Comparison of the quality of temporal subtraction images obtained with manual and automated methods of digital chest radiography

[Development of temporal subtraction method for chest radiographs by using pixel matching technique]

A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can enhance interval changes on a chest radiograph by removal of most normal structures. However, subtraction artifacts, which tend to reduce its effectiveness in the detection of interval changes, were still included in the conventional method. In this study, we have developed a pixel matching technique to reduce artifacts in the temporal subtraction images. With this technique, the pixel value in a nonlinearly warped previous image is replaced by a pixel value within a kernel, which is closest to the pixel value on a current image. For evaluation of the proposed method, one hundred temporal subtraction images with a simulated nodule were used. When the kernel size of 3×3 was employed in the pixel matching technique, the misregistration artifacts decreased by 72%, and the contrast-to-noise ratio of the simulated lung nodules was increased by 5% in comparison with the conventional method. However, the area of the simulated nodule on the subtraction image decreased by 6%. Our results indicated that the pixel matching technique can enhance simulated nodules, with a substantial reduction of misregistration artifacts in comparison with conventional subtraction images. Therefore, we believe that the temporal subtraction method with the pixel matching technique would assist radiologists' diagnoses for detection of lung nodules in digital chest radiography.

Clinical usefulness of temporal subtraction method in screening digital chest radiography with a mobile computed radiography system

The temporal subtraction image which is obtained by subtraction of a previous image from a current image of the same patient can enhance interval changes. In this study, we applied the temporal subtraction method for lung cancer screening and evaluated the clinical usefulness by comparing the review time and the detection accuracy of lung cancers without and with subtraction images. Since 1996, we have been performing screening chest radiography for a mass survey of lung cancers in the Iwate Prefecture, Japan, by using a van equipped with a computed radiography system and a digital archive system. During the 12 years from 1997 to 2008, a total of 186,340 examinations were performed, and 121,526 (65.2%) temporal subtraction images were provided in the lung cancer screening. Twenty-four abnormal cases with lung cancer and 270 normal cases were selected from the lung cancer screening. Five radiologists participated in an observer performance study and interpreted previous and current chest radiographs without and with temporal subtraction images. In addition, radiologists interpreted previous and current images with a double-reading method. The average ROC curves demonstrated a significant improvement in the detection accuracy of lung cancers with the temporal subtraction images compared with that without the temporal subtraction images, and that with the double-reading method. Therefore, we believe strongly that the temporal subtraction method is clinically useful for radiologists in the detection of lung cancers in mass surveys.

Temporal subtraction chest radiography

Radiologist are commonly required to compare a sequence of two or more chest radiographs of a given patient obtained over a period of time, which may range from a few hours to many years. In such cases, the task is one of detecting interval change. In the case of patients who have had a previous chest radiograph, an opportunity exists to enhance selectively areas of interval change, including regions with new or altered pathology, by using the previous radiographs as a subtraction mask. With temporal subtraction, the previous image is superimposed and registered with the current image, using automated two-dimensional warping to compensate for any differences in positioning. A "difference image" is then created, by subtracting the previous from the current radiograph. In this temporal subtraction image, areas that are unchanged appear as uniform gray, while regions of new opacity, such as due to pneumonia or cancer, appear as prominent dark foci on a lighter background. By cancelling out the complex anatomical background, temporal subtraction can provide dramatically enhanced visibility of new areas of disease.

Development of a voxel-matching technique for substantial reduction of subtraction artifacts in temporal subtraction images obtained from thoracic MDCT

A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes (such as formation of new lesions and changes in existing abnormalities) on medical images by removing most of the normal structures. However, subtraction artifacts are commonly included in temporal subtraction images obtained from thoracic computed tomography and thus tend to reduce its effectiveness in the detection of pulmonary nodules. In this study, we developed a new method for substantially removing the artifacts on temporal subtraction images of lungs obtained from multiple-detector computed tomography (MDCT) by using a voxel-matching technique. Our new method was examined on 20 clinical cases with MDCT images. With this technique, the voxel value in a warped (or nonwarped) previous image is replaced by a voxel value within a kernel, such as a small cube centered at a given location, which would be closest (identical or nearly equal) to the voxel value in the corresponding location in the current image. With the voxel-matching technique, the correspondence not only between the structures but also between the voxel values in the current and the previous images is determined. To evaluate the usefulness of the voxel-matching technique for removal of subtraction artifacts, the magnitude of artifacts remaining in the temporal subtraction images was examined by use of the full width at half maximum and the sum of a histogram of voxel values, which may indicate the average contrast and the total amount, respectively, of subtraction artifacts. With our new method, subtraction artifacts due to normal structures such as blood vessels were substantially removed on temporal subtraction images. This computerized method can enhance lung nodules on chest MDCT images without disturbing misregistration artifacts.

Evaluation of the image quality of temporal subtraction images produced automatically in a PACS environment

The aim of the study is to evaluate the reliable production of temporal subtraction images in a picture archiving and communication system environment and to establish objective criteria for the evaluation of image quality. A total of 117 temporal subtraction chest images (55 in the upright position, 62 in the supine position) were obtained in five consecutive days. In all of these, we confirmed that there were no interval changes on the original images, and cases with diffuse lung disease were excluded. The temporal subtraction images were classified by three chest radiologists into five levels: 5, excellent; 4, good; 3, acceptable; 2, poor; and 1, very poor. The following were examined: (1) the yield of adequate quality of the temporal subtraction images; (2) whether the temporal subtraction images were obtained in the warping or nonwarping mode; and (3) the correlation of the overall subjective image quality with the relative shift angles, relative shift distances, and the standard deviation of gray levels in the temporal subtraction images. The percentages of acceptable temporal subtraction images were 100% and 66% in the upright and supine positions, respectively. Sixteen (26%) of the 62 supine-position images were made in nonwarping mode, whereas all upright images were made in warping mode. Significant correlations were obtained in the relative shift angle (P < 0.05), relative horizontal shift distance (P < 0.05), and standard deviation of gray levels (P < 0.0001). Temporal subtraction images with acceptable image quality were obtained in the upright position. The objective criteria may be useful for the evaluation of image quality.

Integration of temporal subtraction and nodule detection system for digital chest radiographs into picture archiving and communication system (PACS): four-year experience

Since May 2002, temporal subtraction and nodule detection systems for digital chest radiographs have been integrated into our hospital's picture archiving and communication systems (PACS). Image data of digital chest radiographs were stored in PACS with the digital image and communication in medicine (DICOM) protocol. Temporal subtraction and nodule detection images were produced automatically in an exclusive server and delivered with current and previous images to the work stations. The problems that we faced and the solutions that we arrived at were analyzed. We encountered four major problems. The first problem, as a result of the storage of the original images' data with the upside-down, reverse, or lying-down positioning on portable chest radiographs, was solved by postponing the original data storage for 30 min. The second problem, the variable matrix sizes of chest radiographs obtained with flat-panel detectors (FPDs), was solved by improving the computer algorithm to produce consistent temporal subtraction images. The third problem, the production of temporal subtraction images of low quality, could not be solved fundamentally when the original images were obtained with different modalities. The fourth problem, an excessive false-positive rate on the nodule detection system, was solved by adjusting this system to chest radiographs obtained in our hospital. Integration of the temporal subtraction and nodule detection system into our hospital's PACS was customized successfully; this experience may be helpful to other hospitals.

Evaluation of usefulness of color digital summation radiography for solitary pulmonary nodules on chest radiographs

PURPOSE

The aim of this study was to evaluate the usefulness of novel color digital summation radiography (CDSR) for detecting solitary pulmonary nodules on chest radiographs by observers with different levels of experience.

MATERIALS AND METHODS

A total of 30 healthy controls and 30 patients with newly detected solitary pulmonary nodules were evaluated. Six radiologists and five residents evaluated three image sets: set A, current and prior radiographs only; set B, set A with temporal subtraction images; and set C, set A with CDSR. The observers were asked to rate each image set using a continuous rating scale. In addition, the reading time required for each set was recorded.

RESULTS

The radiologists showed no significant differences in the mean A(z) value between set A, set B, and set C. However, the residents showed significant differences between set A and set B and between set A and set C. In addition, for set B and set C, the mean reading time per case of all readers was significantly shorter than that for set A.

CONCLUSION

The detection capability of observers with little experience is comparable to that of experienced observers when reading radiographs with temporal subtraction images or with CDSR. The usefulness of CDSR is comparable to that of temporal subtraction.

Temporal subtraction of dual-energy chest radiographs

Temporal subtraction and dual-energy imaging are two enhanced radiography techniques that are receiving increased attention in chest radiography. Temporal subtraction is an image processing technique that facilitates the visualization of pathologic change across serial chest radiographic images acquired from the same patient; dual-energy imaging exploits the differential relative attenuation of x-ray photons exhibited by soft-tissue and bony structures at different x-ray energies to generate a pair of images that accentuate those structures. Although temporal subtraction images provide a powerful mechanism for enhancing visualization of subtle change, misregistration artifacts in these images can mimic or obscure abnormalities. The purpose of this study was to evaluate whether dual-energy imaging could improve the quality of temporal subtraction images. Temporal subtraction images were generated from 100 pairs of temporally sequential standard radiographic chest images and from the corresponding 100 pairs of dual-energy, soft-tissue radiographic images. The registration accuracy demonstrated in the resulting temporal subtraction images was evaluated subjectively by two radiologists. The registration accuracy of the soft-tissue-based temporal subtraction images was rated superior to that of the conventional temporal subtraction images. Registration accuracy also was evaluated objectively through an automated method, which achieved an area-under-the-ROC-curve value of 0.92 in the distinction between temporal subtraction images that demonstrated clinically acceptable and clinically unacceptable registration accuracy. By combining dual-energy soft-tissue images with temporal subtraction, misregistration artifacts can be reduced and superior image quality can be obtained.

Evaluation of the usefulness of color digital summation radiography in temporally sequential digital radiographs: a phantom study

PURPOSE

The purpose of this study was to assess the usefulness of color digital summation radiography (CDSR) for detection of nodules on chest radiographs by observers with different levels of experience.

MATERIALS AND METHODS

A total of 30 radiographs of chest phantoms with abnormalities and 30 normal ones were arranged at random. Set A was conventional radiographs only. Set B consisted of both conventional radiographs and CDSR images, which were colored with magenta. Five chest radiologists and five residents evaluated both image sets on a TFT monitor. The observers were asked to rate each image set using a continuous rating scale. The reading time for each set was also recorded.

RESULTS

In set A, the performance of chest radiologists was significantly superior to that of the residents (P < 0.05). However, in set B, there was no significant difference in the performance of the chest radiologists and the residents. In both observer groups, the mean reading time per case in set B was significantly shorter than that in set A (P < 0.01).

CONCLUSION

By using CDSR, the detection capability of observers with little experience improves and is comparable to that of experienced observers. Moreover, the reading time becomes much shorter using CDSR.

Novel display technique for reference images for visibility of temporal change on radiographs--color digital summation radiography

PURPOSE

The present study investigated color digital summation radiography (CDSR) as a novel display technique for reference images for the visibility of temporal change on radiographs. In CDSR, only the parts with temporal differences are displayed in color. Moreover, all other parts are displayed in gray scale.

MATERIALS AND METHODS

CDSR was defined as "radiographs combined by the additive color mixture method". The visibility of simulated nodules located in the lung fields and mediastinum was evaluated by 12 radiologists (mean experience, 9.8 years; range, 1-26 years) for 24 conventional radiographs and CDSR for 6 color patterns. A five-point rating system (5, very good; 4, good; 3, adequate; 2, poor; 1, very poor) was used.

RESULTS

The mean scores (average +/- standard deviation) for the visibility of simulated nodules were as follows: magenta, 3.88 +/- 0.90; blue, 3.08 +/- 0.72; green, 3.04 +/- 0.86; red, 3.00 +/- 0.98; cyan, 2.71 +/- 0.86; and yellow, 2.50 +/- 0.72. Compared to conventional radiography in gray scale, at 1.21 +/- 0.41, all six color patterns for CDSR displayed significantly improved scores (p<0.001).

CONCLUSION

CDSR might represent a useful technique for reference images from chest digital radiography.

Temporal subtraction in chest radiography: Automated assessment of registration accuracy

Radiologists routinely compare multiple chest radiographs acquired from the same patient over time to more completely understand changes in anatomy and pathology. While such comparisons are achieved conventionally through a side-by-side display of images, image registration techniques have been developed to combine information from two separate radiographic images through construction of a "temporal subtraction image." Although temporal subtraction images provide a powerful mechanism for the enhanced visualization of subtle change, errors in the clinical evaluation of these images may arise from misregistration artifacts that can mimic or obscure pathologic change. We have developed a computerized method for the automated assessment of registration accuracy as demonstrated in temporal subtraction images created from radiographic chest image pairs. The registration accuracy of 150 temporal subtraction images constructed from the computed radiography images of 72 patients was rated manually using a five-point scale ranging from "5-excellent" to "1-poor;" ratings of 3, 4, or 5 reflected clinically acceptable subtraction images, and ratings of 1 or 2 reflected clinically unacceptable images. Gray-level histogram-based features and texture measures are computed at multiple spatial scales within a "lung mask" region that encompasses both lungs in the temporal subtraction images. A subset of these features is merged through a linear discriminant classifier. With a leave-one-out-by-patient training/testing paradigm, the automated method attained an A(z) value of 0.92 in distinguishing between temporal subtraction images that demonstrated clinically acceptable and clinically unacceptable registration accuracy. A second linear discriminant classifier yielded an A(z) value of 0.82 based on a feature subset selected from an independent database of digitized film images. These methods are expected to advance the clinical utility of temporal subtraction images for chest radiography.

[Research on time-course differential imaging by bone scintigraphy]

The temporal image subtraction technique was applied to bone scintigraphy, using Photoshop (commercially available image processing software) and Morpher (public domain warping software). For the temporal subtraction images, 81 subtraction images (19 cases) were prepared by a method used to subtract the previous images from the current ones. Registration of the current and previous images was performed by manual operation using Photoshop, and warping was done using the warping function of Morpher. In addition, difference images prepared after correcting the distributions of radioactive isotopes of the current and previous images using the count of the pelvic region were also examined. Compared with manual operation, alignment of images by warping improved registration and reduced the generation of pseudo-images of subtraction images. The rate of identification of abnormal accumulation-enhanced regions and subjective evaluation by doctors was improved for warping more than for manual operation. Furthermore, abnormal hot regions, which are difficult to find in film images, could be found in three subtraction images. In addition, it was confirmed that abnormal hot regions become more visible in many cases by preparing subtraction images after correcting the count between images using the count of the pelvic region. Thus, it is suggested that the temporal image subtraction technique in bone scintigraphy enables more accurate observation of enhancement of or changes in abnormal hot regions, which will support diagnostic reading. It is considered that enhancement of or changes in abnormal hot regions will be more accurately understood through further detailed discussion in the future.

Temporal subtraction for detection of solitary pulmonary nodules on chest radiographs: evaluation of a commercially available computer-aided diagnosis system

PURPOSE

To evaluate the usefulness of a commercially available computer-aided diagnosis (CAD) system that incorporates temporal subtraction for the detection of solitary pulmonary nodules on chest radiographs by readers with different levels of experience.

MATERIALS AND METHODS

Sixty pairs of chest radiographs in 30 patients with newly detected solitary pulmonary nodules and 30 normal cases, all confirmed with serial chest computed tomography (CT), were obtained from screen-film or digital radiographic systems and were digitized (spatial resolution, 0.171 mm/pixel). Temporal subtraction images were produced with an iterative image-warping technique. Five chest radiologists and five residents evaluated both image sets for solitary nodules: set A, current and prior radiographs with temporal subtraction images, and set B, current and prior radiographs only. Assessment was performed with receiver operating characteristic (ROC) analysis of the images on a monitor (pixel size, 1,280 x 1,024) equipped with the system. The reading time needed by each reader was recorded in each case.

RESULTS

For the chest radiologists, no statistically significant difference was found between set A (area under the ROC curve [A(z)] = 0.934) and set B (A(z) = 0.964). For the residents, however, observer performance in set A (A(z) = 0.907) was superior to that in set B (A(z) = 0.855) (P <.05). For both groups, the mean reading time per case for set A (chest radiologists, 16.7 seconds; residents, 15.7 seconds) was significantly (P <.05) shorter than that for set B (chest radiologists, 20.4 seconds; residents, 26.2 seconds).

CONCLUSION

For the detection of solitary pulmonary nodules, the CAD system with temporal subtraction can promote efficiency for established chest radiologists and improvement in accuracy for less experienced readers.

Computer-aided diagnosis in chest radiography: a survey

The traditional chest radiograph is still ubiquitous in clinical practice, and will likely remain so for quite some time. Yet, its interpretation is notoriously difficult. This explains the continued interest in computer-aided diagnosis for chest radiography. The purpose of this survey is to categorize and briefly review the literature on computer analysis of chest images, which comprises over 150 papers published in the last 30 years. Remaining challenges are indicated and some directions for future research are given.