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A prototype multimedia medical database has been developed to provide image and textual data for thoracic oncology patients undergoing treatment of advanced malignancies. The database integrates image data from the hospital picture archiving and communication system with textual reports from the radiology information system, alphanumeric data contained in the hospital information system, and other electronic medical data. The database presents information in a timeline format and also contains visualization programs that permit the user to view and annotate radiographic measurements in tabular or graphic form. The database provides an efficient and intuitive display of the changing status of oncology patients. The ability to integrate, manage, and access relevant multimedia information may substantially enhance communication among distributed multidisciplinary health care providers and may ensure greater consistency and completeness of patient-related data.

Now the leading subtype of lung cancer, adenocarcinoma received a new classification in 2011. For tumors categorized previously as bronchioloalveolar carcinoma (BAC), criteria and terminology had not been uniform, so the 2011 classification provided four new terms: (a) adenocarcinoma in situ (AIS), representing histopathologically a small (≤3-cm), noninvasive lepidic growth, which at computed tomography (CT) is usually nonsolid; (b) minimally invasive adenocarcinoma, representing histopathologically a small (≤3-cm) and predominantly lepidic growth that has 5-mm or smaller invasion, which at CT is mainly nonsolid but may have a central solid component of up to approximately 5 mm; (c) lepidic predominant nonmucinous adenocarcinoma, representing histopathologically invasive adenocarcinoma that shows predominantly lepidic nonmucinous growth, which at CT is usually part solid but may be nonsolid or occasionally have cystic components; and (d) invasive mucinous adenocarcinoma, histopathologically showing lepidic growth as its predominant component, which at CT varies widely from solid to mostly solid to part solid to nonsolid and may be single or multiple (when multifocal, it was formerly called multicentric BAC). In addition, new histopathologic subcategories of acinar, papillary, micropapillary, and solid predominant adenocarcinoma are now described, all as nonmucinous, predominantly invasive, may include a small lepidic component, and at CT are usually solid but may include a small nonsolid component. The micropapillary subtype has a poorer prognosis than the other subtypes. In addition, molecular genetic correlations for the subcategories of adenocarcinoma of the lung are now a topic of increasing interest. As the new classification enters common use, further descriptions of related correlations can be anticipated.

Pathology and radiology form the core of cancer diagnosis, yet the workflows of both specialties remain ad hoc and occur in separate "silos," with no direct linkage between their case accessioning and/or reporting systems, even when both departments belong to the same host institution. Because both radiologists' and pathologists' data are essential to making correct diagnoses and appropriate patient management and treatment decisions, this isolation of radiology and pathology workflows can be detrimental to the quality and outcomes of patient care. These detrimental effects underscore the need for pathology and radiology workflow integration and for systems that facilitate the synthesis of all data produced by both specialties. With the enormous technological advances currently occurring in both fields, the opportunity has emerged to develop an integrated diagnostic reporting system that supports both specialties and, therefore, improves the overall quality of patient care.

Intrathoracic calcifications occur in a wide variety of disorders. Although they are usually harmless sequelae of remote processes, calcifications provide important information for establishing the diagnosis or for evaluating the progression of known disease. They may arise in the pulmonary parenchyma, mediastinum, hilar and mediastinal lymph nodes, pleura, chest wall, or any combination of these structures. The cause of the calcification may be determined by means of the location and pattern of the calcifications within the lung parenchyma and knowledge of the associated clinical features. Calcifications in the thorax are frequently manifestations of previous infectious processes. Less often, they may be due to neoplasms, metabolic disorders, occupational exposure, or previous medical therapy. Large intrathoracid calcifications are usually identified on conventional chest radiographs; detection of smaller calcifications may require use of other imaging modalities, such as dual-energy digital radiography, fluoroscopy, radionuclide scanning, computed tomography (CT), and high-resolution CT.

Background Randomized controlled trials (RCTs) evaluating cancer screening modalities usually employ cause-specific mortality as their primary endpoint. Because death certificate cause of death can be inaccurate, RCTs frequently use review committees to assign an underlying cause of death. We describe the National Lung Screening Trial's (NLST's) death review approach, the Endpoint Verification Process (EVP), which strives to minimize errors in assignment of cause of death due to lung cancer. Methods Deaths selected for review include those with a notation of lung cancer on the death certificate and those occurring among participants ever diagnosed with lung cancer. Other criteria that trigger death review include, but are not limited to, death within 6 months of a screen suspicious for lung cancer and death within 60 days of certain diagnostic evaluation procedures associated with a screen suspicious for lung cancer or a lung cancer diagnosis. EVP requires concordance on whether death was due to lung cancer. Deaths are first reviewed by the EVP chair. If concordance is not achieved, the death is next reviewed by an Endpoint Verification Team (EVT) member. If concordance between the chair- and member-assigned cause of death is not achieved, the death is next reviewed by a group of at least three EVT members. Cause of death is assigned at the step in which concordance was achieved, or if necessary, at the team review. Conclusions NLST's EVP is designed to produce a highly accurate count of lung cancer deaths.

Ample studies suggest that the cyclooxygenase-2 (COX-2)/prostaglandin E2 (PGE2) pathway plays a pivotal role in carcinogenesis and that COX-2 inhibition may help prevent lung cancer. Therefore, we conducted a randomized, double-blind, placebo-controlled trial of the COX-2–selective inhibitor celecoxib (400 mg bid for 6 months) in former-smokers (age ≥ 45, ≥ 30 pack-years of smoking, ≥ 1 year of sustained abstinence from smoking). We assessed the impact of celecoxib on cellular and molecular events associated with lung cancer pathogenesis; the primary endpoint was bronchial Ki-67 labeling index (Ki-67 LI) after 6 months of treatment. Of 137 randomized subjects, 101 completed both baseline and 6-month bronchoscopies and were evaluable for the primary endpoint analysis. The beneficial effect on Ki-67 LI was greater in the celecoxib arm (versus placebo) in a mixed-effects analysis (P = 0.0006), and celecoxib significantly decreased Ki-67 LI by an average of 34%, whereas placebo increased Ki-67 LI by an average of 3.8% (P = 0.04; t test). In participants who crossed over to the other study arm at 6 months (all of whom had received 6 months of celecoxib at the end of a 12 months treatment period), the decreases in Ki-67 LI correlated with a reduction and/or resolution of lung nodules on computed tomography. Celecoxib significantly reduced plasma c-reactive protein and interleukin-6 mRNA and protein and increased 15(S)-hydroxy-eicosatetraenoic acid levels in bronchoalveolar lavage (BAL) samples. The baseline ratio of COX-2 to 15-hydroxyprostaglandin dehydrogenase mRNA in BAL cells was a significant predictive marker of Ki-67 response to celecoxib (P = 0.002). Our collective findings support the continued investigation of celecoxib for lung cancer chemoprevention in former smokers at a low risk of cardiovascular disease. Cancer Prev Res; 4(7); 984–93. ©2011 AACR.

Introduction: Adenocarcinoma is the most common histologic type of lung cancer. To address advances in oncology, molecular biology, pathology, radiology, and surgery of lung adenocarcinoma, an international multidisciplinary classification was sponsored by the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society. This new adenocarcinoma classification is needed to provide uniform terminology and diagnostic criteria, especially for bronchioloalveolar carcinoma (BAC), the overall approach to small nonresection cancer specimens, and for multidisciplinary strategic management of tissue for molecular and immunohistochemical studies. Methods: An international core panel of experts representing all three societies was formed with oncologists/pulmonologists, pathologists, radiologists, molecular biologists, and thoracic surgeons. A systematic review was performed under the guidance of the American Thoracic Society Documents Development and Implementation Committee. The search strategy identified 11,368 citations of which 312 articles met specified eligibility criteria and were retrieved for full text review. A series of meetings were held to discuss the development of the new classification, to develop the recommendations, and to write the current document. Recommendations for key questions were graded by strength and quality of the evidence according to the Grades of Recommendation, Assessment, Development, and Evaluation approach. Results: The classification addresses both resection specimens, and small biopsies and cytology. The terms BAC and mixed subtype adenocarcinoma are no longer used. For resection specimens, new concepts are introduced such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) for small solitary adenocarcinomas with either pure lepidic growth (AIS) or predominant lepidic growth with ≤5 mm invasion (MIA) to define patients who, if they undergo complete resection, will have 100% or near 100% disease-specific survival, respectively. AIS and MIA are usually nonmucinous but rarely may be mucinous. Invasive adenocarcinomas are classified by predominant pattern after using comprehensive histologic subtyping with lepidic (formerly most mixed subtype tumors with nonmucinous BAC), acinar, papillary, and solid patterns; micropapillary is added as a new histologic subtype. Variants include invasive mucinous adenocarcinoma (formerly mucinous BAC), colloid, fetal, and enteric adenocarcinoma. This classification provides guidance for small biopsies and cytology specimens, as approximately 70% of lung cancers are diagnosed in such samples. Non-small cell lung carcinomas (NSCLCs), in patients with advanced-stage disease, are to be classified into more specific types such as adenocarcinoma or squamous cell carcinoma, whenever possible for several reasons: (1) adenocarcinoma or NSCLC not otherwise specified should be tested for epidermal growth factor receptor (EGFR) mutations as the presence of these mutations is predictive of responsiveness to EGFR tyrosine kinase inhibitors, (2) adenocarcinoma histology is a strong predictor for improved outcome with pemetrexed therapy compared with squamous cell carcinoma, and (3) potential life-threatening hemorrhage may occur in patients with squamous cell carcinoma who receive bevacizumab. If the tumor cannot be classified based on light microscopy alone, special studies such as immunohistochemistry and/or mucin stains should be applied to classify the tumor further. Use of the term NSCLC not otherwise specified should be minimized. Conclusions: This new classification strategy is based on a multidisciplinary approach to diagnosis of lung adenocarcinoma that incorporates clinical, molecular, radiologic, and surgical issues, but it is primarily based on histology. This classification is intended to support clinical practice, and research investigation and clinical trials. As EGFR mutation is a validated predictive marker for response and progression-free survival with EGFR tyrosine kinase inhibitors in advanced lung adenocarcinoma, we recommend that patients with advanced adenocarcinomas be tested for EGFR mutation. This has implications for strategic management of tissue, particularly for small biopsies and cytology samples, to maximize high-quality tissue available for molecular studies. Potential impact for tumor, node, and metastasis staging include adjustment of the size T factor according to only the invasive component (1) pathologically in invasive tumors with lepidic areas or (2) radiologically by measuring the solid component of part-solid nodules.

Background. The clinical staging and management of both primary and metastatic lung lesions depends on accurate imaging techniques. Biochemical imaging with positron emission tomography, (PET), and the glucose analog 2-[18F]-fluoro-2-deoxy-D-glucose, (FDG), complements anatomic imaging with conventional radiologic methods. Methods. A new “whole-body” PET FDG technique that produces two-dimensional, nontomographic and tomographic longitudinal images of the entire body has been developed at UCLA. Sixteen patients with known pulmonary nodules who had undergone thoracic computed tomography (CT) were studied with whole-body PET FDG imaging at the UCLA Medical Center. Results. This PET FDG imaging method identified metabolically active tumor foci in all eight patients with bronchogenic carcinomas, four patients with metastatic lesions to the thorax, and two patients with Hodgkin disease. All diagnoses were confirmed histologically. Additionally, the PET FDG technique detected extrathoracic metastases in 4 of 16 patients. Thoracic CT was not diagnostic of neoplasm in two of the eight patients with bronchogenic carcinomas. In one patient with an ACTH-producing bronchial carcinoid, the lesion ultimately was detected on high-resolution CT but was not metabolically active on PET FDG imaging. Conclusions. This is the first report of whole-body PET FDG imaging in patients with thoracic lesions. PET FDG imaging accurately detected metabolically active tumor (both intrathoracic and extrathoracic) in patients with bronchogenic carcinoma, pulmonary metastatic disease, and Hodgkin lymphoma. Because lung cancer is characteristically a multisystem disease, this whole-body PET FDG technique has significant implications for treatment planning. Cancer 1993; 72:82–90.

The factors influencing the image fidelity of gray-scale monitors and how they are determined through both physical and psycho-physical measurements are discussed. Estimation techniques for the amount of image data to be displayed, both the daily digital image data volume and the estimation of the number of gray-scale display stations required, are also examined. Gray-scale display station hardware and software designs are presented. It is pointed out that exceptional attention must be paid to the details of workstation design, as this is the sole interface of the radiologist to the resources of the digital image management network. >

Objective To provide health-care providers, patients, and the general public with a responsible assessment of currently available data on the diagnosis and management of ductal carcinoma in situ (DCIS). Participants A non-Department of Health and Human Services, nonadvocate, 14-member panel representing the fields of oncology, radiology, surgery (general and reconstructive), pathology, radiation oncology, internal medicine, epidemiology, biostatistics, nursing, obstetrics and gynecology, preventative medicine and population health, and social work. In addition, 22 experts from pertinent fields presented data to the panel and conference audience. Evidence Presentations by experts and a systematic review of the literature prepared by the Minnesota Evidence-based Practice Center, through the Agency for Healthcare Research and Quality. Scientific evidence was given precedence over anecdotal experience. Conference process The panel drafted its statement based on scientific evidence presented in open forum and on published scientific literature. The draft statement was presented on the final day of the conference and circulated to the audience for comment. The panel released a revised statement later that day at http://consensus.nih.gov. This statement is an independent report of the panel and is not a policy statement of the National Institutes of Health or the Federal Government. Conclusions Clearly, the diagnosis and management of DCIS is highly complex with many unanswered questions, including the fundamental natural history of untreated disease. Because of the noninvasive nature of DCIS, coupled with its favorable prognosis, strong consideration should be given to elimination of the use of the anxiety-producing term "carcinoma" from the description of DCIS. The outcomes in women treated with available therapies are excellent. Thus, the primary question for future research must focus on the accurate identification of patient subsets diagnosed with DCIS, including those persons who may be managed with less therapeutic intervention without sacrificing the excellent outcomes presently achieved. Essential in this quest will be the development and validation of accurate risk stratification methods based on a comprehensive understanding of the clinical, pathological, and biological factors associated with DCIS.

Gray-scale monitors are an essential element of electronic radiology, and their ability to provide images that are perceived to be identical to those available on conventional or laser-printed film is crucial to success of electronic radiology. Image fidelity is measured in physical characteristics (luminance, dynamic range, distortion, resolution, and noise) and with psychophysical techniques, including receiver operator characteristics analysis with clinical images and testing with contrast-detail patterns to determine threshold contrast. Currently, laser-printed images facilitate greater information transfer than does a gray-scale monitor because of their higher absolute luminance (500 ft-L vs 60 ft-L), greater perceived dynamic range, and better spatial resolution. In the near future, the developments of gray-scale monitors with 150-200 ft-L luminance, a display standard based on just noticeable differences, and algorithms to improve similarities between gray-scale display images and laser-printed images will help increase the acceptability of monitors as a means to make primary diagnoses.

Conventional PA and lateral chest radiographs continue to be the initial examination of choice to evaluate patients who are suspected of having a pulmonary parenchymal neoplasm. A lung lesion can be characterized as probably benign or malignant based on its radiographic appearance (size, shape, margins, presence of calcification, cavitation or air bronchograms, growth rate). A spiculated or lobulated lesion greater than 3 cm in size that is noncalcified is highly suspicious for malignancy. A lung lesion less than 3 cm in size with smooth borders that appears noncalcified on conventional radiographs should be examined by CT, including densitometry to detect calcification or fat, which indicates benignity. In patients with known lung cancer, CT can help to stage the tumor by indicating hilar or mediastinal involvement, or distant metastases. Currently, MR imaging has a limited role, but can be used as a "problem solving" modality for selected cases in evaluating pulmonary parenchymal neoplasms.

An understanding of medical imaging informatics begins with knowledge of medical imaging and its application toward diagnostic and therapeutic clinical assessment. This chapter is divided into two sections: a review of current imaging modalities; and a primer on imaging anatomy and physiology. In the first half, we introduce the major imaging modalities that are in use today: projectional imaging, computed tomography, magnetic resonance, and ultrasound. The core physics concepts behind each modality; the parameters and algorithms driving image formation; and variants and newer advances in each of these areas are briefly covered to familiarize the reader with the capabilities of each technique. From this foundation, in the second half of the chapter we describe several anatomical and physiologic systems from the perspective of imaging. Three areas are covered in detail: 1) the respiratory system; 2) the brain; and 3) breast imaging. Additional coverage of musculoskeletal, cardiac, urinary, and upper gastrointestinal systems is included. Each anatomical section begins with a general description of the anatomy and physiology, discusses the use of different imaging modalities, and concludes with a description of common medical problems/conditions and their appearance on imaging. From this chapter, the utility of imaging and its complexities becomes apparent and will serve to ground discussion in future chapters.

To provide health care providers, patients, and the general public with a responsible assessment of currently available data on the diagnosis and management of ductal carcinoma in situ (DCIS).An non-DHHS, nonadvocate 14-member panel representing the fields of fields of oncology, radiology, surgery (general and reconstructive), pathology, radiation oncology, internal medicine, epidemiology, biostatistics, nursing, obstetrics and gynecology, preventative medicine and population health, and social work. In addition, 22 experts from pertinent fields presented data to the panel and conference audience.Presentations by experts and a systematic review of the literature prepared by the Minnesota Evidence-based Practice Center, through the Agency for Healthcare Research and Quality. Scientific evidence was given precedence over anecdotal experience.The panel drafted its statement based on scientific evidence presented in open forum and on published scientific literature. The draft statement was presented on the final day of the conference and circulated to the audience for comment. The panel released a revised statement later that day at http://consensus.nih.gov. This statement is an independent report of the panel and is not a policy statement of the NIH or the Federal Government.The diagnosis and management of DCIS is highly complex with many unanswered questions, including the fundamental natural history of untreated disease. Because of the noninvasive nature of DCIS, coupled with its favorable prognosis, strong consideration should be given to remove the anxiety-producing term "carcinoma" from the description of DCIS. The outcomes in women treated with available therapies are excellent. Thus, the primary question for future research must focus on the accurate identification of patient subsets diagnosed with DCIS, including those persons who may be managed with less therapeutic intervention without sacrificing the excellent outcomes presently achieved. Essential in this quest will be the development and validation of accurate risk stratification methods based on a comprehensive understanding of the clinical, radiological, pathological, and biological factors associated with DCIS.

Computed tomography has acquired an increasingly central role in the evaluation of asbestos-exposed individuals. The advantages of increased contrast resolution and axial image display have extended our ability to interrogate areas of the pulmonary parenchyma and pleura that are inadequately seen on chest radiographs. The additional information to be gained from CT evaluation must be balanced by the additional expense and time required, particularly in view of the large numbers of asbestos-exposed individuals who will undergo screening over the coming decades. Ideally, imaging strategies that include CT should emphasize those problematic situations in which additional information will serve a differential or diagnostic function, alter the management or habits of the individuals, modify the working environment, or improve our understanding of asbestos-induced diseases. The chest radiograph is the mainstay in the imaging evaluation of asbestos-exposed individuals, providing an inexpensive and rapid appraisal of the presence of both focal and diffuse abnormalities of the pleura and lung parenchyma. Conventional (whole-thorax) CT may be an important adjunct in the following situations: (1) to clarify the presence of pleural thickening, particularly in distinguishing pleural disease from normal extrapleural soft tissues; (2) to stage and determine tumor extent in malignant pleural mesothelioma; (3) to identify optimal sites for biopsy of suspicious pleural changes; and (4) to detect and characterize lung cancers or other focal masses that may be obscured by extensive pleural or parenchymal fibrosis. Limited HRCT studies are roughly competitive in time and cost with four-view radiographic examinations. There is growing evidence that HRCT can detect interstitial disease in advance of conventional clinical or radiographic studies. However, the application of limited HRCT for large-scale screening is controversial. This issue will be resolved as we gain greater understanding of the specificity of HRCT and establish guidelines for standardizing the technique and image interpretation. At present, limited HRCT scans can supplement the evaluation of subjects in whom there is equivocal parenchymal or pleural disease on radiographs or unexplained abnormalities on pulmonary function tests. In individuals with significant pleural disease, HRCT can effectively define the presence and extent of interstitial fibrosis. In individuals with combined cigarette smoking-asbestos exposure in whom symptoms or functional abnormalities are present, HRCT may play a central role in distinguishing emphysematous lung destruction from the peripheral interstitial changes of asbestosis.

Studies that evaluate the lung nodule detection performance of radiologists or computerized methods depend on an initial inventory of the nodules within the thoracic images (the "truth"). The purpose of this study was to analyze (1) variability in the "truth" defined by different combinations of experienced thoracic radiologists and (2) variability in the performance of other experienced thoracic radiologists based on these definitions of "truth" in the context of lung nodule detection in computed tomographic (CT) scans.Twenty-five thoracic CT scans were reviewed by four thoracic radiologists, who independently marked lesions they considered to be nodulesor=3 mm in maximum diameter. Panel "truth" sets of nodules were then derived from the nodules marked by different combinations of two and three of these four radiologists. The nodule detection performance of the other radiologists was evaluated based on these panel "truth" sets.The number of "true" nodules in the different panel "truth" sets ranged from 15 to 89 (mean 49.8 +/- 25.6). The mean radiologist nodule detection sensitivities across radiologists and panel "truth" sets for different panel "truth" conditions ranged from 51.0 to 83.2%; mean false-positive rates ranged from 0.33 to 1.39 per case.Substantial variability exists across radiologists in the task of lung nodule identification in CT scans. The definition of "truth" on which lung nodule detection studies are based must be carefully considered, because even experienced thoracic radiologists may not perform well when measured against the "truth" established by other experienced thoracic radiologists.

Lung cancer is the leading cause of cancer death in the United States. Non-small cell lung cancer accounts for 75% to 80% of all lung cancers. There is an impetus to find a screening test that can detect non-small cell lung cancer in its early preclinical stages, when surgical resection is most likely to reduce lung cancer mortality. Although earlier randomized controlled trials of lung cancer screening using chest radiography and sputum cytology failed to show reduced lung cancer mortality, CT is a much more sensitive test for detecting small lung nodules, and has generated considerable enthusiasm as a potential contemporary screening tool for lung cancer.

ARDS is the clinical consequence of acute lung injury that results in increased-permeability edema. Distinct pathophysiologic stages are reflected in the radiographic evolution of the syndrome. Diffuse microatelectasis, proteinaceous edema fluid, and multifocal in situ pulmonary vascular occlusions characterize the acute stages of injury and result in the appearance of diffuse consolidations and occasional pleural effusions on the radiograph. In the chronic organizing stage of ARDS, the physiologic consequences of subsiding edema and tissue repair may be reflected by a transition to stable interstitial patterns. There is a high frequency of complications related to the decreased compliance of the injured lung that lead to interstitial emphysema and other barotraumatic complications. Survivors of ARDS exhibit various degrees of physiologic impairment and radiographic abnormality that may improve during the first year after survival. The relations between various indices of the severity of ARDS and the ultimate outcome are emerging. Debate continues about the specificity of the chest radiograph in distinguishing increased-permeability edema from hydrostatic edema. In fact, interstitial patterns and pleural effusions are observed in both. Nonetheless, the chest radiograph is a pivotal tool for monitoring patients at risk of serious morbidity from nosocomial lung infection, barotrauma, and the complications accompanying the use of invasive devices. It is hoped that as we develop a more uniform consensus on the clinical definition of ARDS and begin to classify patients according to specific clinical or physiologic observations, chest radiographic observation will acquire greater diagnostic and prognostic significance in these critically ill patients.

Eight patients with the diagnosis of lymphangiomyomatosis were evaluated with computed tomography (CT), chest radiography, and pulmonary function tests to determine the relationship between the extent of disease seen on imaging studies and functional status. Chest radiographic assessment included the subjective determination of disease extent and measurements of lung length and the arc of the right hemidiaphragm. Disease extent on CT scans was scored as a percentage of lung that was abnormal on the basis of visual assessment of the degree of cystic replacement of the lung parenchyma. Significant correlations were observed between CT scores and percentages of predicted forced expiratory volume in 1 second/forced vital capacity (r = -.92, P less than .002) and diffusing capacity of the lungs for carbon monoxide (r = -.80, P less than .017). No significant correlations were observed between subjective chest radiographic scores and pulmonary function tests, although measurements of lung length and percentage of predicted total lung capacity were correlated (r = .76, P less than .045). CT was more accurate than chest radiography in defining the presence and extent of parenchymal cysts and provided for greater morphologic-physiologic correlation. CT, particularly high-resolution CT, may be useful in the diagnosis and longitudinal evaluation of patients with this disease and may be more sensitive than pulmonary function tests in the early stages of lung damage.

A wide variety of lesions occur in the mediastinum in patients of every age. Twenty five to 50 percent of these primary mediastinal masses may be malignant, making early diagnosis and therapy crucial. Since most arise from normal structures in the region, localization of lesions to compartments of the mediastinum may assist in diagnosis. This article reviews imaging techniques for lesions originating in the mediastinum.

A combination of cytotoxic and corticosteroid therapy has dramatically improved the long-term survival of patients with Wegener granulomatosis. With extended survival, patients now experience diverse cardiopulmonary abnormalities that represent primary or secondary manifestations of the disease or that result from diagnosis and treatment. To evaluate these abnormalities, the authors reviewed the medical histories and chest radiologic findings of 19 patients with the histologic diagnosis of Wegener granulomatosis. In these patients thoracic images demonstrated parenchymal nodules or consolidations with cavitation, diffuse interstitial disease, mediastinal or hilar adenopathy, and isolated stenoses of the larynx or tracheobronchial tree. Intrathoracic relapse occurred in 18 cases; in one-third of these patients, findings at relapse differed from those at initial presentation. Complications from diagnosis or therapy occurred in nine patients. Pulmonary infection was the most frequent complication causing morbidity and was often clinically indistinguishable from the primary disease; it complicated relapse in five patients. The successful radiologic follow-up of patients with Wegener granulomatosis requires a consideration of the varied thoracic manifestations of both the primary disease and the complications of its treatment.

Thoracic imaging constitutes more than one-third of all medical imaging performed in the United States. Despite the substantial impact of computer technology in other areas of imaging, conventional film-screen acquisition systems still provide the bulk of projectional chest radiography. The successful implementation of digital technology in thoracic imaging requires that the standards of current film-screen methods for both diagnostic accuracy and efficient data management be preserved. This article addresses the technical and clinical aspects of film digitization and storage phosphor technology, which are the two digital acquisition systems in widest application. Scanned projection radiography, which may now be applied to computed radiography systems, is also discussed. Finally, some of the issues surrounding the implementation of picture archiving and communication systems for thoracic imaging are addressed.

RATIONALE AND OBJECTIVES: The Lung Image Database Consortium (LIDC) is developing a publicly available database of thoracic computed tomography (CT) scans as a medical imaging research resource to promote the development of computer-aided detection or characterization of pulmonary nodules. To obtain the best estimate of the location and spatial extent of lung nodules, expert thoracic radiologists reviewed and annotated each scan. Because a consensus panel approach was neither feasible nor desirable, a unique two-phase, multicenter data collection process was developed to allow multiple radiologists at different centers to asynchronously review and annotate each CT scan. This data collection process was also intended to capture the variability among readers.MATERIALS AND METHODS: Four radiologists reviewed each scan using the following process. In the first or "blinded" phase, each radiologist reviewed the CT scan independently. In the second or "unblinded" review phase, results from all four blinded reviews were compiled and presented to each radiologist for a second review, allowing the radiologists to review their own annotations together with the annotations of the other radiologists. The results of each radiologist's unblinded review were compiled to form the final unblinded review. An XML-based message system was developed to communicate the results of each reading.RESULTS: This two-phase data collection process was designed, tested, and implemented across the LIDC. More than 500 CT scans have been read and annotated using this method by four expert readers; these scans either are currently publicly available at http://ncia.nci.nih.gov or will be in the near future.CONCLUSIONS: A unique data collection process was developed, tested, and implemented that allowed multiple readers at distributed sites to asynchronously review CT scans multiple times. This process captured the opinions of each reader regarding the location and spatial extent of lung nodules.

RATIONALE AND OBJECTIVES: The purpose of this study was to analyze the variability of experienced thoracic radiologists in the identification of lung nodules on computed tomography (CT) scans and thereby to investigate variability in the establishment of the "truth" against which nodule-based studies are measured.MATERIALS AND METHODS: Thirty CT scans were reviewed twice by four thoracic radiologists through a two-phase image annotation process. During the initial "blinded read" phase, radiologists independently marked lesions they identified as "nodule >or=3 mm (diameter)," "nodule or=3 mm." During the subsequent "unblinded read" phase, the blinded read results of all four radiologists were revealed to each radiologist, who then independently reviewed their marks along with the anonymous marks of their colleagues; a radiologist's own marks then could be deleted, added, or left unchanged. This approach was developed to identify, as completely as possible, all nodules in a scan without requiring forced consensus.RESULTS: After the initial blinded read phase, 71 lesions received "nodule >or=3 mm" marks from at least one radiologist; however, all four radiologists assigned such marks to only 24 (33.8%) of these lesions. After the unblinded reads, a total of 59 lesions were marked as "nodule >or=3 mm" by at least one radiologist. Twenty-seven (45.8%) of these lesions received such marks from all four radiologists, three (5.1%) were identified as such by three radiologists, 12 (20.3%) were identified by two radiologists, and 17 (28.8%) were identified by only a single radiologist.CONCLUSION: The two-phase image annotation process yields improved agreement among radiologists in the interpretation of nodules >or=3 mm. Nevertheless, substantial variability remains across radiologists in the task of lung nodule identification.

In the past decade, lung transplantation has become established as an accepted therapy for end-stage pulmonary disease. Complications of lung transplantation that may occur in the immediate or longer postoperative term include mechanical problems due to a size mismatch between the donor lung and the recipient thoracic cage; malposition of monitoring tubes and lines; injuries from ischemia and reperfusion; acute pleural events; hyperacute, acute, and chronic rejection; pulmonary infections; bronchial anastomotic complications; pulmonary thromboembolism; upper-lobe fibrosis; primary disease recurrence; posttransplantation lymphoproliferative disorder; and native lung complications such as hyperinflation, malignancy, and infection. Radiologic imaging--particularly chest radiography, computed tomography (CT), and high-resolution CT--is critical for the early detection, evaluation, and diagnosis of complications after lung transplantation. To enable the selection of an effective and relevant course of therapy and, ultimately, to decrease morbidity and mortality among lung transplant recipients, radiologists at all levels of experience must be able to recognize and understand the imaging manifestations of posttransplantation complications.

This study developed a methodology to extract the quantitative features of representing nodule 3D shape and investigate the performance of these features in differentiating between benign and malignant solitary pulmonary nodules (SPNs). 36 cases with solitary lung nodules (15 Benign, 21 Malignant) were examined in this study. The CT helical scanning-parameters were l3 mm collimation, pitch 1-2, and 1.5-3 mm reconstruction interval. The nodule boundaries were contoured by radiologists on 3D volume data. Using these boundaries, the nodule physical 3D surfaces were created and several 3D nodule shape-features were computed, including: Compactness Factor (CF) of nodule, Shape Index (SI) and curvedness of each pixel in the physical 3D nodule surface. The histogram characteristic features of SI and curvedness were calculated. AdaBoost was performed to select the features and their statistically differences were analyzed. Logistic Regression Analysis (LRA) and AdaBoost were used to evaluate the overall diagnostic accuracy. For 36 patients, CF is the first feature selected by AdaBoost, which also has significant difference ( t -test, P =0.6%) between Benign and malignant nodules. However, histogram features of SI and curvedness are not all significantly different. The accuracy of LRA is 75%, with accuracies of AdaBoost using all features is about 80% with cross validation. Generally, SI, curvedness and CF may provide a comprehensive examination of the nodule shape, which can be used in differentiating benign from malignant SPNs. However, other types' features (such as texture, angiogenesis) should be combined with shape information to assist radiologists in characterizing SPNs more accurately.

The LIDC is developing a publicly available database of thoracic computed tomography (CT) scans as a medical imaging research resource. A unique multi-center data collection process and communication system were developed to share image data and to capture the location and spatial extent of lung nodules as marked by expert radiologists. A two-phase data collection process was designed to allow multiple radiologists at different centers to asynchronously review and annotate each CT image series. Four radiologists reviewed each case using this process. In the first or "blinded" phase, each radiologist reviewed the CT series independently. In the second or "unblinded" review phase, the results from all four blinded reviews are compiled and presented to each radiologist for a second review. This allows each radiologist to review their own annotations along with those of the other radiologists. The results from each radiologist's unblinded review were compiled to form the final unblinded review. There is no forced consensus in this process. An XML-based message system was developed to communicate the results of each reading. This two-phase data collection process was designed, tested and implemented across the LIDC. It has been used for more than 130 CT cases that have been read and annotated by four expert readers and are publicly available at (http://ncia.nci.nih.gov). A data collection process was developed, tested and implemented that allowed multiple readers to review each case multiple times and that allowed each reader to observe the annotations of other readers.

The development of computer-aided diagnostic (CAD) systems requires an initial establishment of "truth" by expert human observers. Potential inconsistencies in the "truth" data must be identified and corrected before investigators can rely on this data. We developed a quality assurance model to supplement the "truth" collection process for lung nodules on CT scans. A two-phase process was established for the interpretation of CT scans by four radiologists. During the initial "blinded read," radiologists independently assigned lesions they identified into one of three categories: "nodule g 3mm," "nodule < 3mm," or "non-nodule g 3mm." During the subsequent "unblinded read," the blinded read results of all radiologists were revealed. The radiologists then independently reviewed their marks along with their colleague's marks; a radiologist's own marks could be left unchanged, deleted, switched in terms of lesion category, or additional marks could be added. The final set of marks underwent quality assurance, which consisted of identification of potential errors that occurred during the reading process and error correction. All marks were visually grouped into discrete nodules. Six categories of potential error were defined, and any nodule with a mark that satisfied the criterion for one of these categories was referred to the radiologist who assigned the mark in question. The radiologist either corrected the mark or confirmed that the mark was intentional. A total of 829 nodules were identified by at least one radiologist in 100 CT scans through the two-phase process designed to capture "truth." The quality assurance process yielded 81 nodules with potential errors. The establishment of "truth" must incorporate a quality assurance model to guarantee the integrity of the "truth" that will provide the basis for the training and testing of CAD systems.

Rationale and Objectives The American College of Radiology Imaging Network is participating in the National Lung Screening Trial, a large, multicenter, randomized controlled trial, comparing multidetector helical computed tomography (MDCT) versus chest radiography (CXR) in screening for lung cancer. Because the threshold for detection of disease is an inherent function of image quality, and consistent image quality is necessary to track changes in suspicious findings, our purpose was to develop an image quality control (QC) program across all clinical sites for both modalities. Materials and Methods The primary goals of the QC program include standardization of imaging protocols, certification of imaging equipment, and ongoing, periodic evaluation of the equipment calibration and image quality. Minimum standards for equipment and standardized cross-platform acquisition protocols are achieved via radiologist and physicist attestation forms and web-distributed technique charts, respectively. Imaging equipment performance standards are implemented through an initial machine certification process that includes equipment calibration. Ongoing assessment of equipment performance and calibration, as well as adherence to established imaging protocols. is accomplished via periodic submission of calibration records and phantom images. Participant-specific image acquisition parameters are entered into a web-based centralized database and variations from established protocols are automatically flagged for review. Participant radiation dose can be estimated from the image acquisition parameters applied to the imaging equipment calibration measurements. A radiologist visual review committee also evaluates participant images for diagnostic quality. Data are collected from 23 independent centers, representing 14 models of MDCT scanners from four manufacturers, and CXR systems that include film-screen, computed radiography, and direct digital radiography systems. Results Widespread imaging protocol variation in extant clinical practice—as well as variability in equipment technology, image acquisition parameters, manufacturer terminology, and user interface—have required careful standardization as a prerequisite to trial participation and ongoing image QC. Acceptable ranges for image acquisition parameters have been refined to accommodate continuously evolving equipment platforms and the scope of participant size and body habitus. Conclusion Standardization of imaging protocols is a critical component of image-based clinical trials, predicated on ongoing dialogue between sites and a centralized review committee.

Rationale and Objectives We sought to determine how measures of nodule diameter and volume on computed tomography (CT) vary with changes in inspiratory level. Materials and Methods CT scans were performed with inspiration suspended at total lung capacity (TLC) and then at residual volume (RV) in 41 subjects, in whom 75 indeterminate lung nodules were detected. A fully automated contouring program was used to segment the lungs; followed by segmentation of all nodules and the corresponding lobe using semiautomated contouring in both TLC and RV scans. The percent changes in lung and lobar volumes between TLC and RV were correlated with percent changes in nodule diameters and volumes. Results Both nodule diameter and volume varied nonuniformly from TLC to RV—some nodules decreased in size, while others increased. There was a 16.8% mean change in absolute volume across all nodules. Stratified by size, the mean value of the absolute percent volume changes for nodules ≥5 mm and P = .26). Stratified by maximum attenuation, the mean value of the absolute percent volume changes between the TLC and RV series for noncalcified (17.7%, SD = 13.1) and completely calcified nodules (8.6% SD = 5.7) were significantly different ( P Conclusion Significant differences in nodule size were measured between TLC and RV scans. This has important implications for standardizing acquisition protocols in any setting where size and, more important, size change are being used for purposes of lung cancer staging, nodule characterization, or treatment response assessment.

The aim of our investigation was to assess the influence of both CT acquisition dose and reconstruction kernel on computer-aided detection (CAD) of pulmonary nodules. Our hypothesis is that the detection of small nodules is affected by the noise characteristics of the image and the signal to noise ratio of the nodule and bronchiovascular anatomy. Knowledge gained from this experiment will assist in developing an advanced CAD system designed to detect smaller and more subtle nodules with minimal false positives. Eleven research subjects were selected from the Lung Image Database Consortium (LIDC) database based on our inclusion criteria of: 1) having at least one nodule and 2) available raw CT projection data for the series that our institution submitted to the LIDC study. Using the original raw projection data, research software simulated raw projection data acquired with a dose reduced 32-40% from the original scan. Projection data for both dose levels was reconstructed with smooth to very sharp kernels (B10f, B30f, B50f, and B70f). The resulting series were used to investigate the influence of dose and reconstruction kernel on CAD performance. A prototype CAD system was used to investigate changes in sensitivity and false positives with varying imaging parameters. In a sub-study, the prototype system was compared to a commercial CAD system. We did not have enough subjects to conclude significance, but the results indicate our research system had a higher sensitivity with the smooth or medium reconstruction kernels than with the sharper kernels. The sensitivity was similar for both dose levels. The false positive rate was higher with the smooth kernels and the lower dose levels.

Studies have shown that vascular structure of a solitary pulmonary nodule (SPN) can give insight into the diagnosis of the nodule. The purpose of this study is to investigate the utility of texture analysis as a quantitative measure of the vascular structure of a nodule. A contrast CT study was conducted for 29 patients with an indeterminate SPN. For each patient, the post-contrast series at maximum enhancement was volumetrically registered to the pre-contrast series. The two registered series were subtracted to form difference images of the nodule and each voxel was color-coded into 7 bins. Initially, a representative image of each nodule was subjectively rated on a five-point by a radiologist as to the magnitude, extent, and heterogeneity of the enhancement. From the initial analysis the heterogeneity of the nodule was found to be significantly different for benign versus malignant nodules (p

To investigate the utility of a computer-aided diagnosis (CAD) in the task of differentiating malignant nodules from benign nodules based on quantitative features extracted from volumetric thin section CT image data acquired before and after the injection of contrast media.35 volumetric CT datasets of solitary pulmonary nodules (SPN) with proven diagnoses (19 malignant/16 benign) were contoured by a thoracic radiologist. All studies had at least a baseline series obtained without contrast media and at least one series following an intravenous contrast injection at 45, 90, 180, and 360 seconds. Two separate contours were created for each nodule: one including only the solid portion and another including the ground-glass component, if any, of the nodule. For each contour 31 features were calculated that measured the attenuation, shape, and enhancement of the nodule due to the injection of contrast. These features were input into a feature selection step and three different classifiers to determine if the diagnosis could be predicted from the resulting feature vector. In addition, observer input was introduced to two of the classifiers as an a priori probability of malignancy and the resulting performance was compared. Training and testing was conducted in a resubstitution and leave-one-out fashion and performance was evaluated using ROC analysis.In a leave-one-out testing methodology, the classifiers achieved areas under the ROC curves AZ that ranged from 0.69 to 0.92. A classifier based on logistic regression performed the best with an AZ of 0.92 while a classifier based on quadratic discriminant analysis performed the poorest (AZ, 0.69). The AZ increased when using a priori observer input in most cases reaching a maximum of 0.95.Based on this initial work with a limited number of nodules in our dataset, it appears that CAD using volumetric and contrast-enhanced data has the potential to assist radiologists in the task of differentiating solitary pulmonary nodules and in the management of these patients. Further studies with an increased number of patients are required to validate these results.

We sought to investigate the utility of a computer-aided diagnosis in the task of differentiating malignant nodules from benign nodules based on single thin-section computed tomography image data.Eighty-one thin-section computed tomography data sets of solitary pulmonary nodules with proven diagnoses (48 malignant and 33 benign) were contoured manually on a single representative slice by a thoracic radiologist (10 years of experience). Two separate contours were created for each nodule, one including only the solid portion of the nodule and one including any ground-glass components. For each contour 75 features were calculated that measured the attenuation, shape, and texture of the nodule. These features were than input into a feature selection step and four different classifiers to determine if the diagnosis could be predicted from the feature vector. Training and testing was conducted in a resubstitution and leave-one-out fashion and performance was evaluated using ROC techniques.In a leave-one-out testing methodology the classifiers resulted with areas under the ROC curve (A(Z)) that ranged from 0.68 to 0.92. When evaluating with resubstitution the A(Z) ranged from 0.93 to 1.00.Computer-aided diagnosis has the potential to assist radiologists in the task of differentiating solitary pulmonary nodules and in the management of these patients.

To investigate the performance of observers with different levels of experience in distinguishing between benign and malignant solitary pulmonary nodules (SPN) on CT, and to determine the effects on interpretation of three different conditions: image data alone, the addition of clinical data, and the addition of output from a computer-aided diagnosis (CAD) system.28 thin-section CT datasets of SPNs with proven diagnoses (15 malignant and 13 benign) were used to measure observer performance. Readers were categorized according to their experience and read the cases in random order. For each case readers were asked to assign a level of confidence on a scale from 0.0-1.0 (0.0 benign, 1.0 malignant) for the diagnosis of the nodule. Each reader scored the cases based on review of image data alone (phase 1), then with limited clinical data (phase 2), and finally with CAD output (phase 3). To assess performance, multiple reader multiple case (MRMC) receiver operating characteristic (ROC) analysis was used.2 thoracic radiologists, 1 thoracic radiology fellow, 2 nonthoracic radiologists, and 3 radiology residents read the cases. The average area under the ROC curve for all readers (A(z)) at each stage was 0.68, 0.75, and 0.81, for image data alone, with clinical data, and with CAD output respectively. The difference in performance between phases (2 and 3) and (1 and 3) was significantly different (P = 0.018 and P = 0.020). However, the difference between phases (1 and 2) was not significantly different (P = 0.155).Diagnostic performance increased significantly with the addition of CAD output. With further validation CAD output may play a significant role in SPN management.

The problem-oriented electronic medical record has been investigated as an alternative to source-oriented organization of patient data. At the core of a problem-oriented view is the medical problem list. Maintenance of the medical problem list is often manual, making it highly user dependent. We detail the beginnings of an automated medical problem list generator based on ICD-9: given a set of ICD-9 codes associated with a patient record, the system maps the codes (and related data) to an anatomy-centric hierarchy. 1 million patient encounters from an outpatient setting were reviewed to generate a unique set of 7,890 ICD-9 codes. Natural language processing of the ICD-9 string descriptions identified 1,981 anatomical terms, which were subsequently mapped to one of 21 anatomical categories. The output of the medical problem list generator was then used to create a problem-oriented, gestalt view of a patient's medical record. Preliminary evaluation of the generator revealed 100% recall, but only 60% precision. This initial work has highlighted several issues in defining a medical problem list, including questions of granularity and performance trade-offs.

To study the agreement in treatment response classifications between unidimensional (1D), bidimensional (2D), and volumetric (3D) methods of measuring metastatic lung nodules on chest computed tomography (CT).Chest CT scans of 15 patients undergoing treatment for metastatic colorectal, renal cell, or breast carcinoma to the lungs were analyzed. CT images were acquired with 3 mm collimation and contiguous reconstruction. Two or three lung lesions were selected for each patient. Lesions were analyzed at baseline and two follow-up intervals of 1-4 months. 1D and 2D measurements were made with electronic calipers, while nodule volume was measured using a semiautomated segmentation system. Following the World Health Organization and RECIST (Response Evaluation Criteria in Solid Tumors) criteria, patients were categorized into four treatment response classifications. Volumetric criteria were used to classify response based on 3D measurements.Thirty-two lesions from 15 patients were analyzed. Because each patient had a baseline and two follow-up scans, this yielded 30 response classifications for each measurement technique. The 1D, 2D, and 3D measurements were concordant in 21 of 30 classifications. The 1D and 3D measurements were concordant in 29 of 30 classifications, while the 2D and 3D measurements were concordant in 23 of 30 classifications. Level of agreement among the three methods was measured using a kappa statistic (K). For 1D compared with 3D, K = 0.739 +/- 0.345 (visits 1, 2) and 0.273 +/- 0.323 (visits 2, 3). For 2D compared with 3D, K = 0.655 +/- 0.325 (visits 1, 2) and 0.200 +/- 0.208 (visits 2, 3). Agreement among the methods for round and ovoid nodules was also fair to poor.The three methods of tumor measurement show fair to poor agreement in treatment response classification. These findings have negative implications for the accuracy in which patients are classified under the World Health Organization or RECIST criteria and managed under cancer treatment protocols.

A streamlined process of care supported by technology and imaging may be effective in managing the overall healthcare process and costs. This study examined the effect of an imaging-based electronic process of care on costs and rates of hospitalization, emergency room (ER) visits, specialist diagnostic referrals, and patient satisfaction.A healthcare process was implemented for an employer group, highlighting improved patient access to primary care plus routine use of imaging and teleconsultation with diagnostic specialists. An electronic infrastructure supported patient access to physicians and communication among healthcare providers. The employer group, a self-insured company, manages a healthcare plan for its employees and their dependents: 4,072 employees were enrolled in the test group, and 7,639 in the control group. Outcome measures for expenses and frequency of hospitalizations, ER visits, traditional specialist referrals, primary care visits, and imaging utilization rates were measured using claims data over 1 year. Homogeneity tests of proportions were performed with a chi-square statistic, mean differences were tested by two-sample t-tests. Patient satisfaction with access to healthcare was gauged using results from an independent firm.Overall per member/per month costs post-implementation were lower in the enrolled population (126 dollars vs 160 dollars), even though occurrence of chronic/expensive diseases was higher in the enrolled group (18.8% vs 12.2%). Lower per member/per month costs were seen for inpatient (33.29 dollars vs 35.59 dollars); specialist referrals (21.36 dollars vs 26.84 dollars); and ER visits (3.68 dollars vs 5.22 dollars). Moreover, the utilization rate for hospital admissions, ER visits, and traditional specialist referrals were significantly lower in the enrolled group, although primary care and imaging utilization were higher. Comparison to similar employer groups showed that the company's costs were lower than national averages (119.24 dollars vs 146.32 dollars), indicating that the observed result was not attributable to normalization effects. Patient satisfaction with access to healthcare ranked in the top 21st percentile.A streamlined healthcare process supported by technology resulted in higher patient satisfaction and cost savings despite improved access to primary care and higher utilization of imaging.

Some institutions have adopted digital media such as CD ROMs to provide patients and referring physicians with results of radiological procedures. These systems require a computer to review the images and lack the supporting explanations and guidance for patients to properly understand the results. We developed a hybrid DVD encoding format that combines DICOM-compliant image storage format with video streams viewable on any consumer DVD players. The addition of the video material allows radiologists to provide explanations, disclaimers and guidance to the patients regarding the results of the study. The diagnostic report is also included on the DVD as a PDF file and as a set of video frames that can be viewed on a DVD player. The native high-resolution images are also included in DICOM format on the DVD and can be accessed by any workstation equipped with a DICOM viewer. The DVD that can be reviewed on any consumer DVD player overcomes the limitation of CD ROMS that require the use of a personal computer. The results of the radiological procedures become more accessible patients that could be reluctant or unable to use a computer. Also, live video clips add a more personalized note and allow radiologists to convey important messages to the patients. This is particularly useful for self-referred screening procedures where results should always be accompanied with education material and explanations of the findings.© (2003) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A knowledge-based system has been developed for segmenting computed tomography (CT) images. The modular architecture includes an anatomical model, image processing engine, inference engine and blackboard. The model contains a priori knowledge of size, shape, X-ray attenuation and relative position of anatomical structures. This knowledge is used to constrain low-level segmentation routines. Model-derived constraints and segmented image objects are both transformed into a common feature space and posted on the blackboard. The inference engine then matches image to model objects, based on the constraints. The transformation to feature space allows the knowledge and image data representations to be independent. Thus a high-level model can be used, with data being stored in a frame-based semantic network. Also, standard, low-level segmentation algorithms can be easily plugged-in to the system. This modularity allows for straightforward system extension and maintenance. We initially demonstrate an application to lung segmentation in thoracic CT, with subsequent extension of the knowledge-base to include tumors within the lung fields.

The purpose of this study was to determine the electronic requirements for supporting evidence-based radiology in today's medical environment.A software engineering technique, use case modeling, was performed for several clinical settings to determine the use of imaging and its role in evidence-based practice, with particular attention to issues relating to data access and the usage of clinical information. From this basic understanding, the analysis was extended to encompass evidence-based radiologic research and teaching.The analysis showed that a system supporting evidence-based radiology must (a) provide a single point of access to multiple clinical data sources so that patient data can be readily used and incorporated into comprehensive radiologic consults and (b) provide quick access to external evidence in the way of similar patient cases and published medical literature, thus supporting evidence-based practice.Information infrastructures that aim to support evidence-based radiology not only must address issues related to the integration of clinical data from heterogeneous databases, but must facilitate access and filtering of patient data in order to improve radiologic consultation.

To determine differences in coronary artery calcium detection, quantification, and reproducibility, as measured at electron-beam computed tomography (CT) and subsecond spiral CT with retrospective electrocardiogram gating in an asymptomatic adult population.Seventy subjects asymptomatic for coronary heart disease underwent both electron-beam CT and subsecond spiral CT. In all subjects, two images each were obtained with both scanners. Two experienced readers using three different algorithms scored each of the four scans: one score for the electron-beam CT images and two scores for the spiral CT images.With a 130-HU threshold for the quantification of calcium, there were no significant differences in interscan and interobserver variation in calcium scores between the electron-beam CT and spiral CT images. There was greater interobserver (P.001) and interscan (P.03) variation in scores when a 90-HU threshold was used for spiral CT images. With a 130-HU threshold, when calcium scores were used for clinical risk stratification, there was a significant difference between the results obtained with electron-beam CT and those obtained with spiral CT (P.05).Spiral CT has not yet proved to be a feasible alternative to electron-beam CT for coronary artery calcium quantification. There are systematic differences between calcium scores obtained with single-detector array subsecond spiral CT and those obtained with electron-beam CT.

The purpose of this work is to automatically detect lung nodules in CT images, and then relocalize them in follow-up scans so that changes in size or morphology can be measured. We propose a new method that uses a patient's baseline image data to assist in the segmentation of subsequent images. The system uses a generic, a priori model to analyze the baseline scan of a previously unseen patient and then a user confirms or rejects nodule candidates. For analysis of follow-up scans of that particular patient, a patient- specific model is derived that narrows the search in feature-space for previously labeled nodules based on the feature values measured on the baseline scan. Also, some previously identified false positives can be automatically relocalized and eliminated. In the baseline scans of eleven patients, a radiologist identified a total of 14 nodules. All 14 nodules were detected automatically by the system with an average of 11 false positives per case. In follow- up scans, using patient-specified models, 12 of the 14 nodules were relocalized. There was one previously unseen nodule, that was detected by the system, with 9 false positives per follow-up case.

The goal of this work is to determine whether malignant solitary pulmonary nodules (SPNs) can be discriminated form benign lesions based on quantitative features derived form CT images. The goal is to reach an accurate diagnosis quickly and without the need for additional imaging or more invasive tests. CT images were obtained from 54 patients identified as having an SPN. Of these, 24 SPN patients scanned by a spiral volumetric technique before and after the injection of an intravenous contrast agent. Diagnostic truth was determined using either pathology results from biopsy or surgical resection or from radiographic follow-up. All images were acquired using a volumetric CT scan protocol of 90% accuracy, area under ROC of >0.96 and FPF of .28 for TPF = 1.0. When the Logistic Regression classifier was used with 3D and contrast enhancement features, it achieved 92% accuracy, an area under ROC of .969 and a FPF of .063 for TPF = 1.0. When combinations of group features were used, the performance was not as good as individual groups listed above. The best was when enhancement and sphericity were used in a linear discriminant model, which achieved 87.5% accuracy and area under ROC of .820. The combination of contrast enhancement measures with other, morphological descriptors, hold promise for accurate classification of solitary pulmonary nodules imaged on CT. These results are preliminary as they are based on small numbers of cases and may be sensitive to the results of individual cases.

Prefetching methods have traditionally been used to restore archived images from picture archiving and communication systems to diagnostic imaging workstations prior to anticipated need, facilitating timely comparison of historical studies and patient management. The authors describe a problem-oriented prefetching scheme, detailing 1) a mechanism supporting selection of patients for prefetching via characterizations of clinical problems, using multiple data sources (picture archiving and communication systems, hospital information systems, and radiology information systems), classifying patients into cohorts on the basis of their medical conditions (e.g., lung cancer); and 2) prefetching of multimedia data (imaging, laboratory, and medical reports) from clinical databases to enable the viewing of an integrated patient record. Preliminary evaluation of the prefetching algorithm using classic information retrieval measures showed that the system had high recall (100 percent), correctly identifying and retrieving data for all patients belonging to a target cohort, but low precision (50 percent). A key finding during testing was that the recall of the system was increased through the use of multiple data sources (compared with one data source), because of better patient descriptors. Medical problems and patient cohorts were more specifically defined by combining information from heterogeneous databases.

Comprehensive cardiac assessment embraces virtually every imaging modality and includes information about coronary vascular anatomy as well as cardiac morphology, function, perfusion, metabolism, and tissue characterization. Through sophisticated computer processing and image analysis, newer imaging technologies such as computed tomography (CT), magnetic resonance (MR), MR spectroscopy, and positron emission tomography now provide quantitative information that may obviate more invasive angiographic assessment. Currently, no single imaging technology realizes all questions relating to cardiac form and function, and many of the technologies overlap in the content and quality of information they provide. This overview seeks to provide a broad perspective on current cardiac imaging, articulating the benefits of various technologies and their limitations.