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Objectives: Patients receiving remission induction therapy for acute myeloid leukaemia (AML) are at high risk of developing invasive fungal disease (IFD). Newer therapies with targeted antileukemic agents and the emergence of azole resistance pose a challenge to the strategy of primary antifungal prophylaxis. We report the experience of a diagnostic-driven care pathway (DCP) for the management of IFD in these patients, using only culture-directed mould inactive prophylaxis. Methods: Retrospectively, we used a single-centre study of consecutive patients receiving intensive chemotherapy for myeloid malignancies between 2014 and 2021. DCP consisted of serial cultures and serum galactomannan (sGM) screening, CT imaging, and bronchoscopy to direct targeted antifungal treatment. IFD was classified according to the 2020 EORTC/MSGERC criteria. Results: A total of 192 patients with myeloid malignancies received 300 courses of intensive chemotherapy. There were 14 cases of invasive yeast infections and 18 of probable/proven invasive mould disease (IMD). The incidence of probable/proven IMD during the first cycle of remission-induction chemotherapy was 4.6% (n = 9). sGM remained negative in all cases of invasive aspergillosis (IA), with positive mycology findings in bronchoalveolar lavage. All-cause mortality was 9.4% (n = 18) 100 days after starting chemotherapy and was comparable between patients with or without IFD. The fungal-related mortality was 1% (n = 2). Conclusion: Diagnostic-driven based management without universal mould active prophylaxis is a feasible strategy in the management of IFD and limits unnecessary antimould treatment during intensive chemotherapy. The poor performance of serial serum galactomannan screening in detecting IA warrants further investigation.

To compare human observers to a mathematically derived computer model for differentiation between malignant and benign pulmonary nodules detected on baseline screening computed tomography (CT) scans.A case-cohort study design was chosen. The study group consisted of 300 chest CT scans from the Danish Lung Cancer Screening Trial (DLCST). It included all scans with proven malignancies (n = 62) and two subsets of randomly selected baseline scans with benign nodules of all sizes (n = 120) and matched in size to the cancers, respectively (n = 118). Eleven observers and the computer model (PanCan) assigned a malignancy probability score to each nodule. Performances were expressed by area under the ROC curve (AUC). Performance differences were tested using the Dorfman, Berbaum and Metz method. Seven observers assessed morphological nodule characteristics using a predefined list. Differences in morphological features between malignant and size-matched benign nodules were analyzed using chi-square analysis with Bonferroni correction. A significant difference was defined at p < 0.004.Performances of the model and observers were equivalent (AUC 0.932 versus 0.910, p = 0.184) for risk-assessment of malignant and benign nodules of all sizes. However, human readers performed superior to the computer model for differentiating malignant nodules from size-matched benign nodules (AUC 0.819 versus 0.706, p < 0.001). Large variations between observers were seen for ROC areas and ranges of risk scores. Morphological findings indicative of malignancy referred to border characteristics (spiculation, p < 0.001) and perinodular architectural deformation (distortion of surrounding lung parenchyma architecture, p < 0.001; pleural retraction, p = 0.002).Computer model and human observers perform equivalent for differentiating malignant from randomly selected benign nodules, confirming the high potential of computer models for nodule risk estimation in population based screening studies. However, computer models highly rely on size as discriminator. Incorporation of other morphological criteria used by human observers to superiorly discriminate size-matched malignant from benign nodules, will further improve computer performance.

To determine whether density mapping (DM) is more accurate for detection and quantification of pathologic air trapping (pAT) in patients after lung transplantation compared to other CT air trapping measures. One-hundred forty-seven lung and heart-lung transplant recipients underwent CT-examinations at functional residual capacity (FRC) and total lung capacity (TLC) and PFT six months after lung transplantation. Quantification of air trapping was performed with the threshold-based method in expiration (EXP), density mapping (DM) and the expiratory to inspiratory ratio of the mean lung density (E/I-ratio MLD). A non-rigid registration of inspiration-expiration CT-data with a following voxel-to-voxel mapping was carried out for DM. Systematic variation of attenuation ranges was performed for EXP and DM and correlated with the ratio of residual volume to total lung capacity (RV/TLC) by Spearman rank correlation test. AT was considered pathologic if RV/TLC was above the 95th percentile of the predicted upper limit of normal values. Receiver operating characteristic (ROC) analysis was performed. The optimal attenuation range for the EXP method was from -790 HU to -950 HU (EXP(-790 to -950HU)) (r = 0.524, p

ObjectivesTo prospectively evaluate quantitative airway wall measurements of thin-section CT for the diagnosis of Bronchiolitis Obliterans Syndrome (BOS) following lung transplantation.Materials and methodsIn 141 CT examinations, bronchial wall thickness (WT), the wall area percentage (WA%) calculated as the ratio of the bronchial wall area and the total area (sum of bronchial wall area and bronchial lumen area) and the difference of the WT on inspiration and expiration (WTdiff) were automatically measured in different bronchial generations. The measurements were correlated with the lung function parameters. WT and WA% in CT examinations of patients with (n = 25) and without (n = 116) BOS, were compared using the unpaired t-test and univariate analysis of variance, while also considering the differing lung volumes.ResultsMeasurements could be performed in 2,978 bronchial generations. WT, WA%, and WTdiff did not correlate with the lung function parameters (rConclusionWA% on inspiration was significantly greater in patients with than in those without BOS. However, WA% measurements were significantly dependent on lung volume and showed a high variability, thus not allowing the sole use of bronchial wall measurements to differentiate patients with from those without BOS.