Ex vivo infection model for Francisella using human lung tissue.

Introduction: Tularemia is mainly caused by Francisella tularensis (Ft) subsp. tularensis (Ftt) and Ft subsp. holarctica (Ftt) in humans and in more than 200 animal species including rabbits and hares. Human clinical manifestations depend on the route of infection and range from flu-like symptoms to severe pneumonia with a mortality rate up to 60% without treatment. So far, only 2D cell culture and animal models are used to study Francisella virulence, but the gained results are transferable to human infections only to a certain extent. Method: In this study, we firstly established an ex vivo human lung tissue infection model using different Francisella strains: Ftt Life Vaccine Strain (LVS), Ftt LVS ΔiglC, Ftt human clinical isolate A-660 and a German environmental Francisella species strain W12-1067 (F-W12). Human lung tissue was used to determine the colony forming units and to detect infected cell types by using spectral immunofluorescence and electron microscopy. Chemokine and cytokine levels were measured in culture supernatants. Results: Only LVS and A-660 were able to grow within the human lung explants, whereas LVS ΔiglC and F-W12 did not replicate. Using human lung tissue, we observed a greater increase of bacterial load per explant for patient isolate A-660 compared to LVS, whereas a similar replication of both strains was observed in cell culture models with human macrophages. Alveolar macrophages were mainly infected in human lung tissue, but Ftt was also sporadically detected within white blood cells. Although Ftt replicated within lung tissue, an overall low induction of pro-inflammatory cytokines and chemokines was observed. A-660-infected lung explants secreted slightly less of IL-1ß, MCP-1, IP-10 and IL-6 compared to Ftt LVS-infected explants, suggesting a more repressed immune response for patient isolate A-660. When LVS and A-660 were used for simultaneous co-infections, only the ex vivo model reflected the less virulent phenotype of LVS, as it was outcompeted by A-660. Conclusion: We successfully implemented an ex vivo infection model using human lung tissue for Francisella. The model delivers considerable advantages and is able to discriminate virulent Francisella from less- or non-virulent strains and can be used to investigate the role of specific virulence factors.

Contribution of CAD to the Sensitivity for Detecting Lung Metastases on Thin-Section CT - A Prospective Study with Surgical and Histopathological Correlation.

PURPOSE: To assess the sensitivity of radiologists and a CAD system for the detection of lung metastases on thin-section computed tomographic (CT) scans prior to pulmonary metastasectomy. MATERIALS AND METHODS: All patients scheduled for resection of lung metastases were eligible for this prospective single-center trial. 95 patients with 115 surgical procedures (pulmonary metastasectomy using thoracotomy) were included. An experienced radiologist examined the CT scans for pulmonary metastases and documented his findings. A commercial CAD system was used as a second reader; additional CAD findings were recorded. A comparison of the sensitivity of the radiologist alone and with CAD was performed. Intraoperatively surgeons tried to identify the documented lesions and resected them as well as additionally palpable lesions. The standard of reference consisted of surgery and histopathology. Follow-up information for radiologically detected lesions missed during surgery was sought. RESULTS: 693 lesions (262 metastases) were detected radiologically or surgically, 646 of them were resected. The sensitivity of radiologists without CAD was 67.5 % for all lesions (87.4 % for metastases). CAD highly significantly (p < 0.001) increased the sensitivity to 77.9 % (92.7 %). During surgery, 143 additional lesions (19 metastases) were detected. 49 radiologically detected lesions were not palpable during surgery: 4 metastases, 5 benign lesions, and 40 lesions of an unknown nature. CONCLUSION: CAD provides significant additional sensitivity for detecting lung metastases using MDCT compared to the performance of a radiologist alone. CT reveals a relevant number of non-palpable pulmonary lesions. KEY POINTS: · CAD significantly increased the sensitivity for the detection of lung metastases on CT.. · Surgical palpation of the lungs missed 8.5 % of all radiologically detected lesions.. · CT with CAD may increase the chance for complete metastasectomy.. CITATION FORMAT: · Meybaum C, Graff M, Fallenberg EM et al. Contribution of CAD to the Sensitivity for Detecting Lung Metastases on Thin-Section CT - A Prospective Study with Surgical and Histopathological Correlation. Fortschr Röntgenstr 2020; 192: 65 - 73.