Lung Cancer Screening Using Clinical Photon-Counting Detector Computed Tomography and Energy-Integrating-Detector Computed Tomography: A Prospective Patient Study.

OBJECTIVE: To evaluate the diagnostic quality of photon-counting detector (PCD) computed tomography (CT) in patients undergoing lung cancer screening compared with conventional energy-integrating detector (EID) CT in a prospective multireader study. MATERIALS: Patients undergoing lung cancer screening with conventional EID-CT were prospectively enrolled and scanned on a PCD-CT system using similar automatic exposure control settings and reconstruction kernels. Three thoracic radiologists blinded to CT system compared PCD-CT and EID-CT images and scored examinations using a 5-point Likert comparison score (-2 [left image is worse] to +2 [left image is better]) for artifacts, sharpness, image noise, diagnostic image quality, emphysema visualization, and lung nodule evaluation focusing on the border. Post hoc correction of Likert scores was performed such that they reflected PCD-CT performance in comparison to EID-CT. A nonreader radiologist measured objective image noise. RESULTS: Thirty-three patients (mean, 66.9 ± 5.6 years; 11 female; body mass index; 30.1 ± 5.1 kg/m 2 ) were enrolled. Mean volume CT dose index for PCD-CT was lower (0.61 ± 0.21 vs 0.73 ± 0.22; P < 0.001). Pooled reader results showed significant differences between imaging modalities for all comparative rankings ( P < 0.001), with PCD-CT favored for sharpness, image noise, image quality, and emphysema visualization and lung nodule border, but not artifacts. Photon-counting detector CT had significantly lower image noise (74.4 ± 10.5 HU vs 80.1 ± 8.6 HU; P = 0.048). CONCLUSIONS: Photon-counting detector CT with similar acquisition and reconstruction settings demonstrated improved image quality and less noise despite lower radiation dose, with improved ability to depict pulmonary emphysema and lung nodule borders compared with EID-CT at low-dose lung cancer CT screening.

Idiopathic Chronic Eosinophilic Pneumonia Evolving to Pulmonary Fibrosis: A Retrospective Analysis.

Background: Patients with idiopathic chronic eosinophilic pneumonia (ICEP) may have pulmonary fibrosis. Objectives: To investigate the predictors of pulmonary fibrosis in ICEP, to describe the timeline of pulmonary fibrosis after ICEP diagnosis, and to detail the radiologic pattern of fibrosis. Methods: A retrospective computer-assisted search was performed to identify patients with ICEP seen at Mayo Clinic in Rochester, Minnesota, from January 1, 1997, through September 1, 2019. Patients with follow-up chest computed tomography (CT) beyond 12 months after the ICEP diagnosis were included in the study. Demographic, clinical, radiologic, and histopathologic characteristics were analyzed. Proportional hazards regression was used to assess the predictors of pulmonary fibrosis. Results: We identified 62 patients (mean [SD] age at ICEP diagnosis, 60 [13] years; female sex, 37 [60%]). Cough (87%) and shortness of breath (85%) were the most common presenting symptoms. Of patients, 27 (44%) had a history of smoking and 27 (44%) had a history of asthma. During follow-up, 23 patients (37%) had CT evidence of pulmonary fibrosis, of whom 16 patients (70%) had a CT pattern inconsistent with usual interstitial pneumonia. In 29% of the patients, the CT evidence of pulmonary fibrosis developed within 2 years after ICEP. Age and male sex were predictors of pulmonary fibrosis. Of note, a history of asthma decreased the likelihood of pulmonary fibrosis. Conclusions: Development of pulmonary fibro-sis is not uncommon in patients with ICEP, especially older men, and is associated with increased risk of death.

Estimating the Clinical Impact of Photon-Counting-Detector CT in Diagnosing Usual Interstitial Pneumonia.

OBJECTIVE: The aim of this study was to evaluate the clinical impact of a higher spatial resolution, full field-of-view investigational photon-counting detector computed tomography (PCD-CT) on radiologist confidence in imaging findings and diagnosis of usual interstitial pneumonia (UIP) compared with conventional energy-integrating detector CT (EID-CT). MATERIALS AND METHODS: Patients suspected of interstitial lung disease were scanned on a PCD-CT system after informed consent and a clinically indicated EID-CT. In 2 sessions, 3 thoracic radiologists blinded to clinical history and scanner type evaluated CT images of the right and left lungs separately on EID- or PCD-CT, reviewing each lung once/session, rating confidence in imaging findings of reticulation, traction bronchiectasis, honeycombing, ground-glass opacities (GGOs), mosaic pattern, and lower lobe predominance (100-point scale: 0-33, likely absent; 34-66, indeterminate; 67-100, likely present). Radiologists also rated confidence for the probability of UIP (0-20, normal; 21-40, inconsistent with UIP; 41-60, indeterminate UIP; 61-81; probable UIP; 81-100, definite UIP) and graded image quality. Because a confidence scale of 50 represented completely equivocal findings, magnitude score (the absolute value of confidence scores from 50) was used for analysis (higher scores were more confident). Image noise was measured for each modality. The magnitude score was compared using linear mixed effects regression. The consistency of findings and diagnosis between 2 scanners were evaluated using McNemar test and weighted κ statistics, respectively. RESULTS: A total of 30 patients (mean age, 68.8 ± 11.0 years; M:F = 18:12) underwent conventional EID-CT (median CTDI vol , 7.88 mGy) and research PCD-CT (median CTDI vol , 6.49 mGy). The magnitude scores in PCD-CT were significantly higher than EID-CT for imaging findings of reticulation (40.7 vs 38.3; P = 0.023), GGO (34.4 vs 31.7; P = 0.019), and mosaic pattern (38.6 vs 35.9; P = 0.013), but not for other imaging findings ( P ≥ 0.130) or confidence in UIP (34.1 vs 22.2; P < 0.059). Magnitude score of probability of UIP in PCD-CT was significantly higher than EID-CT in one reader (26.0 vs 21.5; P = 0.009). Photon-counting detector CT demonstrated a decreased number of indeterminate GGO (17 vs 26), an increased number of unlikely GGO (74 vs 50), and an increased number of likely reticulations (140 vs 130) relative to EID-CT. Interobserver agreements among 3 readers for imaging findings and probability of UIP were similar between PCD-CT and EID-CT (intraclass coefficient: 0.507-0.818 vs 0.601-0.848). Photon-counting detector CT had higher scores in overall image quality (4.84 ± 0.38) than those in EID-CT (4.02 ± 0.40; P < 0.001) despite increased image noise (mean 85.5 vs 36.1 HU). CONCLUSIONS: Photon-counting detector CT provided better image quality and improved the reader confidence for presence or absence of imaging findings of reticulation, GGO, and mosaic pattern with idiosyncratic improvement in confidence in UIP presence.

Airway Amyloidosis: A Retrospective Analysis of 43 Patients.

BACKGROUND: Amyloidosis can involve any compartment in the thorax. We aimed to explore the clinical and radiologic presentation, treatment, and clinical course of airway amyloidosis. METHODS: A computer-assisted search was performed to identify patients who had biopsy-proven airway amyloidosis and were evaluated at Mayo Clinic in Rochester, MN, from January 1, 1997 through December 31, 2019. Demographic, clinical, and radiologic features along with clinical outcomes were analyzed. RESULTS: We identified 43 patients who had airway amyloidosis. Median age was 60 years (range: 33 to 91 y), and 58% were female. Shortness of breath (63% of patients) and cough (44%) were the most common presenting symptoms. Most patients (82%) had localized amyloidosis with light chain being the most common amyloid type; 63% had tracheobronchial amyloidosis, and 23% had tracheal and upper airway involvement. On computed tomography of the chest, the most common findings were airway wall thickening with nodularity (60% of patients), airway calcification (53%), and airway occlusion without collapse (47%). On bronchoscopy (33 patients), the extent of amyloid involvement was most commonly submucosal (n=15) or nodular (n=8). External beam radiotherapy was the most common treatment modality. Among the 30 patients who had follow-up at our institution, the prognosis appeared to depend on the extent of the disease and whether patients had localized or systemic amyloidosis. CONCLUSION: Computed tomography of the chest, bronchoscopy, and biopsy are needed to establish the diagnosis of airway amyloidosis, and systemic amyloidosis should be ruled out. Treatment of amyloidosis requires a multidisciplinary approach.

Interstitial Lung Disease in Giant Cell Arteritis: Review of 23 Patients.

BACKGROUND/OBJECTIVE: Giant cell arteritis (GCA) is a large-vessel vasculitis with systemic manifestations. A few case reports have described a possible association of GCA with interstitial lung disease (ILD). The primary aim of the present study was to describe the pattern, severity, and course of ILD in patients with GCA. METHODS: This medical records review study evaluated adult patients presenting to Mayo Clinic in Rochester, MN, from January 1, 1997, through December 31, 2018, who had the diagnoses of GCA and ILD. Clinical, laboratory, and radiologic data were analyzed. RESULTS: In total, 23 patients were in the study. Median (range) age was 78 (58-93) years, and 14 (61%) were women. Six patients (26%) had a cough at GCA diagnosis. At ILD diagnosis, 15 patients had respiratory symptoms, including dyspnea (n = 12, 52%), dry cough (n = 6, 26%), wheezing (n = 1, 4%), and chest pain (n = 1, 4%). On initial chest computed tomography, the most common pattern of ILD was probable usual interstitial pneumonia (n = 7, 30%), indeterminate for usual interstitial pneumonia (n = 5, 22%), and combined pulmonary fibrosis and emphysema (n = 3, 13%). Airway abnormalities were present in 10 patients: 6 with bronchial wall thickening, 2 with bronchiectasis, and 2 with both. At follow-up computed tomography, 8 patients had ILD progression. Three patients with cough improved after initiation of glucocorticoid therapy. CONCLUSIONS: Interstitial lung disease and airway abnormalities may be associated with GCA. Although cough may improve, ILD in some patients with GCA may progress despite immunosuppressive therapy.

A 70-Year-Old Man With Cough and Recurrent Respiratory Infections.

CASE PRESENTATION: A 70-year-old man was referred for evaluation of recurrent respiratory infections requiring antibiotics and chronic cough over 3 years. Two months prior to presentation, he started to develop blood-tinged sputum but not frank hemoptysis. He otherwise denied any fever, chills, night sweats, or weight loss. He had dyspnea during the respiratory infections but not otherwise. His medical history was significant for chronic rhinitis without sinusitis and a low serum IgM level. He was a never smoker and a farmer but otherwise had no significant or specific exposures or travel history. His family history was significant for alpha-1 antitrypsin deficiency in his mother.

Clinical, Radiologic, and Pathologic Characteristics of Pulmonary Hamartomas With Uncommon Presentation.

OBJECTIVES: To investigate the clinicopathologic and radiologic features of pulmonary hamartomas (PHs) with uncommon clinical presentation. METHODS: A retrospective clinicopathologic and radiologic review was performed for patients diagnosed (1999-2019) with multiple hamartomas, lesions arising adjacent to a coexisting pulmonary malignancy, and tumors with predominantly extrapulmonary localization. RESULTS: Of 979 patients diagnosed with PHs, 6 (0.6%) had multiple hamartomas, 4 (0.4%) had hamartomas adjacent to lung adenocarcinoma, and 2 (0.2%) had large mediastinal masses. Patients with multiple lesions had a median age of 65 years and mean tumor size of 0.9 cm; 1 patient had 3 hamartomas, and 5 patients had 2. Lesions next to adenocarcinomas had a mean size of 1.4 cm, and affected patients had a median age of 69 years. Predominantly mediastinal PHs, diagnosed in a 63-year-old woman and a 68-year-old man, measured 4.1 to 6 cm and were connected to the lung. All lesions were solid on imaging with absence of definitive fat or calcification, concerning for granuloma or malignancy. All cases had typical histology of PH, although one of the mediastinal tumors had an unusual amount of epithelial hyperplasia. CONCLUSIONS: PHs can be clinically and radiologically challenging to diagnose. Histopathologic examination of biopsies and resection specimens is diagnostically crucial in this setting.

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.

Assessing the inter-observer variability of Computer-Aided Nodule Assessment and Risk Yield (CANARY) to characterize lung adenocarcinomas.

Lung adenocarcinoma (ADC), the most common lung cancer type, is recognized increasingly as a disease spectrum. To guide individualized patient care, a non-invasive means of distinguishing indolent from aggressive ADC subtypes is needed urgently. Computer-Aided Nodule Assessment and Risk Yield (CANARY) is a novel computed tomography (CT) tool that characterizes early ADCs by detecting nine distinct CT voxel classes, representing a spectrum of lepidic to invasive growth, within an ADC. CANARY characterization has been shown to correlate with ADC histology and patient outcomes. This study evaluated the inter-observer variability of CANARY analysis. Three novice observers segmented and analyzed independently 95 biopsy-confirmed lung ADCs from Vanderbilt University Medical Center/Nashville Veterans Administration Tennessee Valley Healthcare system (VUMC/TVHS) and the Mayo Clinic (Mayo). Inter-observer variability was measured using intra-class correlation coefficient (ICC). The average ICC for all CANARY classes was 0.828 (95% CI 0.76, 0.895) for the VUMC/TVHS cohort, and 0.852 (95% CI 0.804, 0.901) for the Mayo cohort. The most invasive voxel classes had the highest ICC values. To determine whether nodule size influenced inter-observer variability, an additional cohort of 49 sub-centimeter nodules from Mayo were also segmented by three observers, with similar ICC results. Our study demonstrates that CANARY ADC classification between novice CANARY users has an acceptably low degree of variability, and supports the further development of CANARY for clinical application.

A virtual clinical trial using projection-based nodule insertion to determine radiologist reader performance in lung cancer screening CT.

Task-based image quality assessment using model observers is promising to provide an efficient, quantitative, and objective approach to CT dose optimization. Before this approach can be reliably used in practice, its correlation with radiologist performance for the same clinical task needs to be established. Determining human observer performance for a well-defined clinical task, however, has always been a challenge due to the tremendous amount of efforts needed to collect a large number of positive cases. To overcome this challenge, we developed an accurate projection-based insertion technique. In this study, we present a virtual clinical trial using this tool and a low-dose simulation tool to determine radiologist performance on lung-nodule detection as a function of radiation dose, nodule type, nodule size, and reconstruction methods. The lesion insertion and low-dose simulation tools together were demonstrated to provide flexibility to generate realistically-appearing clinical cases under well-defined conditions. The reader performance data obtained in this virtual clinical trial can be used as the basis to develop model observers for lung nodule detection, as well as for dose and protocol optimization in lung cancer screening CT.