Pulmonary light chain deposition disease: Case series and review of the literature.

Pulmonary light chain deposition disease is a rare entity characterized by immunoglobulin deposition within the lung parenchyma with pathologic features distinct from pulmonary amyloidosis. Here, the authors present the clinical presentation, associations, and radiologic features of pulmonary light chain deposition disease in a series of 4 patients as well as discuss the distinctions from amyloidosis. The present case series highlights the frequent presence of both cysts and nodules at CT. Clinically, lymphoma and/or autoimmune disease are often associated.

Imaging of Solid Pulmonary Nodules.

Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung cancer morbidity and mortality. Computed tomography (CT) remains the most widely used imaging examination for pulmonary nodule evaluation; however, other imaging modalities, such as PET/CT and MRI, are increasingly used for nodule characterization. Current advances in solid nodule imaging are largely due to developments in machine learning, including automated nodule segmentation and computer-aided detection. This review explores current multi-modality solid pulmonary nodule detection and characterization with discussion of radiomics and risk prediction models.

Evaluating Tissue Heterogeneity in the Radiologically Normal-Appearing Tissue in IPF Compared to Healthy Controls.

RATIONALE AND OBJECTIVES: Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease characterised by heterogeneously distributed fibrotic lesions. The inter- and intra-patient heterogeneity of the disease has meant that useful biomarkers of severity and progression have been elusive. Previous quantitative computed tomography (CT) based studies have focussed on characterising the pathological tissue. However, we hypothesised that the remaining lung tissue, which appears radiologically normal, may show important differences from controls in tissue characteristics. MATERIALS AND METHODS: Quantitative metrics were derived from CT scans in IPF patients (N = 20) and healthy controls with a similar age (N = 59). An automated quantitative software (CALIPER, Computer-Aided Lung Informatics for Pathology Evaluation and Rating) was used to classify tissue as normal-appearing, fibrosis, or low attenuation area. Densitometry metrics were calculated for all lung tissue and for only the normal-appearing tissue. Heterogeneity of lung tissue density was quantified as coefficient of variation and by quadtree. Associations between measured lung function and quantitative metrics were assessed and compared between the two cohorts. RESULTS: All metrics were significantly different between controls and IPF (p < 0.05), including when only the normal tissue was evaluated (p < 0.04). Density in the normal tissue was 14% higher in the IPF participants than controls (p < 0.001). The normal-appearing tissue in IPF had heterogeneity metrics that exhibited significant positive relationships with the percent predicted diffusion capacity for carbon monoxide. CONCLUSION: We provide quantitative assessment of IPF lung tissue characteristics compared to a healthy control group of similar age. Tissue that appears visually normal in IPF exhibits subtle but quantifiable differences that are associated with lung function and gas exchange.

Voxel-Wise Comparison of Co-Registered Quantitative CT and Hyperpolarised Gas Diffusion-Weighted MRI Measurements in IPF.

The patterns of idiopathic pulmonary fibrosis (IPF) lung disease that directly correspond to elevated hyperpolarised gas diffusion-weighted (DW) MRI metrics are currently unknown. This study aims to develop a spatial co-registration framework for a voxel-wise comparison of hyperpolarised gas DW-MRI and CALIPER quantitative CT patterns. Sixteen IPF patients underwent 3He DW-MRI and CT at baseline, and eleven patients had a 1-year follow-up DW-MRI. Six healthy volunteers underwent 129Xe DW-MRI at baseline only. Moreover, 3He DW-MRI was indirectly co-registered to CT via spatially aligned 3He ventilation and structural 1H MRI. A voxel-wise comparison of the overlapping 3He apparent diffusion coefficient (ADC) and mean acinar dimension (LmD) maps with CALIPER CT patterns was performed at baseline and after 1 year. The abnormal lung percentage classified with the LmD value, based on a healthy volunteer 129Xe LmD, and CALIPER was compared with a Bland-Altman analysis. The largest DW-MRI metrics were found in the regions classified as honeycombing, and longitudinal DW-MRI changes were observed in the baseline-classified reticular changes and ground-glass opacities regions. A mean bias of -15.3% (95% interval -56.8% to 26.2%) towards CALIPER was observed for the abnormal lung percentage. This suggests DW-MRI may detect microstructural changes in areas of the lung that are determined visibly and quantitatively normal by CT.

Bronchoscopic Lung Volume Reduction: Highlighting the Patient Selection Process.

Patients with advanced emphysema frequently experience severe dyspnea that is inadequately treated with medical therapy alone. Over the past 4 years, we have seen increased usage of bronchoscopic lung volume reduction (BLVR) with endobronchial valves. Success of the procedure is dependent on patient selection because it is not necessarily appropriate for all patients with severe emphysema. (Table 1) The purpose of this review is to highlight the selection process at a single institution. We also discuss the influence of this process on outcomes. Between March 1, 2019, and October 12, 2021, 2402 patients were referred to a dedicated chronic obstructive pulmonary disease clinic at Mayo Clinic - Rochester, whereas 161 patients were subsequently referred for multidisciplinary BLVR review. Of those patients, 53 (32.9%) were selected to receive valves and 35 (21.7%) ultimately underwent the procedure. The main reasons for exclusion included an incompatible quantitative computed tomography analysis (n=37, 34.3%), presence of pulmonary nodule or active malignancy (n=14, 13.0%), or need for completion of pulmonary rehabilitation (n=9, 8.3%). Full or partial (>70%) target lobe collapse was observed in 58.6% of patients who received valves. Those with collapse experienced statistically significant improvements in spirometric measures. Twelve patients experienced a pneumothorax (34.3%), with 10 patients requiring thoracostomy tube placement and prolonged hospitalization (median, 11 days; range, 4-39 days). Nineteen patients required a secondary procedure within the first year. The study highlights how a multidisciplinary approach to the BLVR selection process enables individualization of a complex procedure and enhances the exclusion of inappropriate candidates.

The Association between Exposures and Disease Characteristics in Familial Pulmonary Fibrosis.

Rationale: Heterogeneous characteristics are observed in familial pulmonary fibrosis (FPF), suggesting that nongenetic factors contribute to disease manifestations. Objectives: To determine the relationship between environmental exposures and disease characteristics of FPF, including the morphological characteristics on chest computed tomography (CT) scan, and timing of FPF symptom onset, lung transplantation, or death. Methods: Subjects with FPF with an exposure questionnaire and chest CT were selected from a prospective cohort at Vanderbilt. Disease characteristics were defined by lung parenchymal findings on chest CT associated with fibrotic hypersensitivity pneumonitis (fHP) or usual interstitial pneumonia (UIP) and by time from birth to symptom onset or a composite of lung transplantation or death. After assessing the potential for confounding by sex or smoking, adjusted logistic or Cox proportional hazards regression models identified exposures associated with fHP or UIP CT findings. Findings were validated in a cohort of patients with sporadic pulmonary fibrosis enrolled in the LTRC (Lung Tissue Research Consortium) study. Results: Among 159 subjects with FPF, 98 (61.6%) were males and 96 (60.4%) were ever-smokers. Males were less likely to have CT features of fHP, including mosaic attenuation (FPF: adjusted [for sex and smoking] odds ratio [aOR], 0.27; 95% confidence interval [CI], 0.09-0.76; P = 0.01; LTRC: aOR, 0.35; 95% CI, 0.21-0.61; P = 0.0002). Organic exposures, however, were not consistently associated with fHP features in either cohort. Smoking was a risk factor for honeycombing in both cohorts (FPF: aOR, 2.19; 95% CI, 1.12-4.28; P = 0.02; LTRC: aOR, 1.69; 95% CI, 1.22-2.33; P = 0.002). Rock dust exposure may also be associated with honeycombing, although the association was not statistically-significant when accounting for sex and smoking (FPF: aOR, 2.27; 95% CI, 0.997-5.15; P = 0.051; LTRC: aOR, 1.51; 95% CI, 0.97-2.33; P = 0.07). In the FPF cohort, ever-smokers experienced a shorter transplant-free survival (adjusted hazard ratio, 1.64; 95% CI, 1.07-2.52; P = 0.02), whereas sex was not associated with differential survival (male adjusted hazard ratio, 0.75; 95% CI, 0.50-1.14; P = 0.18). Conclusions: In FPF, smoking contributes to shortened transplant-free survival and development of honeycombing, a finding that is also likely applicable to sporadic pulmonary fibrosis. Females are more likely to manifest CT features of fHP (mosaic attenuation), a finding that was incompletely explained by sex differences in exposures. These findings may have implications for pulmonary fibrosis classification and management.

Multidisciplinary clinical guidance on trastuzumab deruxtecan (T-DXd)-related interstitial lung disease/pneumonitis-Focus on proactive monitoring, diagnosis, and management.

Trastuzumab deruxtecan (T-DXd; DS-8201) is an antibody-drug conjugate targeting human epidermal growth factor receptor 2. Interstitial lung disease (ILD)/pneumonitis is an adverse event associated with T-DXd; in most cases, it is low grade (grade ≤ 2) and can be treated effectively but may develop to be fatal in some instances. It is important to increase patient and provider understanding of T-DXd-related ILD/pneumonitis to improve patient outcomes. Drug-related ILD/pneumonitis is a diagnosis of exclusion; other possible causes of lung injury/imaging findings must be ruled out for an accurate diagnosis. Symptoms can be nonspecific, and identifying early symptoms is challenging; therefore, diagnosis is often delayed. We reviewed characteristics of patients who developed T-DXd-related ILD/pneumonitis and its patterns, produced multidisciplinary guidelines on diagnosis and management, and described areas for future investigation. Ongoing studies are collecting data on T-DXd-related ILD/pneumonitis to further our understanding of its clinical patterns and mechanisms. SEARCH STRATEGY AND SELECTION CRITERIA: References were identified based on the guidelines used by the authors in treating interstitial lung disease and pneumonitis. Searches of the authors' own files were also completed. A search of PubMed with the search terms (trastuzumab deruxtecan) AND (interstitial lung disease) AND (guidelines) was conducted on November 1, 2021, with no restrictions based on publication date, and the two articles yielded by the search were included.

Vessel-related structures predict UIP pathology in those with a non-IPF pattern on CT.

OBJECTIVES: To determine if a quantitative imaging variable (vessel-related structures [VRS]) could identify subjects with a non-IPF diagnosis CT pattern who were highly likely to have UIP histologically. METHODS: Subjects with a multidisciplinary diagnosis of interstitial lung disease including surgical lung biopsy and chest CT within 1 year of each other were included in the study. Non-contrast CT scans were analyzed using the Computer-Aided Lung Informatics for Pathology Evaluation and Rating (CALIPER) program, which quantifies the amount of various abnormal CT patterns on chest CT. Quantitative data were analyzed relative to pathological diagnosis as well as the qualitative CT pattern. RESULTS: CALIPER-derived volumes of reticulation (p = 0.012), honeycombing (p = 0.017), and VRS (p < 0.001) were associated with a UIP pattern on pathology on univariate analysis but only VRS was associated with a UIP pathology on multivariable analysis (p = 0.013). Using a VRS cut-off of 173 cm3, the sensitivity and specificity for pathological UIP were similar to those for standard qualitative CT assessment (55.9% and 80.4% compared to 60.6% and 80.4%, respectively). VRS differentiated pathological UIP cases in those with a non-IPF diagnosis CT category (p < 0.001) but not in other qualitative CT patterns (typical UIP, probable UIP, and indeterminate for UIP). The rate of pathological UIP in those with VRS greater than 173 cm3 (84.2%) was nearly identical to those who had a qualitative CT pattern of probable UIP (88.9%). CONCLUSIONS: VRS may be an adjunct to CT in predicting pathology in patients with interstitial lung disease. KEY POINTS: • Volume of vessel-related structures (VRS) was associated with usual interstitial pneumonia (UIP) on pathology. • This differentiation arose from those with CT scans with a non-IPF diagnosis imaging pattern. • Higher VRS has similar diagnostic ramifications for UIP as probable UIP, transitively suggesting in patients with high VRS, pathology may be obviated.

Validation of the BRODERS classifier (Benign versus aggRessive nODule Evaluation using Radiomic Stratification), a novel HRCT-based radiomic classifier for indeterminate pulmonary nodules.

INTRODUCTION: Implementation of low-dose chest computed tomography (CT) lung cancer screening and the ever-increasing use of cross-sectional imaging are resulting in the identification of many screen- and incidentally detected indeterminate pulmonary nodules. While the management of nodules with low or high pre-test probability of malignancy is relatively straightforward, those with intermediate pre-test probability commonly require advanced imaging or biopsy. Noninvasive risk stratification tools are highly desirable. METHODS: We previously developed the BRODERS classifier (Benign versus aggRessive nODule Evaluation using Radiomic Stratification), a conventional predictive radiomic model based on eight imaging features capturing nodule location, shape, size, texture and surface characteristics. Herein we report its external validation using a dataset of incidentally identified lung nodules (Vanderbilt University Lung Nodule Registry) in comparison to the Brock model. Area under the curve (AUC), as well as sensitivity, specificity, negative and positive predictive values were calculated. RESULTS: For the entire Vanderbilt validation set (n=170, 54% malignant), the AUC was 0.87 (95% CI 0.81-0.92) for the Brock model and 0.90 (95% CI 0.85-0.94) for the BRODERS model. Using the optimal cut-off determined by Youden's index, the sensitivity was 92.3%, the specificity was 62.0%, the positive (PPV) and negative predictive values (NPV) were 73.7% and 87.5%, respectively. For nodules with intermediate pre-test probability of malignancy, Brock score of 5-65% (n=97), the sensitivity and specificity were 94% and 46%, respectively, the PPV was 78.4% and the NPV was 79.2%. CONCLUSIONS: The BRODERS radiomic predictive model performs well on an independent dataset and may facilitate the management of indeterminate pulmonary nodules.

Putting artificial intelligence (AI) on the spot: machine learning evaluation of pulmonary nodules.

Lung cancer remains the leading cause of cancer related death world-wide despite advances in treatment. This largely relates to the fact that many of these patients already have advanced diseases at the time of initial diagnosis. As most lung cancers present as nodules initially, an accurate classification of pulmonary nodules as early lung cancers is critical to reducing lung cancer morbidity and mortality. There have been significant recent advances in artificial intelligence (AI) for lung nodule evaluation. Deep learning (DL) and convolutional neural networks (CNNs) have shown promising results in pulmonary nodule detection and have also excelled in segmentation and classification of pulmonary nodules. This review aims to provide an overview of progress that has been made in AI recently for pulmonary nodule detection and characterization with the ultimate goal of lung cancer prediction and classification while outlining some of the pitfalls and challenges that remain to bring such advancements to routine clinical use.

Implications of the updated Lung CT Screening Reporting and Data System (Lung-RADS version 1.1) for lung cancer screening.

Lung cancer remains the leading cause of cancer death in the United States. Screening with low-dose computed tomography (LDCT) has been proven to aid in early detection of lung cancer and reduce disease specific mortality. In 2014, the American College of Radiology (ACR) released version 1.0 of the Lung CT Screening Reporting and Data System (Lung-RADS) as a quality tool to standardize the reporting of lung cancer screening LDCT. In 2019, 5 years after the implementation of Lung-RADS version 1.0 the ACR released the updated Lung-RADS version 1.1 which incorporates initial experience with lung cancer screening. In this review, we outline the implications of the changes and additions in Lung-RADS version 1.1 and examine relevant literature for many of the updates. We also highlight several challenges and opportunities as Lung-RADS version 1.1 is implemented in lung cancer screening programs.

Do we need to see to believe?-radiomics for lung nodule classification and lung cancer risk stratification.

Despite multiple recent advances, the diagnosis and management of lung cancer remain challenging and it continues to be the deadliest malignancy. In 2011, the National Lung Screening Trial (NLST) reported 20% reduction in lung cancer related mortality using annual low dose chest computed tomography (CT). These results led to the approval and nationwide establishment of lung cancer CT-based lung cancer screening programs. These findings have been further validated by the recently published Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) and Multicentric Italian Lung Detection (MILD) trials, the latter showing benefit of screening even beyond the 5 years. However, the implementation of lung cancer screening has been impeded by several challenges, including the differentiation between benign and malignant nodules, the large number of false positive studies and the detection of indolent, potentially clinically insignificant lung cancers (overdiagnosis). Hence, the development of non-invasive strategies to accurately classify and risk stratify screen-detected pulmonary nodules in order to individualize clinical management remains a high priority area of research. Radiomics is a recently coined term which refers to the process of imaging feature extraction and quantitative analysis of clinical diagnostic images to characterize the nodule phenotype beyond what is possible with conventional radiologist assessment. Even though it is still in early phase, several studies have already demonstrated that radiomics approaches are potentially useful for lung nodule classification, risk stratification, individualized management and prediction of overall prognosis. The goal of this review is to summarize the current literature regarding the radiomics of screen-detected lung nodules, highlight potential challenges and discuss its clinical application along with future goals and challenges.

Cicatricial organizing pneumonia: a clinicopathologic and radiologic study on a cohort diagnosed by surgical lung biopsy at a single institution.

Cicatricial organizing pneumonia (CiOP) refers to intraluminal collagen deposition in a background of otherwise classic appearing organizing pneumonia (OP), sometimes with formation of peculiar fibrous nodules or densely fibrotic linear bands. Dendriform ossification has been also described in CiOP cases. This study is to evaluate the clinicopathologic and radiologic characteristics of CiOP identified in a cohort of OP cases diagnosed by surgical lung biopsy at a single institution. Electronic search was performed to find surgical lung biopsy cases with OP as the main histopathologic diagnosis during a 9-year period (2005-2013). The presence of mature collagen deposition in intraluminal plugs of OP (Masson bodies), linear fibrous bands, and ossification in association with OP was evaluated. Pertinent clinical information was obtained from medical records, and available chest computed tomography (CT) scans were reviewed by a chest radiologist. A total of 56 cases met the study criteria. Thirty-two of 56 cases (57.1%) showed at least 10% of cicatricial element within Masson bodies, 9 of which revealed cicatricial elements comprising 50% or higher proportion of OP. All 9 cases with CiOP as the major component (≥50%) revealed some areas of linear fibrous bands. Five of these 9 cases had intraluminal ossification, with features suggestive of dendriform ossification. Twenty of 32 cases with the cicatricial component had postoperative follow-up CT scans ranging from 0.4 to 171 months (median = 44) after the biopsy; 18 of these 20 cases showed stable finding or resolution of radiologic densities. Six of 9 patients with CiOP with major cicatricial change (≥50%) were alive and well at the time of clinical follow-up (median = 47 months; range = 12-125). In summary, minor cicatricial changes involving Masson bodies were seen in more than half of our OP cases, and patients with CiOP seem to follow an indolent and favorable course on radiologic and clinical follow-up, even in those with major cicatricial changes (≥50%) that were often accompanied by linear fibrous bands and/or intraluminal ossification.

Automated Computed Tomography analysis in the assessment of Idiopathic Pulmonary Fibrosis severity and progression.

PURPOSE: To investigate the role of a quantitative analysis software (CALIPER) in identifying HRCT thresholds predicting IPF patients' survival and lung function decline and its role in detecting changes of HRCT abnormalities related to treatment and their correlation with Forced Vital Capacity (FVC). METHODS: This retrospective study included 105 patients with a multidisciplinary diagnosis of IPF for whom one HRCT at baseline and concomitant FVC were available. HRCTs were evaluated with CALIPER and the correlation between FVC and radiological features were assessed. Radiological thresholds for survival prediction and functional decline were calculated for all patients. Fifty-nine patients with at least 2 serial HRCTs were classified into two groups based on treatment. For patients for whom a FVC within 3 months of the HRCT was available (n = 44), the correlation of radiological and clinical progression was evaluated. RESULTS: The correlation between FVC and CALIPER-derived features at baseline was significant and strong. A baseline CALIPER-derived interstitial lung disease (ILD%) extent higher than 20 % and pulmonary vascular related structures (PVRS%) score greater than 5 % defined a worse prognosis. A significant progression of CALIPER-derived features in all patients was found with a faster increase in untreated patients. ILD% and PVRS% changes during follow-up demonstrated strong correlations with FVC changes. CONCLUSIONS: CALIPER quantification of fibrosis and vascular involvement could distinguish disease progression in treated versus untreated patients and predict the survival. The changes in CALIPER-derived variables over time were significantly correlated to changes in FVC.

Stratification of long-term outcome in stable idiopathic pulmonary fibrosis by combining longitudinal computed tomography and forced vital capacity.

OBJECTIVES: To test HRCT with either visual or quantitative analysis in both short-term and long-term follow-up of stable IPF against long-term (transplant-free) survival, beyond 2 years of disease stability. METHODS: Fifty-eight IPF patients had FVC measurements and HRCTs at baseline (HRCT0), 10-14 months (HRCT1) and 22-26 months (HRCT2). Visual scoring, CALIPER quantitative analysis of HRCT measures, and their deltas were evaluated against combined all-cause mortality and lung transplantation by adjusted Cox proportional hazard models at each time interval. RESULTS: At HRCT1, a ≥ 20% relative increase in CALIPER-total lung fibrosis yielded the highest radiological association with outcome (C-statistic 0.62). Moreover, the model combining FVC% drop ≥ 10% and ≥ 20% relative increase of CALIPER-total lung fibrosis improved the stratification of outcome (C-statistic 0.69, high-risk category HR 12.1; landmark analysis at HRCT1 C-statistic 0.66, HR 14.9 and at HRCT2 C-statistic 0.61, HR 21.8). Likewise, at HRCT2, the model combining FVC% decrease trend and ≥ 20% relative increase of CALIPER-pulmonary vessel-related volume (VRS) improved the stratification of outcome (C-statistic 0.65, HR 11.0; landmark analysis at HRCT1 C-statistic 0.62, HR 13.8 and at HRCT2 C-statistic 0.58, HR 12.6). A less robust stratification of outcome distinction was also demonstrated with the categorical visual scoring of disease change. CONCLUSIONS: Annual combined CALIPER -FVC changes showed the greatest stratification of long-term outcome in stable IPF patients, beyond 2 years. KEY POINTS: • Longitudinal high-resolution computed tomography (HRCT) data is more helpful than baseline HRCT alone for stratification of long-term outcome in IPF. • HRCT changes by visual or quantitative analysis can be added with benefit to the current spirometric reference standard to improve stratification of long-term outcome in IPF. • HRCT follow-up at 12-14 months is more helpful than HRCT follow-up at 23-26 months in clinically stable subjects with IPF.

Pulmonary Low Attenuation Areas on CT in ANCA-associated Vasculitis: A quantitative and semi-quantitative analysis correlated with pulmonary function testing for obstructive airway disease.

OBJECTIVE: A subset of ANCA-associated vasculitis (AAV) patients are known to manifest obstructive airway disease. Using low attenuation areas (LAA) in the lung on HRCT as an imaging marker for obstructive airway disease, we analyze HRCT studies in AAV patients compared to a matched non-AAV group using visual semi-quantitative and automated quantitative analysis for presence and severity of LAA. Furthermore, HRCT and pulmonary function testing are compared to assess agreement between tests for airway obstruction. MATERIALS AND METHODS: 100 randomly selected AAV patients with HRCT were compared to 100 best-fit matched control subjects. HRCT cases were visually assessed for LAA, along with additional pulmonary patterns. Automated quantitative software analyzed images for texture features and volume of attenuation values of -950 HU or less (e-950). Evidence of obstructive airway disease established by pulmonary function testing, when available, was compared to HRCT analysis for LAA. Additional clinical information, diagnostic testing and mortality data were also compared. RESULTS: Both study groups were comprised of 57 females and 43 males with 35 smokers averaging 10.7 pk/yrs, with average age for the AAV and control groups being 59.4 yrs and 61.9 yrs, respectively. Visually, 46 AAV patients demonstrated LAA on HRCT compared to 25 control patients (p=0.0017) with the difference in LAA presence entirely within the non-smoking subgroup (25 to 3, respectively, p=<0.0001). Quantitatively, greater than 5% e-950 demonstrated similar significant differences between AAV (36/100) and controls (19/100) (p=0.0065), predominantly in non-smokers (p=0.006). Obstruction on PFTs was significantly increased in AAV (p=0.002) with moderate agreement of obstructive disease with visual LAA on CT (Kappa 0.509). Of the obstructive disease metrics, visual LAA on CT correlated best with mortality (p=0.0085). CONCLUSION: Visual LAA and automated quantitative analysis for e-950 on HRCT demonstrate statistically significant increases in AAV patients compared to age, gender and smoking matched controls, with differences primarily seen in the non-smoking subset. AAV revealed statistically significant greater obstructive pulmonary disease on PFTs (Sarcoidosis Vasc Diffuse Lung Dis 2020; 37 (4): e2020016).

Radio-Frequency Identification Specimen Tracking to Improve Quality in Anatomic Pathology.

CONTEXT.­: Preanalytic errors, including specimen labeling errors and specimen loss, occur frequently during specimen collection, transit, and accessioning. Radio-frequency identification tags can decrease specimen identification and tracking errors through continuous and automated tracking of specimens. OBJECTIVE.­: To implement a specimen tracking infrastructure to reduce preanalytic errors (specimen mislabeling or loss) between specimen collection and laboratory accessioning. Specific goals were to decrease preanalytic errors by at least 70% and to simultaneously decrease employee effort dedicated to resolving preanalytic errors or investigating lost specimens. DESIGN.­: A radio-frequency identification specimen-tracking system was developed. Major features included integral radio-frequency identification labels (radio-frequency identification tags and traditional bar codes in a single printed label) printed by point-of-care printers in collection suites; dispersed radio-frequency identification readers at major transit points; and systems integration of the electronic health record, laboratory information system, and radio-frequency identification tracking system to allow for computerized physician order entry driven label generation, specimen transit time tracking, interval-based alarms, and automated accessioning. RESULTS.­: In the 6-month postimplementation period, 6 mislabeling events occurred in collection areas using the radio-frequency identification system, compared with 24 events in the 6-month preimplementation period (75% decrease; P = .001). In addition, the system led to the timely recovery of 3 lost specimens. Labeling expenses were decreased substantially in the transition from high-frequency to ultrahigh frequency radio-frequency identification tags. CONCLUSIONS.­: Radio-frequency identification specimen tracking prevented several potential specimen-loss events, decreased specimen recovery time, and decreased specimen labeling errors. Increases in labeling/tracking expenses for the system were more than offset by time savings and loss avoidance through error mitigation.

Quantitative CT Analysis of Diffuse Lung Disease.

Quantitative analysis of thin-section CT of the chest has a growing role in the clinical evaluation and management of diffuse lung diseases. This heterogeneous group includes diseases with markedly different prognoses and treatment options. Quantitative tools can assist in both accurate diagnosis and longitudinal management by improving characterization and quantification of disease and increasing the reproducibility of disease severity assessment. Furthermore, a quantitative index of disease severity may serve as a useful tool or surrogate endpoint in evaluating treatment efficacy. The authors explore the role of quantitative imaging tools in the evaluation and management of diffuse lung diseases. Lung parenchymal features can be classified with threshold, histogram, morphologic, and texture-analysis-based methods. Quantitative CT analysis has been applied in obstructive, infiltrative, and restrictive pulmonary diseases including emphysema, cystic fibrosis, asthma, idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, connective tissue-related interstitial lung disease, and combined pulmonary fibrosis and emphysema. Some challenges limiting the development and practical application of current quantitative analysis tools include the quality of training data, lack of standard criteria to validate the accuracy of the results, and lack of real-world assessments of the impact on outcomes. Artifacts such as patient motion or metallic beam hardening, variation in inspiratory effort, differences in image acquisition and reconstruction techniques, or inaccurate preprocessing steps such as segmentation of anatomic structures may lead to inaccurate classification. Despite these challenges, as new techniques emerge, quantitative analysis is developing into a viable tool to supplement the traditional visual assessment of diffuse lung diseases and to provide decision support regarding diagnosis, prognosis, and longitudinal evaluation of disease. ©RSNA, 2019.