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

Radiation Dose Reduction in Digital Mammography by Deep-Learning Algorithm Image Reconstruction: A Preliminary Study

Purpose

To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging.

Materials and Methods

A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order.

Results

Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences.

Conclusion

Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

Effect of image quality on calcification detection in digital mammography

PURPOSE

This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection.

METHODS

One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into half of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data.

RESULTS

There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from 0.84 to 0.63 and the ROC area decreased from 0.91 to 0.79 (p < 0.0001). This corresponded to a 30% drop in lesion sensitivity at a NLF equal to 0.1. Detection was also sensitive to the dose used. There was no significant difference in detection between the two image processing algorithms used (p > 0.05). It was additionally found that lower threshold gold thickness from CDMAM analysis implied better cluster detection. The measured threshold gold thickness passed the acceptable limit set in the EU standards for all image qualities except half dose CR. However, calcification detection varied significantly between image qualities. This suggests that the current EU guidelines may need revising.

CONCLUSIONS

Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection.

Effect of greyscale liquid crystal displays of different resolutions on observer performance during detection of small solitary pulmonary nodules

OBJECTIVE

The aim of this study was to evaluate the effect of monochrome liquid crystal displays (LCDs) with different resolutions on observer performance during detection of small solitary pulmonary nodules.

METHODS

Chest images of digital radiography were selected online from the hospital's picture archiving and communication system. Of the 164 images selected, small solitary non-calcified pulmonary nodules were present in 63 images and absent in 101 images. Observer performance was assessed among 3 extremely experienced, 3 very experienced and 3 moderately experienced radiologists, who independently interpreted these images on 2, 3 and 5 megapixel greyscale LCDs. A five-point confidence level rating scale was used to represent the presence of nodules: definite absence, probable absence, indetermination, probable presence and definite presence. The observers were requested to rank each image on the given display according to the presence of the pulmonary nodule. Observer performance was analysed in terms of receiver operating characteristics (ROCs).

RESULTS

The areas under the ROC curves which represented the observer performance for the 2, 3 and 5 megapixel LCDs were found to be 0.705, 0.722 and 0.764, respectively, for the extremely experienced radiologists; 0.687, 0.712 and 0.721, respectively, for the very experienced radiologists; and 0.689, 0.696 and 0.711, respectively, for the moderately experienced radiologists. These differences were not statistically significant.

CONCLUSION

The observer performances for detection of small solitary non-calcified pulmonary nodules by radiologists with varying degrees of experience were comparable between the 2, 3 and 5 megapixel monochrome LCDs.

The basics and implementation of digital mammography

Current day digital mammography acquisition units have already been shown to be equal or better than screen film systems for the detection and classification of breast lesions. The optimal multimodality breast imaging diagnostic workstations and connectivity to existing picture and archiving communication systems and information systems is still a work in progress, but with more and more facilities transitioning to digital imaging it is only a matter of time until these hurdles are overcome.