No abstract

Partially parallel MRI might be used for the assessment of lung perfusion. Future studies are required to further evaluate the diagnostic impact of this technique.

Background: Lung cancer screening may provide a favorable opportunity for a spirometry examination, to diagnose participants with undiagnosed lung function impairments, or to improve targeting of computed tomography (CT) screening intensity in view of expected net benefit.Methods: Spirometry was performed in the CT screening arm (n=2,029) of the German Lung Cancer Screening Intervention Study (LUSI)-a trial examining the effects of annual CT screening on lung cancer mortality, in 50-69-year-old long-term smokers. Participants were classified as having chronic obstructive pulmonary disease (COPD; FEV 1 /FVC <0.7), preserved ratio impaired spirometry (PRISm; FEV 1 /FVC ≥0.7and FEV 1 % predicted <80%), or normal spirometry. Descriptive statistics were used to examine associations of COPD or PRISm with respiratory symptoms, and self-reported medical diagnoses of respiratory and other morbidities. Logistic regression and proportional hazards regression were used to examine associations of COPD and PRISm, as well as their self-reported medical diagnoses, with risks of lung cancer and all-cause mortality.Results: A total of 1,987 screening arm participants (98%) provided interpretable spirometry measurements; of these, 34.3% had spirometric patterns consistent with either COPD (18.6%) or PRISm (15.7%). Two thirds of participants with COPD or PRISm were asymptomatic, and only 23% reported a previous medical diagnosis concordant with COPD. Participants reporting a diagnosis tended to be more often current and heavier smokers, and more often had respiratory symptoms, cardiovascular comorbidities, or more severe lung function impairments. Independently of smoking history, moderate-to-severe (GOLD 2-4) COPD (OR =2.14; 95% CI: 1.54-2.98), and PRISm (OR =2.68; 95% CI: 1.61-4.40), were associated with increased lung cancer risk. Lung cancer patients with PRISm less frequently had adenocarcinomas, and more often squamous cell or small cell tumors, compared to those with normal spirometry (n=45), and both PRISm and COPD were associated with more advanced lung cancer tumor stage for screen-detected cancers.PRISm and COPD, depending on GOLD stage, were also associated with about 2-to 4-fold increases in risk of overall mortality, which to 87 percent had causes other than lung cancer.Conclusions: About one third of smokers eligible for lung cancer screening in Germany have COPD or PRISm. As these conditions were associated with detection of lung cancer, spirometry may help identify populations at high risk for death of lung cancer or other causes, and who might particularly benefit from CT screening.

Objectives: Disseminated bone marrow (BM) involvement is frequent in multiple myeloma (MM). Whole-body magnetic resonance imaging (wb-MRI) enables to evaluate the whole BM. Reading of such whole-body scans is time-consuming, and yet radiologists can transfer only a small fraction of the information of the imaging data set to the report. This limits the influence that imaging can have on clinical decision-making and in research toward precision oncology. The objective of this feasibility study was to implement a concept for automatic, comprehensive characterization of the BM from wb-MRI, by automatic BM segmentation and subsequent radiomics analysis of 30 different BM spaces (BMS). Materials and Methods: This retrospective multicentric pilot study used a total of 106 wb-MRI from 102 patients with (smoldering) MM from 8 centers. Fifty wb-MRI from center 1 were used for training of segmentation algorithms (nnU-Nets) and radiomics algorithms. Fifty-six wb-MRI from 8 centers, acquired with a variety of different MRI scanners and protocols, were used for independent testing. Manual segmentations of 2700 BMS from 90 wb-MRI were performed for training and testing of the segmentation algorithms. For each BMS, 296 radiomics features were calculated individually. Dice score was used to assess similarity between automatic segmentations and manual reference segmentations. Results: The "multilabel nnU-Net" segmentation algorithm, which performs segmentation of 30 BMS and labels them individually, reached mean dice scores of 0.88 ± 0.06/0.87 ± 0.06/0.83 ± 0.11 in independent test sets from center 1/center 2/center 3-8 (interrater variability between radiologists, 0.88 ± 0.01). The subset from the multicenter, multivendor test set (center 3-8) that was of high imaging quality was segmented with high precision (mean dice score, 0.87), comparable to the internal test data from center 1. The radiomic BM phenotype consisting of 8880 descriptive parameters per patient, which result from calculation of 296 radiomics features for each of the 30 BMS, was calculated for all patients.Exemplary cases demonstrated connections between typical BM patterns in MM and radiomic signatures of the respective BMS. In plausibility tests, predicted size and weight based on radiomics models of the radiomic BM phenotype significantly correlated with patients' actual size and weight (P = 0.002 and P = 0.003, respectively). Conclusions: This pilot study demonstrates the feasibility of automatic, objective, comprehensive BM characterization from wb-MRI in multicentric data sets. This concept allows the extraction of high-dimensional phenotypes to capture the complexity of disseminated BM disorders from imaging. Further studies need to assess the clinical potential of this method for automatic staging, therapy response assessment, or prediction of biopsy results.