Subtle lung nodules: influence of local anatomic variations on detection

PURPOSE: To assess the influence of local anatomic noise on the detection of subtle lung nodules depicted on chest radiographs. MATERIALS AND METHODS: Six 8 x 8-cm lung regions were extracted from digital chest radiographs obtained in healthy subjects. Simulated nodules emulating the radiographic characteristics of subtle tissue-equivalent lesions 3.2-6.4 mm in diameter (equivalent to 0.1-0.4 mm in contrast-diameter product [CD]) were added to the images. On multiple renditions of each image, nodules were inserted at slightly different locations within 6 mm of the center; this process allowed different local background patterns to overlie the nodules. An observer detection study involving 15 experienced radiologists was performed. The authors performed analysis of variance and pairwise t test analyses to determine variations in nodule detectability related to nodule location and size on each image. RESULTS: Results indicated a strong correlation between nodule size and observer detection score and significant variation in nodule detectability as a function of location. Changes in nodule position caused observer score variations that were equivalent to the variation caused by an up to 185% change in nodule CD (78% average over all six images), an up to 68% change in diameter (32% average), and an up to 28% change in area under the receiver operating characteristic curve (Az) (14% average). CONCLUSION: Local anatomic variations surrounding and overlying a subtle lung nodule on a chest radiograph that are created by the projection of anatomic features in the thorax, such as ribs and pulmonary vessels, can greatly influence the detection of nodules, altering the Az by as much as 28%.     

Time-dependent observer errors in pulmonary nodule detection

The work was carried out to investigate differences in visual search characteristics between groups of observers with different levels of experience in the task of pulmonary nodule detection in chest radiology and we report here on these differences in respect of time related decisions. Volunteer observers were divided into three groups depending on their level of expertise. There were eight radiologists, eight radiographers and eight novices. Their task was to detect pulmonary nodules in a test bank of 120 digitized posteroanterior (PA) chest radiographs. Five of the eight radiographers were tested twice: once before and once after a 6-month training programme in interpretation of the adult chest radiograph. During each test session the observers' eye movements were tracked. Data on the observers' decisions through Alternate Free Response Operating Characteristic (AFROC) methodology were correlated to their eye-movement and fixation patterns. True negative decisions from all observers were associated with shorter fixation times than false negative decisions. No correct negative decisions were made after fixations exceeding 3 s.     

Search and nonsearch protocols for radiographic consultation

Six radiologists, acting as radiograph reviewers, used two different consultation protocols to differentiate among 292 ambiguous chest radiographic findings: 120 simulated nodules and 172 normal findings (previous readers' false-positive reports of nodules). The nonsearch protocol identified each finding (by film location), and reviewers rated the likelihood of each finding's being a pulmonary nodule. The search protocol asked reviewers to report and rate all locations regarded as possible nodules on each radiograph and assigned a default negative rating to any unreported finding (nodule or normal structure). Receiver operating characteristic analyses demonstrated a significantly higher accuracy for each reviewer's search-protocol discriminations between these nodules and ambiguous normal findings. This superiority-of-search result suggests that radiologists' second opinions about suspected lesions might be more accurate when consultants follow a search protocol, independently reviewing radiographs without prior knowledge of the specific findings that concerned the primary radiograph readers.     

Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists' detection of pulmonary nodules

OBJECTIVE: We developed a digital image database (www.macnet.or.jp/jsrt2/cdrom_nodules.html ) of 247 chest radiographs with and without a lung nodule. The aim of this study was to investigate the characteristics of image databases for potential use in various digital image research projects. Radiologists' detection of solitary pulmonary nodules included in the database was evaluated using a receiver operating characteristic (ROC) analysis. MATERIALS AND METHODS: One hundred and fifty-four conventional chest radiographs with a lung nodule and 93 radiographs without a nodule were selected from 14 medical centers and were digitized by a laser digitizer with a 2048 x 2048 matrix size (0.175-mm pixels) and a 12-bit gray scale. Lung nodule images were classified into five groups according to the degrees of subtlety shown. The observations of 20 participating radiologists were subjected to ROC analysis for detecting solitary pulmonary nodules. Experimental results (areas under the curve, Az) obtained from observer studies were used for characterization of five groups of lung nodules with different degrees of subtlety. RESULTS: ROC analysis showed that the database included a wide range of various nodules yielding Az values from 0.574 to 0.991 for the five categories of cases for different degrees of subtlety. CONCLUSION: This database can be useful for many purposes, including research, education, quality assurance, and other demonstrations.     

Comparison of radiologist and CAD performance in the detection of CT-confirmed subtle pulmonary nodules on digital chest radiographs

OBJECTIVES: Detection of subtle pulmonary nodules on digital radiography is a challenging task for radiologists. The aim of this study was to evaluate the performance of a newly approved computer aided detection (CAD) system. MATERIALS AND METHODS: The sensitivity of 3 radiologists and of a CAD system for the detection of pulmonary nodules from 5 to 15 mm in size on digital chest radiography of 117 patients was compared. The reference standard was established by consensus reading of computed tomography scans by 2 experienced radiologists. Computed tomography scans and chest radiographs were performed within 4 weeks. Sixty-six pulmonary nodules from 42 patients, with a mean nodule diameter of 7.5 mm (standard deviation: 2.2 mm), were included in the statistical analysis. Seventy-five of the 117 patients did not have nodules from 5 to 15 mm of size. RESULTS: Two hundred and eighty-eight false-positive detections of the CAD system were found with an average of 2.5 false-positives per image. Sensitivity of the CAD system was 39.4% (95% confidence interval: 11.8%), when compared with 18.2% to 30.3% (95% confidence interval 9.3% to 11.1%) of the 3 radiologists. Substantial agreement for nodule detection ([kappa]N: 0.64-0.73) was found among the 3 radiologists, whereas only moderate agreement was found between the radiologists and the CAD performance ([kappa]N: 0.45-0.52). CONCLUSIONS: The CAD system's diagnostic sensitivity in detecting pulmonary nodules of 5 to 15 mm of size was superior to the 1 of radiologists. The CAD system may be used for assisting the radiologist in the detection of lung nodules on digital chest radiographs.     

Computer-simulated lung nodules in digital chest radiographs for detection studies

Computer simulations of lung nodules overcome many shortcomings of creating radiographs using anthropomorphic nodule phantoms for lung nodule detection studies, but these algorithms can be cumbersome and involved. A simple, fast, and flexible computer program to simulate lung nodules in digital chest radiographs for detection studies is reported. To verify the realism of the simulated nodules, a psychophysical study and a statistical study were conducted. In the psychophysical study, six radiologists and four nonradiologists were asked to distinguish between 17 real lung nodules and 17 computer-simulated lung nodules shown in eight radiographs. The results show that the computer-simulated lung nodules are indistinguishable visually from real lung nodules. Using parameters from the Rose model of vision, results show that the simulated and real nodules are the same statistically. Thus, besides visual validity, statistical analysis in confirming the validity of the simulated lung nodules is included.     

Neural network based detection of pulmonary nodules on chest radiographs

PURPOSE: We investigated the capabilities of an artificial neural network-based Computer-Aided Diagnosis (CAD) system in improving early detection of pulmonary nodules on chest radiographs. MATERIAL AND METHODS: We used a data-set of 145 digitized chest films. Two different radiologists read the radiographs to detect the sites of possible nodules. The system uses two neural networks trained on a training-set of 100 radiographs selected from the data-set. The first network is used to focus attention on the sites of potential nodules while the second calculates the likeliness of nodule presence in ROIs. The clinical test was performed on 45 more radiographs from the training-set, but different from those in the data-set, which were positive for both benign and malignant nodules. These latter plain films showed 65 nodular lesions which differed by shape and acquisition technique. RESULTS: Sensitivity was 89% in all radiographs while specificity, evaluated by ROI, and accuracy, were 98%. CONCLUSIONS: There are potential limitations in nodule detection on plain radiographs. Some of them are operator-dependent, such as nonsystematic investigation, lesion underestimation, and poor reading, and some are technique-dependent, such as X-ray beam/tube, low voltage, patient positioning, focus-film distance and development process. CADs may contribute to improving detection of pulmonary nodules because the false-negative rate is decreased and sensitivity consequently increased. The high sensitivity and specificity rates of neural networks encourage further trials on wider data-sets to help the radiologist in the early detection of pulmonary nodules.     

Assessment of digital chest radiography using stimulable phosphor

In this pilot study, conventional and digital radiography of the chest was compared in 170 patients. Two digitized radiographs, one frequency modified and one simulating the conventional film-screen combination, and the conventional films were reviewed independently by 5 radiologists with different experience. In spite of the smaller size and lower spatial resolution of the digitized compared with the conventional radiograph, only slight differences were revealed in the observation of different pulmonary and mediastinal changes. Digitized radiography is therefore considered suitable for chest examinations.     

Computerized analysis of the likelihood of malignancy in solitary pulmonary nodules with use of artificial neural networks

PURPOSE: To develop a computer-aided diagnostic scheme by using an artificial neural network (ANN) to assist radiologists in the distinction of benign and malignant pulmonary nodules. MATERIALS AND METHODS: Fifty-six chest radiographs of 34 primary lung cancers and 22 benign nodules were digitized with a 0.175-mm pixel size and a 10-bit gray scale. Eight subjective image features were evaluated and recorded by radiologists in each case. A computerized method was developed to extract objective features that could be correlated with the subjective features. An ANN was used to distinguish benign from malignant nodules on the basis of subjective or objective features. The performance of the ANN was compared with that of the radiologists by means of receiver operating characteristic (ROC) analysis. RESULTS: Performance of the ANN was considerably greater with objective features (area under the ROC curve, Az = 0.854) than with subjective features (Az = 0.761). Performance of the ANN was also greater than that of the radiologists (Az = 0.752). CONCLUSION: The computerized scheme has the potential to improve the diagnostic accuracy of radiologists in the distinction of benign and malignant solitary pulmonary nodules.     

计算机辅助检测肺结节在数字化X线胸片肺癌筛查中的应用价值

目的 评价计算机辅助检测(CAD)肺结节系统在数字化X线胸片上肺癌筛查中的应用价值.方法 由1名放射科医师和CAD肺结节检测系统独立阅读100例连续的数字摄影(DR)X线胸片,CAD系统可以检出最长直径在5～15 mm的肺结节.由2名放射科专家(有15年胸部影像诊断经验)进行回顾性阅读,参照相应的CT图像,两人意见达成一致后标记真结节的个数和位置并保存标记结果,将标记结果作为金标准来比较放射科医师和CAD系统的肺结节检测敏感性和假阳性率.结果 放射科医师共检测到95个结节,CAD系统共检测到304个结节.在回顾性检查中2名放射科专家共标记134个真结节,其中放射科医师检测到82个(61.2%),CAD检测到105个(78.4%),CAD系统检测到而被放射科医师漏诊的结节35个,放射科医师检测到而CAD系统漏诊的结节10个.放射科医师应用CAD系统后检测到112个真结节,检测率提高到83.6%.放射科专家意见一致后认为CAD系统检出199个假阳性结节,平均每张胸片约2.0个.结论 在肺癌筛查中放射科医师和CAD系统必须联合应用才可以识别X线胸片中所有的结节.     

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.     

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.     

Improved pulmonary nodule detection with scanning equalization radiography

The potential for improved pulmonary nodule detection with scanning equalization radiography (SER) was evaluated by means of observer performance testing during the interpretation of posteroanterior conventional radiographs and SER images of an anthropomorphic chest phantom with simulated nodules. A test set of 200 conventional and 200 SER radiographs of phantoms containing either one nodule or none was interpreted by four radiologists attempting to detect a nodule and indicate a confidence value. Their ability to detect nodules positioned over the lung was slightly improved with SER compared with conventional radiography (sensitivity, .56 vs .70); for nodules over the mediastinum or diaphragmatic areas, it was much improved (sensitivity, .29 vs .64). The results were also analyzed with receiver-operating characteristic methods, which revealed a significant improvement in lesion detect-ability over the thicker body parts with SER images. The capability of equalized chest radiographs to provide improved lesion detectability suggests that SER may set a new standard for film-based chest radiography and have a large clinical application.     

Pulmonary nodule detection of chest phantom with CRT images--comparison with conventional radiography (film-screen system) and FCR (Fuji Computed Radiography) hardcopy

Conventional Radiography, Fuji Computed Radiography (FCR) hardcopy and CRT images were evaluated about the detectability of pulmonary nodule using the chest phantom. Conventional and digitized chest radiographs (FCR) were used, including 45 normal cases and 45 abnormal cases with a variety pulmonary nodule. Observer performance tests were conducted to compare the effects on diagnostic accuracy of Conventional Radiography, FCR hardcopy and CRT images, and diagnostic accuracy was determined with receiver operating characteristic (ROC) analysis. ROC study was performed in which six radiologists were asked to locate nodule on three modalities. Two CRT monitors were used to observed CRT images. The left side CRT monitor was divided into two parts and displayed two images which were done as same image processing as FCR hardcopy. The right side CRT monitor was divided into four parts and displayed four images as a subsidiary diagnosis. The upper two images were displayed to diagnose the nodule of cardiac and diaphragmatic area, and lower two images were displayed to diagnose the nodule of the lung field. The results were summarized as follows: 1) CRT images were superior in sensitivity (78.5%) to the others, and FCR hardcopys were superior in specificity (95.9%). 2) About the accuracy of 5 and 8 mm in diameter nodule detection, there was no significant difference among three modalities. 3) Diagnostic accuracy of 3 mm in diameter nodule detection was significantly greater with digitized radiographs (FCR 44.4%, CRT images 54.4%) than with conventional radiograph (17.7%).(ABSTRACT TRUNCATED AT 250 WORDS)     

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.     

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.     

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.     

Differentiation of benign from malignant pulmonary nodules with digitized chest radiographs

To assess whether it is possible to distinguish benign from malignant solitary pulmonary nodules with digital techniques, a retrospective study of 68 patients with proved solitary nodules was performed. The conventional chest radiograph for each patient was digitized to 2,048 X 2,048 X 12 bits, and changes in the optical density within the nodule were analyzed. A number (the corrected gradient number) was then generated that reflected this variation. Striking differences were noted between 26 malignant nodules and 21 calcified granulomas. The technique was then applied to 21 benign nodules that had initially required thoracotomy or further study for diagnosis. In nine of these 21 patients (43%), the corrected gradient number allowed correct classification as a benign lesion.     

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。     

数字化断层融合技术对肺结节筛查应用的初步研究

目的：探讨数字化断层融合技术对肺结节的检出价值.方法：选取48例肺结节患者,先后分别行DR、断层融合（DTS）及CT检查.将CT检查结果作为判断肺结节的标准,另选择两位有3年以上工作经验的放射科医师,在已知每例患者CT所显示的结节位置后,分别观察胸片和数字断层融合图像上对相应部位结节的显示率,对结果进行x2检验.将结节依据直径大小分为3组（3～5 cm,5～10 cm和10～20 cm）后,对组与组之间的观察结果进行比较.结果：48例患者共发现结节59个,DR和DTS发现结节的敏感度分别为47.46%（28/59）和88.14%（52/59）,x2检验示差异有显著性意义（P〈0.01）,结节直径为5～10 mm组DTS较DR检出结节的敏感度最高.59个结节中,CT显示磨玻璃密度结节16个,其中,DTS可显示14个（14/16）,DR显示2个（2/16）,DTS较DR显示率明显高.结论：数字化断层融合较传统DR可显著提高肺结节的检出率,对磨玻璃密度结节的检出率较高.