evaluate the performance and reproducibility of a computer-aided detection (CAD) system in mediolateral oblique (MLO) digital mammograms taken serially, without release of breast compression.

Materials and Methods

A CAD system was applied preoperatively to the full-field digital mammograms of two MLO views taken without release of breast compression in 82 patients (age range: 33 - 83 years; mean age: 49 years) with previously diagnosed breast cancers. The total number of visible lesion components in 82 patients was 101: 66 masses and 35 microcalcifications. We analyzed the sensitivity and reproducibility of the CAD marks.

Results

The sensitivity of the CAD system for first MLO views was 71% (47/66) for masses and 80% (28/35) for microcalcifications. The sensitivity of the CAD system for second MLO views was 68% (45/66) for masses and 17% (6/35) for microcalcifications. In 84 ipsilateral serial MLO image sets (two patients had bilateral cancers), identical images, regardless of the existence of CAD marks, were obtained for 35% (29/84) and identical images with CAD marks were obtained for 29% (23/78). Identical images, regardless of the existence of CAD marks, for contralateral MLO images were 65% (52/80) and identical images with CAD marks were obtained for 28% (11/39). The reproducibility of CAD marks for the true positive masses in serial MLO views was 84% (42/50) and that for the true positive microcalcifications was 0% (0/34).

Conclusion

The CAD system in digital mammograms showed a high sensitivity for detecting masses and microcalcifications. However, reproducibility of microcalcification marks was very low in MLO views taken serially without release of breast compression. Minute positional change and patient movement can alter the images and result in a significant effect on the algorithm utilized by the CAD for detecting microcalcifications.     

Understanding CAD (computer-aided diagnosis) in mammography

Generalization of breast screening programs requires efficient double reading of mammograms, which allows reduction of false negative interpretations, but it may be difficult to achieve. CAD (Computed Aided Detection) systems are dramatically improving and can now assist in the detection of suspicious mammographic lesions, either suspicious microcalcifications, masses or architectural distortion. Characterization of the lesions is improving as well. CAD mammography might complete or substitute to "human" double reading. The aim of this review is to present the main CAD systems commercially available, review the principles of CAD and discuss the results of CAD mammography. Specifically, the role of CAD within breast screening program, according to the results of recent prospective studies will be discussed.     

Radiologists' preferences for digital mammographic display. The International Digital Mammography Development Group

PURPOSE: To determine the preferences of radiologists among eight different image processing algorithms applied to digital mammograms obtained for screening and diagnostic imaging tasks. MATERIALS AND METHODS: Twenty-eight images representing histologically proved masses or calcifications were obtained by using three clinically available digital mammographic units. Images were processed and printed on film by using manual intensity windowing, histogram-based intensity windowing, mixture model intensity windowing, peripheral equalization, multiscale image contrast amplification (MUSICA), contrast-limited adaptive histogram equalization, Trex processing, and unsharp masking. Twelve radiologists compared the processed digital images with screen-film mammograms obtained in the same patient for breast cancer screening and breast lesion diagnosis. RESULTS: For the screening task, screen-film mammograms were preferred to all digital presentations, but the acceptability of images processed with Trex and MUSICA algorithms were not significantly different. All printed digital images were preferred to screen-film radiographs in the diagnosis of masses; mammograms processed with unsharp masking were significantly preferred. For the diagnosis of calcifications, no processed digital mammogram was preferred to screen-film mammograms. CONCLUSION: When digital mammograms were preferred to screen-film mammograms, radiologists selected different digital processing algorithms for each of three mammographic reading tasks and for different lesion types. Soft-copy display will eventually allow radiologists to select among these options more easily.