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.     

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.     

Sliding window adaptive histogram equalization of intraoral radiographs: effect on image quality

OBJECTIVES: To investigate whether contrast enhancement by non-interactive, sliding window adaptive histogram equalization (SWAHE) can enhance the image quality of intraoral radiographs in the dental clinic. METHODS: Three dentists read 22 periapical and 12 bitewing storage phosphor (SP) radiographs. For the periapical readings they graded the quality of the examination with regard to visually locating the root apex. For the bitewing readings they registered all occurrences of approximal caries on a confidence scale. Each reading was first done on an unprocessed radiograph ("single-view"), and then re-done with the image processed with SWAHE displayed beside the unprocessed version ("twin-view"). The processing parameters for SWAHE were the same for all the images. RESULTS: For the periapical examinations, twin-view was judged to raise the image quality for 52% of those cases where the single-view quality was below the maximum. For the bitewing radiographs, there was a change of caries classification (both positive and negative) with twin-view in 19% of the cases, but with only a 3% net increase in the total number of caries registrations. For both examinations interobserver variance was unaffected. CONCLUSIONS: Non-interactive SWAHE applied to dental SP radiographs produces a supplemental contrast enhanced image which in twin-view reading improves the image quality of periapical examinations. SWAHE also affects caries diagnosis of bitewing images, and further study using a gold standard is warranted.     

Comparison of independent double readings and computer-aided diagnosis (CAD) for the diagnosis of breast calcifications

RATIONALE AND OBJECTIVES: The aim of the study is to compare independent double readings by radiologists and computer-aided diagnosis (CAD) in diagnostic interpretation of mammographic calcifications. MATERIALS AND METHODS: Ten radiologists independently interpreted 104 mammograms containing clustered microcalcifications. Forty-six of these were malignant and 58 were benign at biopsy. Radiologists read the images with and without a computer aid by using a counterbalanced study design. Sensitivity and specificity were calculated from observer biopsy recommendations, and receiver operating characteristic (ROC) curves were computed from their diagnostic confidence ratings. Unaided double-reading sensitivity and specificity values were derived post hoc by using three different objective rules and an additional rule of simulated-optimal double reading that assumed that consultations for resolving two radiologists' different independent diagnoses always produce the correct clinical recommendation. ROC curves of unaided double readings were obtained according to the literature. RESULTS: Single reading without computer aid yielded 74% sensitivity and 32% specificity, whereas CAD reading yielded 87% sensitivity and 42% specificity and appeared on a higher ROC curve (P < .0001). Three methods of formulating independent double readings generated sensitivities between 59% and 89%, specificities between 50% and 13%, and operating points that moved essentially along the average unaided single-reading ROC curve. ROC curves of unaided independent double readings showed small, statistically insignificant improvement over those of unaided single readings. Results of the simulated-optimal double reading were similar to CAD: 89% sensitivity and 50% specificity. CONCLUSION: Independent double readings of mammographic calcifications may not improve diagnostic performance. CAD reading improves diagnostic performance to an extent approaching the maximum possible performance.     

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.     

Detecting clustered microcalcifications in the female breast: secondary digitized images versus mammograms.

We compared the detection of clustered microcalcifications by means of conventional mammograms and by means of secondary digitized images with a spatial resolution of 2048 x 1684 pixels and a contrast resolution of 12 bit. A Receiver Operating Characteristic (ROC) study was carried out using a cadaver breast showing phantom microcalcifications. A set of 100 mammograms was evaluated by two experienced senior radiologists. The ROC scores obtained with the digital images were 10% lower than those obtained with the conventional images. This difference however does not reach statistical significance. The use of a digital zoom function based on pixel duplication is also investigated. This zoom function does not produce a change in the diagnostic accuracy of the digital method. Attention is also paid to the advantages and disadvantages encountered by the radiologists when working on the digital viewing system. The most important drawback seems to be that it is considerably more time consuming than the conventional procedure, and this is especially due to the long loading time of the images and to the absence of window and level preselections.     

A comparison of digitized storage phosphors and conventional mammography in the detection of malignant microcalcifications

The detectability of malignant tumor-derived microcalcifications with conventional mammography was compared to that with digital images (2000 X 2510 pixels by 10 bits) derived from a storage phosphor-based digital radiography system capable of 5 line pair/mm resolution at identical exposure factors (30 kVp, 250 mAs, 65 cm film-focus distance). Microcalcifications (50-800 microns in diameter) were randomly superimposed on a preserved human breast specimen. ROC analysis based on 480 observations made by four readers indicated that the ability to detect the calcifications with digital images (ROC area = 0.871 +/- 0.066) was equivalent to conventional mammography (ROC area = 0.866 +/- 0.075) despite lower spatial resolution. With digital mammography, 62% of all clusters were correctly localized, but only 23.6% of the individual calcifications were counted. With conventional mammography 61% of all clusters were correctly localized, but significantly more of the individual calcifications (31.5%) were counted.     

The effects of gray scale image processing on digital mammography interpretation performance

RATIONALE AND OBJECTIVES: To determine the effects of three image-processing algorithms on diagnostic accuracy of digital mammography in comparison with conventional screen-film mammography. MATERIALS AND METHODS: A total of 201 cases consisting of nonprocessed soft copy versions of the digital mammograms acquired from GE, Fischer, and Trex digital mammography systems (1997-1999) and conventional screen-film mammograms of the same patients were interpreted by nine radiologists. The raw digital data were processed with each of three different image-processing algorithms creating three presentations-manufacturer's default (applied and laser printed to film by each of the manufacturers), MUSICA, and PLAHE-were presented in soft copy display. There were three radiologists per presentation. RESULTS: Area under the receiver operating characteristic curve for GE digital mass cases was worse than screen-film for all digital presentations. The area under the receiver operating characteristic for Trex digital mass cases was better, but only with images processed with the manufacturer's default algorithm. Sensitivity for GE digital mass cases was worse than screen film for all digital presentations. Specificity for Fischer digital calcifications cases was worse than screen film for images processed in default and PLAHE algorithms. Specificity for Trex digital calcifications cases was worse than screen film for images processed with MUSICA. CONCLUSION: Specific image-processing algorithms may be necessary for optimal presentation for interpretation based on machine and lesion type.     

Effects of image processing on nodule detection rates in digitized chest radiographs: ROC study of observer performance

To evaluate the effects of image processing in digitized chest radiographs when high-resolution images are used, an examination was done in which the detection of pulmonary nodules in unprocessed digitized chest radiographs was compared with that in images that had undergone processing with two methods, adaptive filtration and histogram equalization. The processing techniques have been optimized in previous work to selectively enhance the retrocardiac and subdiaphragmatic areas without significant alteration of detail in the lung. Eight observers were shown 150 test radiographs (50 unprocessed, 50 processed with adaptive filtration, 50 processed with histogram equalization) containing 150 nodules. The results indicate a statistically significant (P less than .03) difference, with highest observer performance in the chest radiographs processed with adaptive filtration (median area under ROC curve = 0.78), compared with unprocessed images (median = 0.68) and chest radiographs processed with histogram equalization (median = 0.62). Performance in the lung was not significantly different. Adaptive filtration applied to selectively enhance underexposed areas of film images may improve nodule detection. Histogram equalization provided no improvement in performance.     

Mammographic and histologic correlations of microcalcifications

The majority of microcalcifications found on mammograms are associated with benign disease; however, some types accompany malignant disease. By correlating histologic with mammographic findings, the radiologist may gain an understanding of the morphologic characteristics and distribution of microcalcifications. We present radiologic and histologic images from a series of cases of nonpalpable, clustered microcalcifications. Such microcalcifications can be divided into two basic histologic groups: lobular and ductal. Although rounded, similarly shaped lobular calcifications can be differentiated mammographically from ductal calcifications with their irregular margins and varying size and shape, both types can be associated with benign and malignant processes. Biopsy is usually needed to confirm the diagnosis when clustered microcalcifications are found at mammography.     

Analogic versus digital mammographic examination a radiological study of mammary microcalcifications on 52 surgical samples

PURPOSE: Digital mammography is known to have lower spatial resolution compared to conventional analogic mammography. The aim of this study was to evaluate whether this physical feature could compromise the perception of microcalcifications in radiological findings. MATERIALS AND METHODS: Fifty-two surgical samples of non-palpable breast lesions with microcalcifications were imaged using both techniques. The images were examined by four different radiologists. Data processing was limited to comparing the number of microcalcifications found on the conventional and digital images, in both standard and magnified modality. The cases were classified into 3 groups according to the number of calcifications demonstrated in the surgical sample: less than 10, 10 to 30, and more than 30. The differences in the count of microcalcifications with the two acquisition modalities were evaluated with the Kappa test. In order to compare the differences we synthesised by percentage those cases exhibiting a larger or lesser number of calcifications. RESULTS: The Kappa test was 0.546 in standard analogic vs standard digital, 0.582 in magnified analogic vs magnified digital, 0.828 in standard analogic vs magnified analogic and 0.492 in standard digital vs magnified digital. The most significant results were observed on comparing the magnifications produced with the two modalities: in 25% of cases, digital magnification detected more calcifications than did traditional magnification. The number of cases where standard digital images allowed the detection of more calcifications than standard analogic images was significant, although less important (17.8%). CONCLUSIONS: The study was able to provide data that confirm the overall equivalence of the two techniques, as far as subtle mammographic findings (such as microcalcifications) are concerned. In particular, as applied to the series we examined, there is a cautious advantage in favour of the digital technique. More clinical studies, on larger series, will be necessary for a further and more thorough comparison of the two techniques, so that the results might be consistently useful in clinical practice.     

Zooming method (× 2.0) of digital mammography vs digital magnification view (× 1.8) in full-field digital mammography for the diagnosis of microcalcifications

The purpose of this study was to determine whether the interpretation of microcalcifications assessed on images zoomed (× 2.0) from digital mammograms is at least equivalent to that from digital magnification mammography (× 1.8) with respect to diagnostic accuracy and image quality. Three radiologists with different levels of experience in mammography reviewed each full-field digital mammography reader set for 185 patients with pathologically proven microcalcification clusters, which consisted of digital magnification mammograms (MAGs) with a magnification factor of 1.8 and images zoomed from mammograms (ZOOM) with a zoom factor of 2.0. Each radiologist rated their suspicion of breast cancer in microcalcific lesions using a six-point scale and the image quality and their confidence in the decisions using a five-point scale. Results were analysed according to display methods using areas under the receiver operating characteristic curves (A_z value) for ZOOM and MAGs to interpret microcalcifications, and the Wilcoxon matched pairs signed rank test for image quality and confidence levels. There was no statistically significant difference in the level of suspicion of breast cancer between the ZOOM and MAG groups (A_z = 0.8680 for ZOOM; A_z = 0.8682 for MAG; p = 0.9897). However, MAG images were significantly better than ZOOM images in terms of visual imaging quality (p < 0.001), and the confidence level with MAG was better than with ZOOM (p < 0.001). In conclusion, the performance of radiologists in the diagnosis of microcalcifications using ZOOM was similar to that using MAGs, although image quality and confidence levels were better using MAGs.Magnification mammography produces better spatial resolution and signal-to-noise ratio than does contact mammography. It is well established as a valuable adjunct to contact mammography, especially for the diagnosis of microcalcifications, despite the additional radiation exposure and increased radiation dose because of the shorter distance between the breast and X-ray source during examination [1–4].However, with respect to full-field digital mammography (FFDM), a few studies using zoomed images from contact mammograms have recently been reported and, as a result, a debate has arisen over whether a digital zooming system of FFDM can replace the magnification view of digital mammography [5–7]. Whereas Fischer et al [5] reported that zoomed images of a digital contact mammogram were equivalent to direct magnification of FFDM for the interpretation of microcalcifications, our previous report suggested that magnification mammography yielded better sensitivity and receiver operating characteristic (ROC) analysis than did zoomed images [7]. However, that study compared images zoomed by a factor of 1.3 with images magnified by a factor of 1.8. Therefore, we wondered whether using a zooming factor comparable to a magnification factor of 1.8 would yield the same results.The purpose of this study was to determine whether the diagnostic accuracy and image quality of microcalcification assessments using images twice zoomed from contact mammograms were equivalent to those obtained using digital magnification mammography by a magnification factor of 1.8.     

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.     

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.     

Independent evaluation of computer classification of malignant and benign calcifications in full-field digital mammograms

RATIONALE AND OBJECTIVES: To evaluate whether a computer-aided diagnosis (CADx) technique can accurately classify breast calcifications in full-field digital mammograms (FFDMs) as malignant or benign. The computer technique was developed previously on screen-film mammograms (SFMs) in which individual calcifications were identified manually. The present study evaluated the computer technique independently on a new database of FFDM images with automatic detection of the individual calcifications. MATERIALS AND METHODS: We analyzed 49 consecutive FFDM cases (19 cancers) that showed suspicious calcifications. Four mammography radiologists read soft-copy mammograms retrospectively and electronically indicated the region of calcifications in each image. The computer then automatically detected the individual calcifications within the indicated region and analyzed eight features of calcification morphology and distribution to arrive at an estimated likelihood of malignancy. The radiologists entered Breast Imaging Report and Data System assessments before and after seeing the computer results. Performance was analyzed using receiver operating characteristic analysis. RESULTS: Despite variability in radiologist-indicated regions of calcifications, the computer achieved consistently high performance taking input from the four radiologists (receiver operating characteristic curve area, A(z): 0.80, 0.80, 0.78, and 0.77; differences not statistically significant). Previous results showed that the computer technique achieved an A(z) value of 0.80 on SFMs, which improved radiologists' performance significantly. CONCLUSIONS: The computer technique appears to maintain consistently high performance in classifying calcifications in FFDMs as malignant or benign without requiring substantial modification from its initial development on SFMs. The computer performance appears to be robust with respect to variations in radiologists' input.     

Classification of breast ultrasound images using fractal feature

Fractal analyses have been applied successfully for the image compression, texture analysis, and texture image segmentation. The fractal dimension could be used to quantify the texture information. In this study, the differences of gray value of neighboring pixels are used to estimate the fractal dimension of an ultrasound image of breast lesion by using the fractal Brownian motion. Furthermore, a computer-aided diagnosis (CAD) system based on the fractal analysis is proposed to classify the breast lesions into two classes: benign and malignant. To improve the classification performances, the ultrasound images are preprocessed by using morphology operations and histogram equalization. Finally, the k-means classification method is used to classify benign tumors from malignant ones. The US breast image databases include only histologically confirmed cases: 110 malignant and 140 benign tumors, which were recorded. All the digital images were obtained prior to biopsy using by an ATL HDI 3000 system. The receiver operator characteristic (ROC) area index AZ is 0.9218, which represents the diagnostic performance.     

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.     

Use of artificial neural networks (computer analysis) in the diagnosis of microcalcifications on mammography.

INTRODUCTION/OBJECTIVE: The purpose of this study was to evaluate a computer based method for differentiating malignant from benign clustered microcalcifications, comparing it with the performance of three physicians. METHODS AND MATERIAL: Materials for the study are 240 suspicious microcalcifications on mammograms from 220 female patients who underwent breast biopsy, following hook wire localization under mammographic guidance. The histologic findings were malignant in 108 cases (45%) and benign in 132 cases (55%). Those clusters were analyzed by a computer program and eight features of the calcifications (density, number, area, brightness, diameter average, distance average, proximity average, perimeter compacity average) were quantitatively estimated by a specific artificial neural network. Human input was limited to initial identification of the calcifications. Three physicians-observers were also evaluated for the malignant or benign nature of the clustered microcalcifications. RESULTS: The performance of the artificial network was evaluated by receiver operating characteristics (ROC) curves. ROC curves were also generated for the performance of each observer and for the three observers as a group. The ROC curves for the computer and for the physicians were compared and the results are:area under the curve (AUC) value for computer is 0.937, for physician-1 is 0.746, for physician-2 is 0.785, for physician-3 is 0.835 and for physicians as a group is 0.810. The results of the Student's t-test for paired data showed statistically significant difference between the artificial neural network and the physicians' performance, independently and as a group. DISCUSSION AND CONCLUSION: Our study showed that computer analysis achieves statistically significantly better performance than that of physicians in the classification of malignant and benign calcifications. This method, after further evaluation and improvement, may help radiologists and breast surgeons in better predictive estimation of suspicious clustered microcalcifications and reduce the number of biopsies for non-palpable benign lesions.     

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.     

Detection of masses and calcifications by soft-copy reading: comparison of two postprocessing algorithms for full-field digital mammography

Purpose  The purpose of this study was to determine the effects of a commercially available postprocessing algorithm on the detection of masses and microcalcifications of breast cancer by soft-copy reading. Materials and methods  The study included 64 digital mammograms with 16 histologically proven abnormal findings (eight masses and eight microcalcifications) and 48 normal breasts. Two image-processing algorithms were applied to the digital images, which were acquired using General Electric units. The commercially available advanced and standard postprocessed digital mammograms were evaluated in a localization receiver operating characteristic (ROC) curve experiment involving seven mammography radiographers. Results  The mean area under the ROC curve was 0.921 ± 0.022 for the commercially available advanced postprocessed digital mammograms session and 0.904 ± 0.026 for the standard postprocessed digital mammograms session (P = 0.1953). Observer agreement among the readers was better for the advanced postprocessed digital mammograms than for the standard postprocessed digital mammograms. Conclusion  During soft-copy reading, the interpretation accuracy might be influenced by the postprocessing algorithm.