Automatic lung segmentation in COVID-19 patients: Impact on quantitative computed tomography analysis.

PURPOSE: To assess the impact of lung segmentation accuracy in an automatic pipeline for quantitative analysis of CT images. METHODS: Four different platforms for automatic lung segmentation based on convolutional neural network (CNN), region-growing technique and atlas-based algorithm were considered. The platforms were tested using CT images of 55 COVID-19 patients with severe lung impairment. Four radiologists assessed the segmentations using a 5-point qualitative score (QS). For each CT series, a manually revised reference segmentation (RS) was obtained. Histogram-based quantitative metrics (QM) were calculated from CT histogram using lung segmentationsfrom all platforms and RS. Dice index (DI) and differences of QMs (ΔQMs) were calculated between RS and other segmentations. RESULTS: Highest QS and lower ΔQMs values were associated to the CNN algorithm. However, only 45% CNN segmentations were judged to need no or only minimal corrections, and in only 17 cases (31%), automatic segmentations provided RS without manual corrections. Median values of the DI for the four algorithms ranged from 0.993 to 0.904. Significant differences for all QMs calculated between automatic segmentations and RS were found both when data were pooled together and stratified according to QS, indicating a relationship between qualitative and quantitative measurements. The most unstable QM was the histogram 90th percentile, with median ΔQMs values ranging from 10HU and 158HU between different algorithms. CONCLUSIONS: None of tested algorithms provided fully reliable segmentation. Segmentation accuracy impacts differently on different quantitative metrics, and each of them should be individually evaluated according to the purpose of subsequent analyses.

Severe pneumonia after intravesical BCG instillation in a patient with invasive bladder cancer: case report and literature review.

We present here the case of a 66 year old man with a severe bilateral community acquired pneumonia secondary to dissemination after an intravesical instillation of bacilllus Calmette-Guerin (BCG). Diagnosis was based on positive polymerase chain reaction (PCR) for mycobacterium tuberculosis complex in bronchoalveolar lavage and on the finding on transbronchial biopsy of non necrotising granulomas histopathologically similar to the granulomas found in bladder biopsies. These findings were confirmed using a validated real time PCR assay demonstrating the presence of the BCG genome in transbronchial and bladder biopsies.

Automatic registration of PET and CT studies for clinical use in thoracic and abdominal conformal radiotherapy.

AIM: Implementation and validation of an automatic registration method based on mutual information (MI) for the integration of thoracic and abdominal positron emission tomography (PET)/computed tomography (CT) studies, with the purpose to facilitate in a clinical context the inclusion of PET metabolic information in conformal radiotherapy (RT). METHODS: Registration was obtained by modeling a rigid spatial transformation between CT and PET transmission studies. The registration method was based on Normalized Mutual Information (NMI), by iteratively transforming the PET volume, until its optimal alignment to the CT study is achieved, in correspondence of the maximum of NMI. To avoid entrapment in local maxima and to improve convergence speed we introduced a multiresolution scheme. Accuracy of the proposed approach was investigated in experimental data, relative to phantom and patient studies, acquired in conditions similar to clinical situations. RESULTS: In phantom studies the mean error in the 3D space is 3.6 mm (range 3-4 mm) in thoracic region and 3.2 mm (range 2.9-3.7 mm) in abdominal region, considerably less than PET spatial resolution. In patient studies the spatial mean error increases with respect to phantom studies (5.4 mm and 5.2 mm for thorax and abdomen, respectively) but remains comparable to the PET spatial resolution. The accuracy of spatial realignment was thus found adequate for the registration of PET/CT registration, if good patient repositioning was adopted. CONCLUSIONS: The proposed registration method, based on MI, was validated for the integration of PET/CT studies of patients candidate for thoracic and abdominal conformal RT. The method is automatic and provided with a user interface, thus suitable for clinical use.

Feasibility of [18F]FDG-PET and coregistered CT on clinical target volume definition of advanced non-small cell lung cancer.

AIM: To prospectively evaluate the impact of coregistered positron emission tomography (PET) and computed tomography (CT) in 3D conformal radiotherapy (3D-CRT) planning in patients with non-small lung cancer (NSCLC). METHODS: Twenty-one patients (median age: 57 years; range: 42-80 years) referred to 3D-CRT for NSCLC were recruited. Positron emission tomography with 18F-fluorodeoxyglucose ([18F]FDG-PET) and conventional CT images were coregistered (PET/CT images) using a commercial software package based on surface matching technique. Neoplastic areas were contoured on [18F]FDG-PET images with the aid of the correspondent CT image by a nuclear medicine physician. CT images and their relative PET contours were then transferred to treatment planning system. A radiation oncologist firstly contoured clinical target volumes (CTV) on CT scan alone (CTV-CT), and then on coregistered PET/CT images (CTV-PET/CT). CTV-CT and CTV-PET/CT were compared for each patient; a difference higher than 25% was considered of clinical relevance. RESULTS: Three patients were shifted to palliative radiotherapy for metastatic disease or very large tumor size, showed by [18F]FDG-PET. Of the remaining 18 patients a CTV change, after inclusion of PET/CT data, was observed in 10/18 cases (55%): larger in 7/18 (range 33-279%) and smaller in 3/18 patients (range 26-34%), mainly due to inclusion or exclusion of lymph-nodal disease and to better definition of tumor extent. CTV changes smaller than 25% occurred in the remaining 8/18 patients. CONCLUSIONS: [18F]FDG-PET and CT images co-registration in radiotherapy treatment planning led to a change in CTV definition in the majority of our patients, which may significantly modify management and radiation treatment modality in these patients.

[An important variability factor in determination of urinary activity of N-acetyl-beta-D-glucosaminidase: contamination of urine with semen]. / A proposito di un importante fattore di variabilità nella determinazione dell'attività urinaria della N-acetil-beta-D- glucosaminidasi: la contaminazione delle urine con liquido seminale.

BACKGROUND: Urinary N-acetyl-beta-D-glucosaminidase (U-NAG) and its isoenzyme B (U-NAG-B) have been demonstrated useful and early markers of renal damage, although they are present in many other tissues and organs. OBJECTIVES: To evaluate semen contamination of the urine and its role in variability of U-NAG. METHODS: To assess control group values beta2-microglobulin, retinol-binding protein and U-NAG were measured in the urine of 30 healthy, non-smoking and non metal-exposed adults (19 females and 11 males). RESULTS: In four urine samples U-NAG was higher than the method reference value (5 U/g creatinine), without increases in other functional markers. Microscope examination revealed the presence of sperm in these samples. U-NAG variability decreased after the exclusion of these four values. The role of contamination was confirmed by adding semen to urine: when semen to urine ratio was 1:1000, enzyme activity was more than twice the basal level. CONCLUSIONS: U-NAG variability is strongly increased by contamination with semen, where enzyme concentration (especially NAG-B) is very high. Increased excretion of U-NAG and of its iso-form (U-NAG-B) in males, not correlated with other renal alterations or with exposure to heavy metals or other renal toxic substances, should be carefully evaluated and microscopic observation is advisable to detect the presence of sperm in urine.