Osteophyte induced lung fibrosis prevalence and osteophyte qualities predicting disease

OBJECTIVE

To determine the prevalence of osteophyte induced lung fibrosis (OIF) and its relationship to osteophyte size, location, and surrounding fat.

METHODS

94 CT scans of the chest were reviewed, size of the largest osteophyte and the presence of fibrosis were recorded.

RESULTS

Presence of fibrosis was higher among patient with large (>10 mm) osteophytes compared to those with small (1-10mm) osteophytes. Age and presence of periosteophyte fat were significantly associated with presence of fibrosis.

CONCLUSIONS

As the size of an osteophyte increases, there is a greater likelihood of lung fibrosis. Subpleural fat protects the lung from OIF.

2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans: A report of the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology

The Society of Cardiovascular Computed Tomography (SCCT) and the Society of Thoracic Radiology (STR) have jointly produced this document. Experts in this subject have been selected from both organizations to examine subject-specific data and write this guideline in partnership. A formal literature review, weighing the strength of evidence has been performed. When available, information from studies on cost was considered. Computed tomography (CT) acquisition, CAC scoring methodologies and clinical outcomes are the primary basis for the recommendations in this guideline. This guideline is intended to assist healthcare providers in clinical decision making. The recommendations reflect a consensus after a thorough review of the best available current scientific evidence and practice patterns of experts in the field and are intended to improve patient care while acknowledging that situations arise where additional information may be needed to better inform patient care.

The International Association for the Study of Lung Cancer Consensus Statement on Optimizing Management of EGFR Mutation-Positive Non-Small Cell Lung Cancer: Status in 2016

Mutations in the epidermal growth factor receptor gene (EGFR) represent one of the most frequent "actionable" alterations in non-small cell lung cancer (NSCLC). Typified by high response rates to targeted therapies, EGFR tyrosine kinase inhibitors (TKIs) are now established first-line treatment options and have transformed the treatment paradigm for NSCLC. With the recent breakthrough designation and approval of the third-generation EGFR TKI osimertinib, available systemic and local treatment options have expanded, requiring new clinical algorithms that take into account individual patient molecular and clinical profiles. In this International Association for the Study of Lung Cancer commissioned consensus statement, key pathologic, diagnostic, and therapeutic considerations, such as optimal choice of EGFR TKI and management of brain metastasis, are discussed. In addition, recommendations are made for clinical guidelines and research priorities, such as the role of repeat biopsies and use of circulating free DNA for molecular studies. With the rapid pace of progress in treating EGFR-mutant NSCLC, this statement provides a state-of-the-art review of the contemporary issues in managing this unique subgroup of patients.

Low-Dose CT Screening for Lung Cancer: Computer-aided Detection of Missed Lung Cancers

Purpose To update information regarding the usefulness of computer-aided detection (CAD) systems with a focus on the most critical category, that of missed cancers at earlier imaging, for cancers that manifest as a solid nodule. Materials and Methods By using a HIPAA-compliant institutional review board-approved protocol where informed consent was obtained, 50 lung cancers that manifested as a solid nodule on computed tomographic (CT) scans in annual rounds of screening (time 1) were retrospectively identified that could, in retrospect, be identified on the previous CT scans (time 0). Four CAD systems were compared, which were referred to as CAD 1, CAD 2, CAD 3, and CAD 4. The total number of accepted CAD-system-detected nodules at time 0 was determined by consensus of two radiologists and the number of CAD-system-detected nodules that were rejected by the radiologists was also documented. Results At time 0 when all the cancers had been missed, CAD system detection rates for the cancers were 56%, 70%, 68%, and 60% (κ = 0.45) for CAD systems 1, 2, 3, and 4, respectively. At time 1, the rates were 74%, 82%, 82%, and 78% (κ = 0.32), respectively. The average diameter of the 50 cancers at time 0 and time 1 was 4.8 mm and 11.4 mm, respectively. The number of CAD-system-detected nodules that were rejected per CT scan for CAD systems 1-4 at time 0 was 7.4, 1.7, 0.6, and 4.5 respectively. Conclusion CAD systems detected up to 70% of lung cancers that were not detected by the radiologist but failed to detect about 20% of the lung cancers when they were identified by the radiologist, which suggests that CAD may be useful in the role of second reader. (©) RSNA, 2016.

Fine-needle aspiration of small pulmonary nodules yields material for reliable molecular analysis of adenocarcinomas

INTRODUCTION

Early molecular characterization with Kirsten rat sarcoma factor, epidermal growth factor, and anaplastic lymphoma kinase are critical to manage pulmonary adenocarcinoma. Fine-needle aspiration (FNA) of lesions <2 cm are routine in our institution and are used in molecular analysis. We report our experience.

MATERIALS AND METHODS

We searched our databank for primary pulmonary adenocarcinomas diagnosed by FNA between January 2009 and April 2013. Size of the lesion aspirated, molecular results, and sample source (FNA versus surgical specimen) were recorded. We compared the frequency of mutations identified by FNA versus surgical specimens and the frequency of mutations in lesions by size (<1 cm, 1-2 cm, >2 cm).

RESULTS

We identified 397 primary pulmonary adenocarcinomas. Molecular studies were requested by the clinician in 89 (22%) of primary adenocarcinomas. FNAs were used in 55 cases; 51 (93%) yielded sufficient material for molecular studies; surgical tissue were used in 34 cases; 33 (97%) yielded sufficient material for molecular studies. The insufficient specimens came from 2 FNAs of 0.6 cm nodules, an FNA of a 2 cm nodule, and a core biopsy.

CONCLUSIONS

FNA was adequate for molecular analysis of small nodules. In nodules greater than 0.6 cm, the adequacy is comparable to surgical tissue. There was no statistically significant change in mutation rate by size (53%-58%). Importantly, FNA of small lesions for cytological diagnosis and molecular analysis is encouraged by our data and experience in order to provide early treatment.

Survival after Sublobar Resection for Early-Stage Lung Cancer: Methodological Obstacles in Comparing the Efficacy to Lobectomy

INTRODUCTION

Surgery is the treatment of choice for early-stage lung cancer (LC). Although lobectomy (L) is the historic standard treatment, the issue of whether long-term outcomes of sublobar resection (SL) are comparable is still under debate. The objective of this study was to perform a review of the literature on 5-year survival rates after SL compared to L for patients with early-stage LC.

METHODS

A priori inclusion criteria were as follows: (1) observational studies, (2) L compared to SL for early-stage LC, (3) radiographic staging by computed tomography scan, and (4) 5-year survival reported. A Medline search through January 2015 resulted in 31 studies representing 23 distinct datasets. The absolute difference in 5-year survival was calculated and plotted for each study.

RESULTS

L was performed in 4564 patients and SL in 2287 patients. Of 19 studies reporting the reason for SL, 11 indicated that SL was performed because of comorbidities or impaired cardiopulmonary function. Four studies showed no difference in 5-year survival, 13 favored L, and six favored SL. One propensity score study favored L and the other favored SL. Of 20 studies reporting recurrence rate, 11 favored L and nine favored SL.

CONCLUSIONS

Studies comparing 5-year survival rates of SL to L are sufficiently heterogeneous to prevent carrying out traditional meta-analysis. SL survival is often similar to L when adjustments are made for age, comorbidities, or impaired cardiopulmonary function. New approaches are needed for the comparison of L to SL.

Lung Cancer Workshop XI: Tobacco-Induced Disease: Advances in Policy, Early Detection and Management

The Prevent Cancer Foundation Lung Cancer Workshop XI: Tobacco-Induced Disease: Advances in Policy, Early Detection and Management was held in New York, NY on May 16 and 17, 2014. The two goals of the Workshop were to define strategies to drive innovation in precompetitive quantitative research on the use of imaging to assess new therapies for management of early lung cancer and to discuss a process to implement a national program to provide high quality computed tomography imaging for lung cancer and other tobacco-induced disease. With the central importance of computed tomography imaging for both early detection and volumetric lung cancer assessment, strategic issues around the development of imaging and ensuring its quality are critical to ensure continued progress against this most lethal cancer.

Local noise estimation in low-dose chest CT images

PURPOSE

Image noise in computed tomography (CT) images may have significant local variation due to tissue properties, dose, and location of the X-ray source. We developed and tested an automated tissue-based estimator method for estimating local noise in CT images.

METHOD

An automated TBE method for estimating the local noise in CT image in 3 steps was developed: (1) Partition the image into homogeneous and transition regions, (2) For each pixel in the homogeneous regions, compute the standard deviation in a 15 x 15 x 1 voxel local region using only pixels from the same homogeneous region, and (3) Interpolate the noise estimate from the homogeneous regions in the transition regions. Noise-aware fat segmentation was implemented. Experiments were conducted on the anthropomorphic phantom and in vivo low-dose chest CT scans to validate the TBE, characterize the magnitude of local noise variation, and determine the sensitivity of noise estimates to the size of the region in which noise is computed. The TBE was tested on all scans from the Early Lung Cancer Action Program public database. The TBE was evaluated quantitatively on the phantom data and qualitatively on the in vivo data.

RESULTS

The results show that noise can vary locally by over 200 Hounsfield units on low-dose in vivo chest CT scans and that the TBE can characterize these noise variations within 5 %. The new fat segmentation algorithm successfully improved segmentation on all 50 scans tested.

CONCLUSION

The TBE provides a means to estimate noise for image quality monitoring, optimization of denoising algorithms, and improvement of segmentation algorithms. The TBE was shown to accurately characterize the large local noise variations that occur due to changes in material, dose, and X-ray source location.

Radiologic implications of the 2011 classification of adenocarcinoma of the lung

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.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans

PURPOSE

The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.

METHODS

Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.

RESULTS

The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "nodule > or =3 mm" by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.

CONCLUSIONS

The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.

A public image database to support research in computer aided diagnosis

The Public Lung Database to address drug response (PLD) has been developed to support research in computer aided diagnosis (CAD). Originally established for applications involving the characterization of pulmonary nodules, the PLD has been augmented to provide initial datasets for CAD research of other diseases. In general, the best performance for a CAD system is achieved when it is trained with a large amount of well documented data. Such training databases are very expensive to create and their lack of general availability limits the targets that can be considered for CAD applications and hampers development of the CAD field. The approach taken with the PLD has been to make available small datasets together with both manual and automated documentation. Furthermore, datasets with special properties are provided either to span the range of task complexity or to provide small change repeat images for direct calibration and evaluation of CAD systems. This resource offers a starting point for other research groups wishing to pursue CAD research in new directions. It also provides an on-line reference for better defining the issues relating to specific CAD tasks.