Temporal subtraction for the detection of hazy pulmonary opacities on chest radiography

OBJECTIVE: The purpose of this study was to evaluate the accuracy of temporal subtraction with a commercially available computer-assisted diagnosis system for the detection of multifocal hazy pulmonary opacities on chest radiographs, which are sometimes difficult to detect directly on chest radiographs. MATERIALS AND METHODS: Thirty healthy patients and 30 patients with new multifocal hazy pulmonary opacities that were confirmed by serial chest CT examinations were evaluated with and without temporal subtraction images. Chest radiographs were taken from either film-screen or digital radiography images and were digitized with a spatial resolution of 0.171 mm per pixel. Temporal subtraction images were produced by an iterative image-warping technique. We designed an observer performance study in which observers (six chest radiologists and four residents) indicated their confidence level for the presence or absence of hazy pulmonary opacities on two sets of images, current and previous radiographs only (set A), and current and previous radiographs with temporal subtraction images (set B). Receiver operating characteristic curves were generated. RESULTS: For chest radiologists, observer performance with set B (with temporal subtraction images; A(z) = 0.947) was superior to that with set A (without temporal subtraction images; A(z) = 0.916) (p < 0.05). For residents, no statistically significant difference was found between sets A and B. CONCLUSION: The temporal subtraction technique clearly improves diagnostic accuracy for the detection of multifocal hazy pulmonary opacities on chest radiographs, especially when the observers are experienced chest radiologists who have sufficient skill to evaluate the patient's condition as revealed on the images.     

ROC analysis of detection of interval changes in interstitial lung diseases on digital chest radiographs using the temporal subtraction technique

PURPOSE: To demonstrate the clinical usefulness of a temporal subtraction technique for the detection of interval changes in various interstitial lung diseases on digital chest radiographs. MATERIALS AND METHODS: One hundred pairs of chest radiographs in 34 patients (63 with and 37 without interval changes) with various interstitial lung diseases were selected. All cases were confirmed by serial chest computed tomography (CT) and ascertained by radiologists. All chest radiographs were obtained with a computed radiography (CR) system, and temporal subtraction images were produced with an iterative image-warping technique. Four radiologists and two thoracic physicians provided confidence levels for interval changes in interstitial lung diseases with and without temporal subtraction. Their performances with and without temporal subtraction were evaluated by means of receiver operating characteristic (ROC) analysis using a sequential test. RESULTS: The area under the ROC curve (Az) values of six observers obtained with and without temporal subtraction were 0.90 and 0.78, respectively. Results showed that the detection of interval changes in interstitial lung diseases was significantly improved by the use of temporal subtraction images compared with CR images alone(P = 0.002). Furthermore, the high detection rate was achieved with temporal subtraction images regardless of the subtlety and location of interval changes. CONCLUSION: Temporal subtraction improved the diagnostic accuracy of radiologists in detecting interval changes in interstitial lung diseases on chest radiographs. It was also useful for cases of multiple interval changes.     

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.     

Effect of temporal subtraction technique on the diagnosis of primary lung cancer with chest radiography

PURPOSE: The purpose of this study was to assess the diagnostic accuracy of the temporal subtraction technique in the detection of primary lung cancers by readers with different levels of experience. METHODS: Previous and current chest radiographs from 40 patients with histologically proven lung cancer and 40 controls were studied. Temporal subtraction images were produced using an automated digital subtraction technique. We evaluated the effect of temporal subtraction images in the diagnosis of lung cancer with chest radiographs via an observer performance study with the use of receiver operating characteristic analysis. Six experienced radiologists and six residents participated as observers. RESULTS: Observer performance for all observers was superior when temporal subtraction images were used (mean Az value increased from 0.764 to 0.836, p=0.0006). Although the average Az value for residents increased significantly, from 0.707 to 0.795 (p=0.0038), the average Az value for experienced radiologists increased only from 0.821 to 0.878 (n.s.). CONCLUSION: In conclusion, the temporal subtraction technique clearly improves diagnostic accuracy for the detection of primary lung cancer. The results indicated that the use of temporal subtraction images was more beneficial for the residents than for the experienced radiologists. This method would compensate to some extent for experience-dependent diagnostic accuracy in the detection of lung cancer.     

Detection of lung nodules on digital chest radiographs: potential usefulness of a new contralateral subtraction technique

PURPOSE: To evaluate the potential usefulness of a contralateral subtraction technique developed for radiologists' performance in the detection of subtle lung nodules on chest radiographs. MATERIALS AND METHODS: Fifty chest radiographs (25 normal and 25 abnormal with a subtle lung nodule) that were digitized with a 0.175-mm pixel size and 4,096 gray levels were used. Twelve radiologists (10 attending and two residents) participated in observer tests and read both original and contralateral subtraction images with a sequential testing method. Radiologists' performance was evaluated by means of receiver operating characteristic analysis with use of a continuous rating scale. The beneficial and detrimental effects of the contralateral subtraction technique on the radiologists' performance were also evaluated. RESULTS: The area under the receiver operating characteristic curve values obtained without and with contralateral subtraction images were 0.926 and 0.962, respectively. Results indicated that the contralateral subtraction images significantly (P <.05) improved diagnostic accuracy, particularly for radiologists with limited experience. CONCLUSION: The contralateral subtraction technique can assist radiologists in the correct identification of subtle lung nodules on chest radiographs.     

Detectability of lung nodules using flat panel detector with dual energy subtraction by two shot method: evaluation by ROC method

The aim of this study was to evaluate the effectiveness of dual-exposure dual energy subtraction technique in flat-panel chest radiography for lung nodules detection. Chest radiographs were acquired in 100 patients (57 men and 43 women; mean age, 60.2 years; range, 18-89 years) using a flat-panel digital chest system. These images were evaluated by seven radiologists. A continuous rating scale of 0-100 was used to represent each observer's confidence level regarding the presence or absence of lung nodules. Observer performance for detection of lung nodules with subtraction images was tested by using receiver operating characteristic (ROC) analysis of individual and averaged reader data. The average area under the ROC curve (Az value) significantly increased with subtraction images (Az=0.79 in standard radiographs versus Az=0.84 with subtraction images, p<0.05). In conclusion, the two-exposure dual-energy subtraction chest radiography significantly would improve detection of lung nodules.     

ROC Analysis of Detection of Metastatic Pulmonary Nodules on Digital Chest Radiographs with Temporal Subtraction

RATIONALE AND OBJECTIVES: The authors' purpose was to evaluate the effect of temporal subtraction on digital chest radiographs in the detection of metastatic pulmonary nodules. MATERIALS AND METHODS: The study included 21 cases with metastatic pulmonary nodule and 21 cases without metastatic nodule. Eleven radiologists, including eight residents and three certified radiologists, provided their confidence levels for the presence or absence of pulmonary nodules without and with temporal subtraction. Their performances without and with temporal subtraction were evaluated by means of receiver operating characteristic analysis with both independent and sequential tests. RESULTS: For the independent test, the radiologists' Az (area under the receiver operating characteristic curve) values were 0.871 without and 0.954 with temporal subtraction, compared with 0.882 and 0.955, respectively, for the sequential test. Diagnosis accuracy was significantly improved with the use of temporal subtraction. There was no significant difference in Az values between the independent and sequential tests. CONCLUSION: Temporal subtraction is useful in the detection of metastatic pulmonary nodules, and this technique augments the value of digital chest radiography.     

Computer-aided diagnosis in the detection of temporal changes in sequential chest radiographs

To aid radiologists in the diagnosis of screening chest radiographs, a temporal subtraction technique using digital image processing was developed. The accurate image registration of two sequential images enables us to detect even subtle changes in the "difference image" between them. In this report, a new method based on matching "lung markings" is introduced. Twenty-nine pairs of sequential posteroanterior chest radiographs with and without temporal changes were selected from cases examined with the computed radiography system. Image registration was employed, with the local matching of "lung markings" in previous and current radiographs. Observer performance tests were carried out by eight radiologists, with and without the "difference image." Observer performance tests with the temporal subtraction image showed that six of eight observers diagnosed them with higher sensitivity (mean, 43.9% vs. 55.3%) and a comparable false positive response. Mean area under the AFROC (alternative free-response receiver operating characteristics) curve also improved from 0.596 to 0.647, a statistically significant difference. The subtraction image using this registration technique improved diagnostic accuracy for subtle temporal changes.     

Usefulness of temporal subtraction images of chest computed radiography for detection of metastatic pulmonary nodules

Temporal subtraction is a technique by which a previous chest radiograph is subtracted from a current radiograph in order to enhance interval changes. Our purpose in this study was to evaluate the usefulness of temporal subtraction for the detection of metastatic pulmonary nodules. We examined 19 cases of metastatic nodules less than 15 mm in diameter (8.4 mm on average). Temporal subtraction images were created based on the matching of local lung areas in pairs of chest radiographs. By using the subtraction images, the detectability of nodules was clearly improved in 5 cases and moderately improved in 8 cases; there was no improvement in 6 cases. The subtraction images were especially useful for nodules superimposed over normal structures, such as rib, mediastinum, and diaphragm, as well as for small nodules. In 6 of the 19 cases, the nodules had been missed clinically; however, the temporal subtraction images clearly demonstrated half of missed small nodules. Temporal subtraction made it possible to enhance subtle interval changes and helped in detecting small pulmonary metastases. This technique seems promising for augmenting the capabilities of computed radiography of the chest.     

Improved detection of lung cancer arising in diffuse lung diseases on chest radiographs using temporal subtraction

RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate the usefulness of temporal subtraction for the detection of lung cancer arising in pneumoconiosis, idiopathic pulmonary fibrosis, and pulmonary emphysema. MATERIALS AND METHODS: Fifteen cases of lung cancer arising in diffuse lung diseases, including three cases of pneumoconiosis, six of idiopathic pulmonary fibrosis, and six of pulmonary emphysema, were evaluated. Pathologic proof was obtained by surgery or transbronchial lung biopsy. The average interval between previous and current radiographs was 356 days (range, 31-947 days). All chest radiographs were obtained with a computed radiography system, and temporal subtraction images were produced by subtracting of a previous image from a current one with a nonlinear image-warping technique. The effect of the temporal subtraction image was evaluated by observer performance study with receiver operating characteristic analysis. RESULTS: The average observer performance with temporal subtraction was significantly improved (Az = 0.935) compared with that without temporal subtraction (Az = 0.857, P < .0001). CONCLUSION: The temporal subtraction technique is useful for the detection of lung cancer arising in pneumoconiosis, idiopathic pulmonary fibrosis, and pulmonary emphysema.     

Usefulness of computerized method for lung nodule detection on digital chest radiographs using similar subtraction images from different patients

Purpose

The purpose of this study is to evaluate the usefulness of a novel computerized method to select automatically the similar chest radiograph for image subtraction in the patients who have no previous chest radiographs and to assist the radiologists’ interpretation by presenting the “similar subtraction image” from different patients.

Materials and methods

Institutional review board approval was obtained, and the requirement for informed patient consent was waived. A large database of approximately 15,000 normal chest radiographs was used for searching similar images of different patients. One hundred images of candidates were selected according to two clinical parameters and similarity of the lung field in the target image. We used the correlation value of chest region in the 100 images for searching the most similar image. The similar subtraction images were obtained by subtracting the similar image selected from the target image. Thirty cases with lung nodules and 30 cases without lung nodules were used for an observer performance test. Four attending radiologists and four radiology residents participated in this observer performance test.

Results

The AUC for all radiologists increased significantly from 0.925 to 0.974 with the CAD (P = .004). When the computer output images were available, the average AUC for the residents was more improved (0.960 vs. 0.890) than for the attending radiologists (0.987 vs. 0.960).

Conclusion

The novel computerized method for lung nodule detection using similar subtraction images from different patients would be useful to detect lung nodules on digital chest radiographs, especially for less experienced readers.     

数字化双能量减影胸部摄片的临床应用价值

目的 :评价双能量减影胸部摄片的临床应用价值 ,探讨影响图像质量的因素。方法 :选择双能减影检查病人 15 0例 ,其中男 78例 ,女 72例 ,年龄 4～ 88岁 ,平均 4 7岁。使用美国GERevolutionXQ/d全数字摄影系统 ,自动曝光条件下采集数字平片、软组织像及骨组织像。由三名医师对图像进行综合分析 ,统计分析采用卡方检验。结果 :15 0例胸片中有阳性征象者 86例 ,其中钙化 2 9例 ,肺内结节性病变 4 5例 ,肋骨骨折 3例 ,骨病 4例 ,胸部其它病变 5例。胸部钙化检出情况 :数字平片检出 5例 ,骨组织像检出 2 9例 ,其中两者共同检出 5例。两者对胸部钙化的检出率有显著差异 (P <0 .0 1)。对肺内结节的检出情况 :数字平片检出 35例 ,软组织像检出 4 5例 ,两者共同检出 35例 ,两者对肺内结节的检出率经统计学处理无显著差异 (P >0 .0 5 )。左下肺心室搏动伪影、双下肺呼吸运动伪影是软组织像上常见的伪影表现 ,曝光时身体移动是双能减影失败的常见原因。结论 :双能减影可增加诊断的信息量 ,增加胸部钙化的检出率 ,有助于肺内结节性病变细节的观察 ;有利于对肺野边缘、骨性胸廓及大气管影像解剖结构和病变的观察 ;心室搏动、曝光时呼吸及身体移动是影响双能减影成像质量的主要因素。     

Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs

PURPOSE: To assess the relative influence of quantum mottle and structured lung patterns (anatomic noise) on the detection of subtle lung nodules on chest radiographs. MATERIALS AND METHODS: Sixty 8 x 8-cm lung pattern images were extracted from digital chest radiographs in healthy individuals. Sixty quantum mottle images of the same size and quantum noise level were extracted from uniformly exposed digital radiographs. Simulated nodules with various peak contrast-diameter products (CD) that emulated subtle tissue-equivalent lung nodules were numerically superimposed at the center on three-fourths of the images. Printouts were independently viewed and scored by five experienced radiologists. The area under the receiver operating characteristic curve (Az) was estimated as a measure of the detectability of the nodules. RESULTS: At a fixed observer performance level (e.g., Az = 0.8), much smaller and lower-contrast nodules were detected on quantum mottle images (1-mm diameter, CD = 0.01 mm), compared with those on anatomic images (4.5-mm diameter, CD = 0.20 mm). The findings generally agreed with the signal-to-noise ratio calculations based on statistical observer models. CONCLUSION: The detection of subtle lung nodules on chest radiographs is limited by anatomic noise.     

深度卷积网络骨抑制技术对孤立性肺结节诊断效能的研究

目的评估新型骨抑制技术—深度卷积网络骨抑制成像(deep bone suppression imaging,deepBSI)对孤立性肺结节(solitary pulmonary nodule,SPN)的诊断效能,并与数字化X线片(digital radiograph,DR)、双能量减影技术(dual energy substraction,DES)进行对比分析。方法收集我院2016年12月~2017年9月拍摄标准胸部正位片247例(114例诊断SPN,133例无结节)。3位低年资及3位高年资医师按DR图像→DR+deepBSI图像→DR+DES图像的阅片顺序,分别在三组图像上标出结节可能位置并评分,进行Z检验,应用ROC曲线分析三种检查方法对SPN的诊断效能。结果6位医师,DR、deepBSI、DES三种检查方法诊断SPN的ROC曲线下面积分别约0.715、0.804、0.800,deepBSI、DES诊断效能均优于DR(P<0.05)。当结节与肋骨重叠面积>50%时,deepBSI、DES二种方法相比于DR诊断SPN的诊断效能越好。结论deepBSI、DES诊断效能均优于DR,有助于肺结节的检出,与肋骨重叠面积大的结节优势更显著,deepBSI、DES诊断敏感性及特异性始终相似。     

Development of an image processing scheme for chest radiographs using a dot printer

The performance of dot printers has recently been improved. Images output by dot printers can provide simple, economical medical reference images if important diagnostic information is not lost. We developed an image processing scheme for chest radiographs that employed a dot printer. We used two types of pixel value conversions, a nonlinear pixel value correction using a lookup table and a linear pixel value conversion using histogram analysis. The density distribution of chest radiographs was analyzed and classified into high-density and low-density images. The two types of pixel value conversions were used depending on the density of chest radiographs. Converted pixel value had density characteristics that were adapted to the output image of the dot printer, and thus the density distributions of the lungs of radiographs became comparable. In addition, an adaptive unsharp masking technique with processing parameters optimized for each of the lungs and mediastinum was applied. An ROC study for the detection of lung nodules was carried out to evaluate the performance of dot printer images. The area under the ROC curve (A(z)) for dot printer images was 0.816, while sensitivity and specificity were 77.6% and 75.2%, respectively. The performance indicated the usefulness of our image processing scheme.     

双能量减影数字X线摄影技术的应用

目的:用双能量减影数字X线摄影提高肺部小结节病变的检出率。方法:双能量减影摄影可以用两次曝光法和一次曝光法来完成。结果:双能量减影数字化胸部摄影技术作为胸部X线检查的一种辅助手段,它能有效的提高肺部小结节病变的检出率,并能增加鉴别诊断的依据。结论:直接数字化X线摄影(DR)的使用,使两次曝光法得以实行。由于两次曝光法能量差大,它产生的双能量减影图像上组织对比良好,图像信噪比高,比一次曝光法具有更明显的优势。     

Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system

OBJECTIVE: The aim of this study was to evaluate the usefulness of a new commercially available computer-aided diagnosis (CAD) system with an automated method of detecting nodules due to lung cancers on chest radiograph. MATERIALS AND METHODS: For patients with cancer, 45 cases with solitary lung nodules up to 25 mm in diameter (nodule size range, 8-25 mm in diameter; mean, 18 mm; median, 20 mm) were used. For healthy patients, 45 cases were selected on the basis of confirmation on chest CT. All chest radiographs were obtained with a computed radiography system. The CAD output images were produced with a newly developed CAD system, which consisted of an image server including CAD software called EpiSight/XR. Eight radiologists (four board-certified radiologists and four radiology residents) participated in observer performance studies and interpreted both the original radiographs and CAD output images using a sequential testing method. The observers' performance was evaluated with receiver operating characteristic analysis. RESULTS: The average area under the curve value increased significantly from 0.924 without to 0.986 with CAD output images. Individually, the use of CAD output images was more beneficial to radiology residents than to board-certified radiologists. CONCLUSION: This CAD system for digital chest radiographs can assist radiologists and has the potential to improve the detection of lung nodules due to lung cancer.     

Effect of high sensitivity in a computerized scheme for detecting extremely subtle solitary pulmonary nodules in chest radiographs: observer performance study

RATIONALES AND OBJECTIVES: This study investigated the effect of a high sensitivity in computer-aided diagnosis (CAD) for detecting lung nodules in chest radiographs when extremely subtle cases were presented to radiologists. MATERIAL AND METHODS: The chest radiographs used in this study consisted of 36 normal images and 54 abnormals containing solitary lung nodules, of which 25 were extremely subtle and 29 were very subtle. Receiver operating characteristic analysis for detecting lung nodules was performed without and with CAD. The levels of CAD output were simulated with a hypothetical ideal performance of 100% sensitivity, but with three or four false positives per image. Six radiologists participated in an observer study in which cases were interpreted first without and then with the use of CAD. RESULTS: The average A(z) values for radiologists without and with CAD were 0.682 and 0.808, respectively. The performance of radiologists was improved significantly when high sensitivity was used (P = .0003). However, the radiologists were not able to recognize some extremely subtle nodules (5 of 54 nodules by all radiologists), even with the correct CAD output; these nodules were then considered as non-actionable. None of 306 computer-false positives was incorrectly regarded as a nodule by all radiologists, but 63 false positives were incorrectly identified by one or more radiologists. CONCLUSION: The accuracy of radiologists in the detection of some extremely subtle solitary pulmonary nodules can be improved significantly when the sensitivity of a CAD scheme can be made to be at an extremely high level. However, all of the six radiologists failed to identify some nodules (about 10%), even with the correct output of the CAD.     

Effect of temporal subtraction images on radiologists' detection of lung cancer on CT: results of the observer performance study with use of film computed tomography images

RATIONALE AND OBJECTIVES: To evaluate the effect of temporal subtraction images on the radiologists' detection of early primary lung cancer in computed tomography (CT) scans. MATERIALS AND METHODS: Fourteen cases with primary lung cancer and 16 normal cases were used for this study from a database of low-dose CT images, which were obtained from a lung cancer screening program in Nagano, Japan. Images were obtained with a single-detector helical CT scanner using 10 mm collimation and 2:1 pitch. Each case had both previous and current CT scans. Temporal subtraction images were obtained by subtracting the warped previous images from the current images. Seven radiologists, including four attendings and three residents, provided their confidence levels for the presence or absence of lung cancers with use of film CT images without and with temporal subtraction images. Receiver operating characteristic analysis was used to compare their performance without and with temporal subtraction images. RESULTS: The mean Az values (area under the receiver operating characteristic curve) of seven observers without and with temporal subtraction images were 0.868 and 0.930, respectively. Diagnostic accuracy was significantly improved by using temporal subtraction images (P = .007). Temporal subtraction images were especially useful when a nodule was present near the pulmonary hilum, where radiologists tended to overlook it. CONCLUSION: The temporal subtraction technique can significantly improve the sensitivity and specificity for detection of lung cancer on CT scans.     

Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance

RATIONALE AND OBJECTIVES: The aim of the study is to investigate the effect of a computer-aided diagnostic (CAD) scheme on radiologist performance in the detection of lung cancers on chest radiographs. MATERIALS AND METHODS: We combined two independent CAD schemes for the detection and classification of lung nodules into one new CAD scheme by use of a database of 150 chest images, including 108 cases with solitary pulmonary nodules and 42 cases without nodules. For the observer study, we selected 48 chest images, including 24 lung cancers, 12 benign nodules, and 12 cases without nodules, from the database to investigate radiologist performance in the detection of lung cancers. Nine radiologists participated in a receiver operating characteristic (ROC) study in which cases were interpreted first without and then with computer output, which indicated locations of possible lung nodules, together with a five-color scale illustrating the computer-estimated likelihood of malignancy of the detected nodules. RESULTS: Performance of the CAD scheme indicated that sensitivity in detecting lung nodules was 80.6%, with 1.2 false-positive results per image, and sensitivity and specificity for classification of nodules by use of the same database for training and testing the CAD scheme were 87.7% and 66.7%, respectively. Average area under the ROC curve value for detection of lung cancers improved significantly (P = .008) from without (0.724) to with CAD (0.778). CONCLUSION: This type of CAD scheme, which includes two functions, namely detection and classification, can improve radiologist accuracy in the diagnosis of lung cancer.