Lucio Calandriello

Interobserver agreement for the ATS/ERS/JRS/ALAT criteria for a UIP pattern on CT

Objectives To establish the level of observer variation for the current ATS/ERS/JRS/ALAT criteria for a diagnosis of usual interstitial pneumonia (UIP) on CT among a large group of thoracic radiologists of varying levels of experience. Materials and methods 112 observers (96 of whom were thoracic radiologists) categorised CTs of 150 consecutive patients with fibrotic lung disease using the ATS/ERS/JRS/ALAT CT criteria for a UIP pattern (3 categories—UIP, possibly UIP and inconsistent with UIP). The presence of honeycombing, traction bronchiectasis and emphysema was also scored using a 3-point scale (definitely present, possibly present, absent). Observer agreement for the UIP categorisation and for the 3 CT patterns in the entire observer group and in subgroups stratified by observer experience, were evaluated. Results Interobserver agreement across the diagnosis category scores among the 112 observers was moderate, ranging from 0.48 (IQR 0.18) for general radiologists to 0.52 (IQR 0.20) for thoracic radiologists of 10–20 years’ experience. A binary score for UIP versus possible or inconsistent with UIP was examined. Observer agreement for this binary score was only moderate. No significant differences in agreement levels were identified when the CTs were stratified according to multidisciplinary team (MDT) diagnosis or patient age or when observers were categorised according to experience. Observer agreement for each of honeycombing, traction bronchiectasis and emphysema were 0.59±0.12, 0.42±0.15 and 0.43±0.18, respectively. Conclusions Interobserver agreement for the current ATS/ERS/JRS/ALAT CT criteria for UIP is only moderate among thoracic radiologists, irrespective of their experience, and did not vary with patient age or the MDT diagnosis.

An integrated clinicoradiological staging system for pulmonary sarcoidosis: a case-cohort study

BACKGROUND Mortality in pulmonary sarcoidosis is highly variable and a reliable prognostic algorithm for disease staging and for guiding management decisions is needed. The objective of this study is to derive and test a staging system for determining prognosis in pulmonary sarcoidosis. METHODS We identified the prognostic value of high-resolution computed tomography (HRCT) patterns and pulmonary function tests, including the composite physiological index (CPI) in patients with pulmonary sarcoidosis. We integrated prognostic physiological and HRCT variables to form a clinical staging algorithm predictive of mortality in a test cohort. The staging system was externally validated in a separate cohort by the same methods of discrimination used in the primary analysis and tested for clinical applicability by four test observers. FINDINGS The test cohort included 251 patients with pulmonary sarcoidosis in the study referred to the Sarcoidosis clinic at the Royal Brompton Hospital, UK, between Jan 1, 2000, and June 30, 2010. The CPI was the strongest predictor of mortality (HR 1·04, 95% CI 1·02-1·06, p<0·0001) in the test cohort. An optimal CPI threshold of 40 units was identified (HR 4·24, 2·84-6·33, p<0·0001). The CPI40, main pulmonary artery diameter to ascending aorta diameter ratio (MPAD/AAD), and an extent of fibrosis threshold of 20% were combined to form a staging algorithm. When assessed in the validation cohort (n=252), this staging system was strikingly more predictive of mortality than any individual variable alone (HR 5·89, 2·68-10·08, p<0·0001). The staging system was successfully applied to the test and validation cohorts combined, by two radiologists and two physicians. INTERPRETATION A clear prognostic separation of patients with pulmonary sarcoidosis is provided by a simple staging system integrating the CPI and two HRCT variables.

Regional and global pancreatic T*2 MRI for iron overload assessment in a large cohort of healthy subjects: Normal values and correlation with age and gender

Multiecho gradient‐echo T*2 magnetic resonance imaging is a well‐established technique for iron overload assessment but there are few reports concerning the pancreas. The aim of this work was to assess the feasibility and reproducibility of the magnetic resonance imaging for measuring pancreatic regional and global T*2 values, to establish the lower limit of normal in a large cohort of healthy subjects and to correlate the measured values with age and gender. One hundred and twenty healthy subjects (61 males, 51 ± 17 years) underwent magnetic resonance imaging (1.5T) using a multiecho gradient‐echo T*2 sequence. T*2 measurements were performed in pancreatic head, body, and tail. The global value was calculated as the mean. Measurement of pancreatic T*2 values was feasible in all subjects. For the T*2 global value the coefficient of variation for intraoperator and interoperator reproducibility were 7.7% and 13%, respectively. The global T*2 values ranged from 24 to 52 ms with the lower limit of normal of 26 ms. There were no significant differences among the regional pancreatic T*2 values. No significant correlation was found between T*2 and patient age or gender. In conclusion, pancreatic T*2 measurements appear to be feasible, reproducible, nontime‐consuming and reliable. Gender‐ and age‐related differences concerning pancreatic T*2 were not found. Magn Reson Med, 2011.

Comparison between whole-body MRI and Fluorine-18-Fluorodeoxyglucose PET or PET/CT in oncology: a systematic review

Abstract Background. The aim of the article is to systematically review published data about the comparison between positron emission tomography (PET) or PET/computed tomography (PET/CT) using Fluorine-18-Fluorodeoxyglucose (FDG) and whole-body magnetic resonance imaging (WB-MRI) in patients with different tumours. Methods. A comprehensive literature search of studies published in PubMed/MEDLINE, Scopus and Embase databases through April 2012 and regarding the comparison between FDG-PET or PET/CT and WB-MRI in patients with various tumours was carried out. Results. Forty-four articles comprising 2287 patients were retrieved in full-text version, included and discussed in this systematic review. Several articles evaluated mixed tumours with both diagnostic methods. Concerning the specific tumour types, more evidence exists for lymphomas, bone tumours, head and neck tumours and lung tumours, whereas there is less evidence for other tumour types. Conclusions. Overall, based on the literature findings, WB-MRI seems to be a valid alternative method compared to PET/CT in oncology. Further larger prospective studies and in particular cost-effectiveness analysis comparing these two whole-body imaging techniques are needed to better assess the role of WB-MRI compared to FDG-PET or PET/ CT in specific tumour types.

Benign metastasizing leiomyoma presenting as cystic lung disease: a diagnostic pitfall

concordance for human epidermal growth factor 2 testing between the core biopsy TMA, the original core biopsy, and the subsequent resection specimen, further validating this technique. We are concerned that, if duplicate TMA cores are required, which would normally be the case, a substantial amount of donor tissue (8 mm) will be used, irrevocably compromising the original donor block. Nevertheless, this is likely to be a valuable technique when the donor block has generous amounts of tumour tissue. We have piloted this approach with biopsies taken from formalin-fixed tissue which is then paraffinprocessed as per routine. We do not believe that this will cause practical differences in comparison with the true situation, where fresh tissue is cored. Our cases were all no-special-type carcinomas, and we accept that the technique might not be as effective with some other types of cancer, particularly mucinous carcinomas and some lobular carcinomas. We are also aware of the possibility of a small gap being present between the two apposing TMA cores, leading to section dropout. This is likely to be the explanation for the drop-out of core R04 C13 between steps 13 and 19 and of core R02 C07 between steps 14 and 16 in Figure 2. We expect that this problem will be minimized by using the ‘depth stop’ kit described above, and also note that the number of sections that can be cut from a block should compensate for this loss. We have used 0.6-mm cores on this occasion, but most 14G needle core biopsies would allow the extraction of 1-mm cores, which would substantially increase the tissue area for analysis where one such core has the equivalent area of three 0.6-mm cores. We believe that two 1-mm cores per recipient well could be taken from a routine diagnostic block, leaving at least 90% of the original tumour for future analysis for direct patient care, and that such a provision should be put in place before these specimens are utilized for TMA construction.

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study

BACKGROUND Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the correct clinical context, when high-resolution CT appearances are those of usual interstitial pneumonia, a diagnosis of idiopathic pulmonary fibrosis can be made without surgical lung biopsy. We investigated the use of a deep learning algorithm for provision of automated classification of fibrotic lung disease on high-resolution CT according to criteria specified in two international diagnostic guideline statements: the 2011 American Thoracic Society (ATS)/European Respiratory Society (ERS)/Japanese Respiratory Society (JRS)/Latin American Thoracic Association (ALAT) guidelines for diagnosis and management of idiopathic pulmonary fibrosis and the Fleischner Society diagnostic criteria for idiopathic pulmonary fibrosis. METHODS In this case-cohort study, for algorithm development and testing, a database of 1157 anonymised high-resolution CT scans showing evidence of diffuse fibrotic lung disease was generated from two institutions. We separated the scans into three non-overlapping cohorts (training set, n=929; validation set, n=89; and test set A, n=139) and classified them using 2011 ATS/ERS/JRS/ALAT idiopathic pulmonary fibrosis diagnostic guidelines. For each scan, the lungs were segmented and resampled to create a maximum of 500 unique four slice combinations, which we converted into image montages. The final training dataset consisted of 420 096 unique montages for algorithm training. We evaluated algorithm performance, reported as accuracy, prognostic accuracy, and weighted κ coefficient (κw) of interobserver agreement, on test set A and a cohort of 150 high-resolution CT scans (test set B) with fibrotic lung disease compared with the majority vote of 91 specialist thoracic radiologists drawn from multiple international thoracic imaging societies. We then reclassified high-resolution CT scans according to Fleischner Society diagnostic criteria for idiopathic pulmonary fibrosis. We retrained the algorithm using these criteria and evaluated its performance on 75 fibrotic lung disease specific high-resolution CT scans compared with four specialist thoracic radiologists using weighted κ coefficient of interobserver agreement. FINDINGS The accuracy of the algorithm on test set A was 76·4%, with 92·7% of diagnoses within one category. The algorithm took 2·31 s to evaluate 150 four slice montages (each montage representing a single case from test set B). The median accuracy of the thoracic radiologists on test set B was 70·7% (IQR 65·3-74·7), and the accuracy of the algorithm was 73·3% (93·3% were within one category), outperforming 60 (66%) of 91 thoracic radiologists. Median interobserver agreement between each of the thoracic radiologists and the radiologists majority opinion was good (κw=0·67 [IQR 0·58-0·72]). Interobserver agreement between the algorithm and the radiologists majority opinion was good (κw=0·69), outperforming 56 (62%) of 91 thoracic radiologists. The algorithm provided equally prognostic discrimination between usual interstitial pneumonia and non-usual interstitial pneumonia diagnoses (hazard ratio 2·88, 95% CI 1·79-4·61, p<0·0001) compared with the majority opinion of the thoracic radiologists (2·74, 1·67-4·48, p<0·0001). For Fleischner Society high-resolution CT criteria for usual interstitial pneumonia, median interobserver agreement between the radiologists was moderate (κw=0·56 [IQR 0·55-0·58]), but was good between the algorithm and the radiologists (κw=0·64 [0·55-0·72]). INTERPRETATION High-resolution CT evaluation by a deep learning algorithm might provide low-cost, reproducible, near-instantaneous classification of fibrotic lung disease with human-level accuracy. These methods could be of benefit to centres at which thoracic imaging expertise is scarce, as well as for stratification of patients in clinical trials. FUNDING None.

Imaging for Sarcoidosis

Abstract Sarcoidosis is a systemic disease characterized by widespread development of noncaseating epithelioid granulomas. Based on a joint statement by the American Thoracic Society (ATS), European Thoracic Society (ERS), and the World Association for Sarcoidosis and other Granulomatous Disorders (WASOG), the diagnosis of sarcoidosis requires a compatible clinical picture, histologic demonstration of noncaseating granulomas, and exclusion of other diseases that may give a similar histologic or clinical picture. Although to a casual reader these recommendations suggest that making a diagnosis of sarcoidosis is straightforward, a consensus on the diagnostic role of imaging in sarcoidosis remains unclear. First, despite the primacy of chest computed tomography (CT) for evaluating diffuse lung disease, a guideline‐based diagnosis of sarcoidosis without biopsy requires specific appearances on chest radiography (Löfgrens syndrome) or67 Ga Scintigraphy (Heerfordts syndrome). Second, although the literature on CT as a prognostic tool in interstitial lung disease is relatively extensive, very little of this focuses specifically on sarcoidosis. Third, staging of sarcoidosis relies on radiographic appearances at presentation using a system devised by Scadding more than 40 years ago. This is in stark contrast to idiopathic pulmonary fibrosis where significant advances have been made in imaging‐based staging and computer‐assisted quantification of disease in the past 10 years. In this article, in addition to describing the myriad of imaging patterns seen in sarcoidosis, the impact imaging has on diagnosis, staging, and prediction of outcome will also be discussed. Cardiac‐related sarcoidosis and neurosarcoidosis will be discussed in separate articles.

Pulmonary fibrolysis in a patient with idiopathic pulmonary fibrosis: improvement of clinical and radiological pattern after treatment with pirfenidone

Idiopathic Pulmonary Fibrosis (IPF) is a chronic, progressive, fibrosing interstitial pneumonia associated with the histologic and/or radiologic pattern of usual interstitial pneumonia (UIP). Nowadays, the high‐resolution computed tomography pattern of “definite UIP” is enough to define a diagnosis of UIP without histological proof. This is pivotal especially in elderly patients with comorbidities. Early recognition of IPF is relevant for its prognostic implication. Some pharmacological strategies have been proposing novel molecules that tend to slow lung function decline, even though without healing fibrosis. We report a case of ex‐heavy smoker male with IPF showing clinical and radiological improvement after 11 months of treatment with Pirfenidone. The definite diagnosis was challenging and it was reached by a multidisciplinary approach.

Multifunctional Assessment of Non–Small Cell Lung Cancer: Perfusion-Metabolic Correlation

Purpose The aim of this study was to investigate the relationship between whole-tumor CT perfusion and FDG PET/CT parameters in non–small cell lung cancer (NSCLC). Methods Twenty-five patients with NSCLC were prospectively included. CT perfusion parameters calculated were blood flow (BF), blood volume (BV), mean transit time, and peak enhancement intensity. SUVmax, SUVpeak, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were evaluated for PET/CT. Tumor diameter and volume were measured, and lesions were divided according to maximum axial diameter in more than 3 cm and 3 cm or less. The correlations between CT perfusion and PET/CT parameters were assessed in all tumors, as well as according to tumor diameter and volume. Results Lesion diameter and volume showed a negative correlation with BF and BV (r = −0.78, −0.78, −0.57, −0.48, respectively) and a positive correlation with mean transit time (r = 0.55, 0.65, respectively). The negative correlation between BF and lesion diameter and volume was confirmed in the subgroup of lesions of more than 3 cm (r = −0.68, −0.68, respectively). A positive correlation between SUVmax, SUVpeak, SUVmean, and lesion volume was observed (r = 0.50, 0.50, 0.46, respectively) and confirmed in lesions 3 cm or less (r = 0.81, 0.79, 0.78, respectively). Metabolic tumor volume and TLG showed a positive correlation with lesion diameter and volume in the overall population (r = 0.93, 0.87, 0.88, 0.90, respectively) and in lesions of more than 3 cm (r = 0.89, 0.84, 0.84, 0.79, respectively). Blood flow and BV showed a negative correlation with MTV and TLG (r = −0.77, −0.74, and −0.58, −0.48, respectively) in the overall population and with MTV in lesions of more than 3 cm (r = −0.69, −0.62, respectively). Conclusions Perfusion and metabolic parameters seem to depend on tumor size. The bigger the tumor, the lower the BF and the BV and, conversely, the higher the SUVpeak, MTV, and TLG. This information would be useful in the clinical setting when diagnosing or treating NSCLC, especially with novel therapies and/or for radiation treatment modulation.