Differentiating inflammatory and malignant pulmonary lesions on 3T lung MRI with radiomics of apparent diffusion coefficient maps and T2w derived radiomic feature maps.

Background: Differentiating inflammatory from malignant lung lesions continues to be challenging in clinical routine, frequently requiring invasive methods like biopsy. Therefore, we aimed to investigate if inflammatory and malignant pulmonary lesions could be distinguished noninvasively using radiomics of apparent diffusion coefficient (ADC) maps and radiomic feature maps calculated from T2-weighted (T2w) 3 Tesla (3T) magnetic resonance imaging (MRI) of the lung. Methods: Fifty-four patients with an unclear pulmonary lesion on computed tomography (CT) were prospectively included and examined by 3T MRI with T2w and diffusion-weighted sequences (b values of 50 and 800). ADC maps were calculated automatically. All patients underwent biopsy or bronchoalveolar lavage (BAL). Sixteen patients were excluded (e.g., motion artifacts), leaving 19 patients each with malignant and inflammatory pulmonary lesions. Target lesions were defined by biopsy or as the largest lesion (BAL-based pathogen detection), and two readers placed volumes of interest (VOIs) around the lesions on T2w images and ADC maps. One hundred and seven features were conventionally extracted from the ADC maps using PyRadiomics. T2w images were converted to 107 parametric feature maps per patient using a PyRadiomics-based, pretested software tool developed by our group. VOIs were copied from T2w images to T2 maps for feature quantification. Features were tested for significant differences using the Mann-Whitney U-test. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis and interreader agreement by intraclass correlation coefficients (ICCs). Results: Fifty-eight features derived from ADC maps differed significantly between malignant and inflammatory pulmonary lesions, with areas under the curve (AUCs) >0.90 for 5 and >0.80 for 27 features, compared with 67 features from T2 maps (5 features with AUCs >0.80). ICCs were excellent throughout. Conclusions: ADC and T2 maps differentiate inflammatory and malignant pulmonary lesions with outstanding (ADC) and excellent (T2w derived feature maps) diagnostic performance. MRI could thus guide the further diagnostic workup and a timely initiation of the appropriate therapy.

Elevation of cardiac biomarkers in stroke is associated with pathological findings on cardiac MRI-results of the HEart and BRain interfaces in Acute Stroke study.

INTRODUCTION: Cardiac biomarkers, such as high-sensitivity cardiac troponin T (hs-cTnT), are frequently elevated in ischemic stroke patients but the mechanisms underlying this elevation are insufficiently understood. We determined the presence of cardiac damage, assessed using cardiac magnetic resonance imaging (CMR), in stroke patients with elevated hs-cTnT and brain natriuretic peptide (BNP). METHODS: This is a post hoc analysis of the prospective, investigator-initiated, cross-sectional HEart and BRain interfaces in Acute Stroke (HEBRAS) study. All patients underwent the measurement of hs-cTnT and BNP as well as gadolinium-enhanced CMR in the acute phase of ischemic stroke. We performed unadjusted and adjusted logistic regression models to assess the association between hs-cTnT and BNP elevation and the presence of pathological CMR findings. RESULTS: Two hundred and thirty-three stroke patients (median age 67 years, 33% female) were included, of whom 43 (21%) had elevated hs-cTnT and 109 (47%) had elevated BNP. Hundred of the 233 (43%) patients had pathological findings on CMR had focal fibrosis as detected by late-gadolinium enhancement (LGE) in 51 (23%), left-ventricular hypertrophy (LVH) in 38 (16%), reduced LVEF in 32 (14%), and left-atrial dilatation in 34 (15%). After adjustment for potential confounders, both hs-cTnT (adjOR 5.0 (95%CI 2.1-11.7), p < 0.001) and BNP (adjOR 4.1 (95%CI 2.3-7.3), p < 0.001) were significantly associated with pathological findings on CMR. Hs-cTnT was associated with LGE, LVEF, and LVH, whereas BNP was associated with left-atrial dilatation and LVEF, LVH. CONCLUSION: Elevated cardiac biomarkers in acute stroke including CMR are strongly associated with pathological findings on CMR. In acute stroke patients, the elevation of cardiac biomarkers may identify patients who require a more thorough cardiology work-up.

CT radiomics to predict Deauville score 4 positive and negative Hodgkin lymphoma manifestations.

18F-FDG-PET/CT is standard to assess response in Hodgkin lymphoma by quantifying metabolic activity with the Deauville score. PET/CT, however, is time-consuming, cost-extensive, linked to high radiation and has a low availability. As an alternative, we investigated radiomics from non-contrast-enhanced computed tomography (NECT) scans. 75 PET/CT examinations of 43 patients on two different scanners were included. Target lesions were classified as Deauville score 4 positive (DS4+) or negative (DS4-) based on their SUVpeak and then segmented in NECT images. From these segmentations, 107 features were extracted with PyRadiomics. All further statistical analyses were then performed scanner-wise: differences between DS4+ and DS4- manifestations were assessed with the Mann-Whitney-U-test and single feature performances with the ROC-analysis. To further verify the reliability of the results, the number of features was reduced using different techniques. The feature median showed a high sensitivity for DS4+ manifestations on both scanners (scanner A: 0.91, scanner B: 0.85). It furthermore was the only feature that remained in both datasets after applying different feature reduction techniques. The feature median from NECT concordantly has a high sensitivity for DS4+ Hodgkin manifestations on two different scanners and thus could provide a surrogate for increased metabolic activity in PET/CT.

Two-Stage Deep Learning Model for Automated Segmentation and Classification of Splenomegaly.

Splenomegaly is a common cross-sectional imaging finding with a variety of differential diagnoses. This study aimed to evaluate whether a deep learning model could automatically segment the spleen and identify the cause of splenomegaly in patients with cirrhotic portal hypertension versus patients with lymphoma disease. This retrospective study included 149 patients with splenomegaly on computed tomography (CT) images (77 patients with cirrhotic portal hypertension, 72 patients with lymphoma) who underwent a CT scan between October 2020 and July 2021. The dataset was divided into a training (n = 99), a validation (n = 25) and a test cohort (n = 25). In the first stage, the spleen was automatically segmented using a modified U-Net architecture. In the second stage, the CT images were classified into two groups using a 3D DenseNet to discriminate between the causes of splenomegaly, first using the whole abdominal CT, and second using only the spleen segmentation mask. The classification performances were evaluated using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). Occlusion sensitivity maps were applied to the whole abdominal CT images, to illustrate which regions were important for the prediction. When trained on the whole abdominal CT volume, the DenseNet was able to differentiate between the lymphoma and liver cirrhosis in the test cohort with an AUC of 0.88 and an ACC of 0.88. When the model was trained on the spleen segmentation mask, the performance decreased (AUC = 0.81, ACC = 0.76). Our model was able to accurately segment splenomegaly and recognize the underlying cause. Training on whole abdomen scans outperformed training using the segmentation mask. Nonetheless, considering the performance, a broader and more general application to differentiate other causes for splenomegaly is also conceivable.

Enhancing the stability of CT radiomics across different volume of interest sizes using parametric feature maps: a phantom study.

BACKGROUND: In radiomics studies, differences in the volume of interest (VOI) are often inevitable and may confound the extracted features. We aimed to correct this confounding effect of VOI variability by applying parametric maps with a fixed voxel size. METHODS: Ten scans of a cup filled with sodium chloride solution were scanned using a multislice computed tomography (CT) unit. Sphere-shaped VOIs with different diameters (4, 8, or 16 mm) were drawn centrally into the phantom. A total of 93 features were extracted conventionally from the original images using PyRadiomics. Using a self-designed and pretested software tool, parametric maps for the same 93 features with a fixed voxel size of 4 mm3 were created. To retrieve the feature values from the maps, VOIs were copied from the original images to preserve the position. Differences in feature quantities between the VOI sizes were tested with the Mann-Whitney U-test and agreement with overall concordance correlation coefficients (OCCC). RESULTS: Fifty-five conventionally extracted features were significantly different between the VOI sizes, and none of the features showed excellent agreement in terms of OCCCs. When read from the parametric maps, only 8 features showed significant differences, and 3 features showed an excellent OCCC (≥ 0.85). The OCCCs for 89 features substantially increased using the parametric maps. CONCLUSIONS: This phantom study shows that converting CT images into parametric maps resolves the confounding effect of VOI variability and increases feature reproducibility across VOI sizes.

Differentiation of Pulmonary Lymphoma Manifestations and Nonlymphoma Infiltrates in Possible Invasive Fungal Disease Using Fast T1-weighted Magnetic Resonance Imaging at 3 T Comparison of Texture Analysis, Mapping, and Signal Intensity Quotients.

PURPOSE: This study aimed to evaluate the diagnostic performance of texture analysis (TA), T1 mapping, and signal intensity quotients derived from fast T1-weighted gradient echo (T1w GRE) sequences for differentiating pulmonary lymphoma manifestations and nonlymphoma infiltrates in possible invasive fungal disease in immunocompromised hematological patients. MATERIALS AND METHODS: Twenty patients with hematologic malignancies and concomitant immunosuppression (including 10 patients with pulmonary lymphoma manifestations and 10 patients with nonlymphoma infiltrates) prospectively underwent 3 T magnetic resonance imaging using a conventional T1w GRE sequence and a T1w GRE mapping sequence with variable flip angle. A region of interest was placed around the most representative lesion in each patient. TA was performed using PyRadiomics. T1 relaxation times were extracted from precompiled maps and calculated manually. Signal intensity quotients (lesion/muscle) were calculated from conventional T1w GRE sequences. RESULTS: Of all TA features, variance, mean absolute deviation, robust mean absolute deviation, interquartile range, and minimum were significantly different between the 2 entities (P<0.05), with excellent diagnostic performance in receiver operating characteristic analysis (area under the curve [AUC] >80%). Neither T1 relaxation times from precompiled maps (AUC=63%; P=0.353) nor manual calculation (AUC=63%; P=0.353) nor signal intensity quotients (AUC=70%; P=0.143) yielded significant differences. CONCLUSIONS: TA from fast T1w GRE images can differentiate pulmonary lymphoma manifestations and nonlymphoma infiltrates in possible invasive fungal disease with excellent diagnostic performance using the TA features variance, mean absolute deviation, robust mean absolute deviation, interquartile range, and minimum. Combining a fast T1w GRE sequence with TA seems to be a promising tool to differentiate these 2 entities noninvasively.

Stability of Liver Radiomics across Different 3D ROI Sizes-An MRI In Vivo Study.

We aimed to evaluate the stability of radiomic features in the liver of healthy individuals across different three-dimensional regions of interest (3D ROI) sizes in T1-weighted (T1w) and T2-weighted (T2w) images from different MR scanners. We retrospectively included 66 examinations of patients without known diseases or pathological imaging findings acquired on three MRI scanners (3 Tesla I: 25 patients, 3 Tesla II: 19 patients, 1.5 Tesla: 22 patients). 3D ROIs of different diameters (10, 20, 30 mm) were drawn on T1w GRE and T2w TSE images into the liver parenchyma (segment V-VIII). We extracted 93 radiomic features from the different ROIs and tested features for significant differences with the Mann-Whitney-U (MWU)-test. The MWU-test revealed significant differences for most second- and higher-order features, indicating a systematic difference dependent on the ROI size. The features mean, median, root mean squared (RMS), 10th percentile, and 90th percentile were not significantly different. We also assessed feature robustness to ROI size variation with overall concordance correlation coefficients (OCCCs). OCCCs across the different ROI-sizes for mean, median, and RMS were excellent (>0.90) in both sequences on all three scanners. These features, therefore, seem robust to ROI-size variation and suitable for radiomic studies of liver MRI.

Evaluation of a Deep Learning Algorithm for Automated Spleen Segmentation in Patients with Conditions Directly or Indirectly Affecting the Spleen.

The aim of this study was to develop a deep learning-based algorithm for fully automated spleen segmentation using CT images and to evaluate the performance in conditions directly or indirectly affecting the spleen (e.g., splenomegaly, ascites). For this, a 3D U-Net was trained on an in-house dataset (n = 61) including diseases with and without splenic involvement (in-house U-Net), and an open-source dataset from the Medical Segmentation Decathlon (open dataset, n = 61) without splenic abnormalities (open U-Net). Both datasets were split into a training (n = 32.52%), a validation (n = 9.15%) and a testing dataset (n = 20.33%). The segmentation performances of the two models were measured using four established metrics, including the Dice Similarity Coefficient (DSC). On the open test dataset, the in-house and open U-Net achieved a mean DSC of 0.906 and 0.897 respectively (p = 0.526). On the in-house test dataset, the in-house U-Net achieved a mean DSC of 0.941, whereas the open U-Net obtained a mean DSC of 0.648 (p < 0.001), showing very poor segmentation results in patients with abnormalities in or surrounding the spleen. Thus, for reliable, fully automated spleen segmentation in clinical routine, the training dataset of a deep learning-based algorithm should include conditions that directly or indirectly affect the spleen.

Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features.

Aim was to develop a user-friendly method for creating parametric maps that would provide a comprehensible visualization and allow immediate quantification of radiomics features. For this, a self-explanatory graphical user interface was designed, and for the proof of concept, maps were created for CT and MR images and features were compared to those from conventional extractions. Especially first-order features were concordant between maps and conventional extractions, some even across all examples. Potential clinical applications were tested on CT and MR images for the differentiation of pulmonary lesions. In these sample applications, maps of Skewness enhanced the differentiation of non-malignant lesions and non-small lung carcinoma manifestations on CT images and maps of Variance enhanced the differentiation of pulmonary lymphoma manifestations and fungal infiltrates on MR images. This new and simple method for creating parametric maps makes radiomics features visually perceivable, allows direct feature quantification by placing a region of interest, can improve the assessment of radiological images and, furthermore, can increase the use of radiomics in clinical routine.

Stability of Radiomic Features across Different Region of Interest Sizes-A CT and MR Phantom Study.

We aimed to evaluate radiomic features' stability across different region of interest (ROI) sizes in CT and MR images. We chose a phantom with a homogenous internal structure so no differences for a feature extracted from ROIs of different sizes would be expected. For this, we scanned a plastic cup filled with sodium chloride solution ten times in CT and per MR sequence (T1-weighted-gradient-echo and T2-weighted-turbo-inversion-recovery-magnitude). We placed sphere-shaped ROIs of different diameters (4, 8, and 16 mm, and 4, 8, and 16 pixels) into the phantom's center. Features were extracted using PyRadiomics. We assessed feature stability across ROI sizes with overall concordance correlation coefficients (OCCCs). Differences were tested for significance with the Mann-Whitney U-test. Of 93 features, 87 T1w-derived, 87 TIRM-derived, and 70 CT-derived features were significantly different between ROI sizes. Among MR-derived features, OCCCs showed excellent (>0.90) agreement for mean, median, and root mean squared for ROI sizes between 4 and 16 mm and pixels. We further observed excellent agreement for 10th and 90th percentile in T1w and 10th percentile in T2w TIRM images. There was no excellent agreement among the OCCCs of CT-derived features. In summary, many features indicated significant differences and only few showed excellent agreement across varying ROI sizes, although we examined a homogenous phantom. Since we considered a small phantom in an experimental setting, further studies to investigate this size effect would be necessary for a generalization. Nevertheless, we believe knowledge about this effect is crucial in interpreting radiomics studies, as features that supposedly discriminate disease entities may only indicate a systematic difference in ROI size.

Enhancing the differentiation of pulmonary lymphoma and fungal pneumonia in hematological patients using texture analysis in 3-T MRI.

OBJECTIVES: To evaluate texture analysis in nonenhanced 3-T MRI for differentiating pulmonary fungal infiltrates and lymphoma manifestations in hematological patients and to compare the diagnostic performance with that of signal intensity quotients ("nonenhanced imaging characterization quotients," NICQs). METHODS: MR scans were performed using a speed-optimized imaging protocol without an intravenous contrast medium including axial T2-weighted (T2w) single-shot fast spin-echo and T1-weighted (T1w) gradient-echo sequences. ROIs were drawn within the lesions to extract first-order statistics from original images using HeterogeneityCAD and PyRadiomics. NICQs were calculated using signal intensities of the lesions, muscle, and fat. The standard of reference was histology or clinical diagnosis in follow-up. Statistical testing included ROC analysis, clustered ROC analysis, and DeLong test. Intra- and interrater reliability was tested using intraclass correlation coefficients (ICC). RESULTS: Thirty-three fungal infiltrates in 16 patients and 38 pulmonary lymphoma manifestations in 19 patients were included. Considering the leading lesion in each patient, diagnostic performance was excellent for T1w entropy (AUC 80.2%; p < 0.005) and slightly inferior for T2w energy (79.9%; p < 0.005), T1w uniformity (79.6%; p < 0.005), and T1w energy (77.0%; p < 0.01); the best AUC for NICQs was 72.0% for T2NICQmean (p < 0.05). Intra- and interrater reliability was good to excellent (ICC > 0.81) for these parameters except for moderate intrarater reliability of T1w energy (ICC = 0.64). CONCLUSIONS: T1w entropy, uniformity, and energy and T2w energy showed the best performances for differentiating pulmonary lymphoma and fungal pneumonia and outperformed NICQs. Results of the texture analysis should be checked for their intrinsic consistency to identify possible incongruities of single parameters. KEY POINTS: • Texture analysis in nonenhanced pulmonary MRI improves the differentiation of pulmonary lymphoma and fungal pneumonia compared with signal intensity quotients. • T1w entropy, uniformity, and energy along with T2w energy show the best performances for differentiating pulmonary lymphoma from fungal pneumonia. • The results of the texture analysis should be checked for their intrinsic consistency to identify possible incongruities of single parameters.

Evaluation of left ventricular function in patients with acute ischaemic stroke using cine cardiovascular magnetic resonance imaging.

AIMS: Heart failure (HF) is frequent in patients with acute ischaemic stroke (AIS) and associated with higher morbidity and mortality. Assessment of cardiac function in AIS patients using cardiovascular MRI (CMR) may help to detect HF. We report the rate of systolic and diastolic dysfunction in a cohort of patients with AIS using CMR and compare cine real-time (CRT) sequences with the reference of segmented cine steady-state free precession sequences. METHODS AND RESULTS: Patients with AIS without known atrial fibrillation were prospectively enrolled in the HEart and BRain Interfaces in Acute Ischemic Stroke (HEBRAS) study (NCT02142413) and underwent CMR at 3 Tesla within 7 days after AIS. Validity of CRT sequences was determined in 50 patients. A total of 229 patients were included in the analysis (mean age 66 years; 35% women; HF 2%). Evaluation of cardiac function was successful in 172 (75%) patients. Median time from stroke onset to CMR was 82 h (interquartile range 56-111) and 54 h (interquartile range 31-78) from cerebral MRI to CMR. Systolic dysfunction was observed in 43 (25%) and diastolic dysfunction in 102 (59%) patients. Diagnostic yield was similar using CRT or segmented cine imaging (no significant difference in left ventricular ejection fraction, myocardial mass, time to peak filling rate, and peak filling rate ratio E/A). Intraobserver and interobserver agreement was high (κ = 0.78-1.0 for all modalities). CONCLUSIONS: Cardiovascular MRI at 3 Tesla is an appropriate method for the evaluation of cardiac function in a selected cohort of patients with AIS. Systolic and diastolic dysfunction is frequent in these patients. CRT imaging allows reliable assessment of systolic and diastolic function.

Age-dependent diagnostic accuracy of clinical scoring systems and D-dimer levels in the diagnosis of pulmonary embolism with computed tomography pulmonary angiography (CTPA).

OBJECTIVE: The aim of this study was to compare the age-dependent diagnostic performance of clinical scores and D-dimer testing to identify patients with suspected pulmonary embolism (PE). METHODS: Consecutive patients with suspected PE referred from the emergency department for computed tomography pulmonary angiography (CTPA) were retrospectively evaluated. Diagnostic scores (classic Wells score (WS), modified WS, simplified WS, revised Geneva score (GS), simplified GS, and YEARS score) were calculated from medical records. Results of D-dimer testing were retrieved from the laboratory database. CTPA was the diagnostic reference standard. Four age groups were analyzed (< 50, 50-64, 65-74, and ≥ 75 years). Statistical analysis used receiver operating characteristics as well as uni- and multivariate analyses with calculation of prediction models. The study was IRB approved. RESULTS: One thousand consecutive patients were included. Areas under the curve (AUC) and accuracies were superior in patients < 50 years. For the classic WS, the AUC decreased by 11% with the optimal cutoff dropping 1.5 points in patients ≥ 75 years; for D-dimer levels, the optimal cutoff was 900 µg/L higher in both ≥ 65 years groups with a max. decrease of the AUC of 9%. In terms of accuracy, the YEARS score performed best across all groups. Classic WS and D-dimer level showed a significant interaction with patient age in prediction models. CONCLUSION: D-dimer measurement and clinical scores perform best in patients < 50 years. The YEARS score performs best across all age groups and is therefore recommended. KEY POINTS: • The probability of pulmonary embolism predicted by fibrin fibrinogen degradation products and clinical scores shows the highest accuracy in patients < 50 years. • The probability of pulmonary embolism predicted by the YEARS score shows the highest accuracy in each age group. • Classic Wells score and fibrin fibrinogen degradation products show a significant interaction with patient age in a logistic regression model.

Clinical benefit of power-injectable port systems: a prospective observational study.

OBJECTIVE: To prospectively evaluate the clinical benefit of a central venous port system, which is approved for contrast media injection during contrast enhanced computed tomography. MATERIALS AND METHODS: At a university teaching hospital, 98 patients (59 female, 39 male; median age 61.7 years; range 23-83) had a power-injectable central venous port catheter system implanted. All implantations were performed under ultrasonographic and fluoroscopic guidance by interventional radiologists. Procedure related immediate (up to 24 h after implantation), early (<30 days after implantation) and late complications were documented. The frequency of port system use for contrast enhanced computed tomography scans was also considered. Any port capsule migration was assessed indirectly by determining the catheter tip position. The intended follow-up period was 180 days. RESULTS: An overall complication rate of 0.69 for 1,000 catheter days in 78 evaluated ports was recorded (12 ports affected, 15.4%). During the observational period, 40 of 104 contrast enhanced computed tomography scans were performed utilizing the port for contrast media administration (38.5%). 30 catheter tip retractions of more than 3 cm were observed in 82 patients (36.6%). Overall, tip dislocations were statistically more frequent in the female subgroup. CONCLUSION: The complication rate found in this study is comparable to those, which have been published for standard port systems. The utilization of the device for contrast media injection during contrast enhanced computed tomography scans should be increased. Finally, the port capsule has to be carefully positioned and fixed to prevent migration.

Evaluation of radiologically implanted central venous port systems explanted due to complications.

PURPOSE: The aim of this study was to evaluate explantations of central venous port systems that were implanted by interventional radiologists in cases where complications demanded the removal of the port device. METHODS: In this retrospective single-center study, explantation rates of central venous port catheter systems (CVPS) associated with complications were investigated over a 10-year period. All CVPS were implanted and explanted in our radiology department's interventional suite. Port catheter dysfunctions were divided into early and late complications, as well as into nonthrombotic and thrombotic events. Indications for implantation and explantation as well as clinical demographics were considered. RESULTS: One hundred and ninety-three CVPS were removed from 182 patients, due to complications. The total indwelling time of all CVPS was 55,132 catheter-days (mean 285.7; range 1-2,704). The most common diagnoses were gastrointestinal cancers 77 (39.9%) and hematological malignancies 32 (16.6%). Bloodstream infections 134 (69.4%) were the most common indication for the explantation procedure. These were followed by catheter-related thrombosis 28 (14.5%), nonthrombotic CVPS dysfunction 18 (9.3%), port pocket infections 9 (4.7%), and others 4 (2.1%). The highest percentages of explantations related to bloodstream infections were observed in patients with malabsorption (81.8%) and hematological malignancies (81.3%). CONCLUSION: Bloodstream infections were the most common cause for port explantation, followed by catheter-related thrombosis. Complication-related explantations were mainly for late-onset complications. Prevention and management strategies should be applied regarding care and usage of port systems to reduce the rate of complication-related explantations.

Outcome analysis in 3,160 implantations of radiologically guided placements of totally implantable central venous port systems.

OBJECTIVES: In this retrospective study the success and complication rates after radiologically guided port catheter implantation were evaluated. METHODS: Between 2000 and 2008, 3,160 port catheter systems were implanted in our interventional suite. All interventions were imaging guided. The puncture of the preferably right internal jugular vein (IJV) was ultrasound-assisted and the catheter tip position was controlled with fluoroscopy. Catheter indwelling time and rates of periprocedural, early and late complications were evaluated. RESULTS: 922,599 catheter days (mean, 292 days; range, 0-2,704 days) were documented. The implantation was successful in 3,153 (99.8%) cases. A total of 374 (11.8%; 0.41/1,000 catheter days) adverse events were recorded. Of these, 42 (1.33%) were periprocedural complications. 86 (3.3%; 0.09/1,000 catheter days) early and 246 (9.4%; 0.27/1,000 catheter days) late onset complications occurred after port implantation. The most common complications were blood stream infection (n = 134; 5.1%; 0.15/1,000 catheter days), catheter-induced venous thrombosis (n = 97; 3.7%; 0.11/1,000 catheter days) and catheter migration (n = 34; 1.3%; 0.04/1,000 catheter days). A total of 193 (6.1%) port explantations were required. CONCLUSION: Ultrasound guided port implantation via the IJV results in low periprocedural complication rates.

Double-lumen central venous port catheters: simultaneous application for chemotherapy and parenteral nutrition in cancer patients.

PURPOSE: This study was designed to evaluate the clinical benefit of low-profile double-lumen port catheters in patients receiving simultaneous chemotherapy and parenteral nutrition (PN). Potential advantages, complications, and the durations of simultaneous and single use of the catheter were assessed. METHODS: At a university teaching hospital, 10 patients received a double-lumen port catheter (5 men, 5 women; mean age 61.5 ± 12 years). All port implantations were performed under ultrasonographic and fluoroscopic guidance in the radiologic interventional suite. Procedure-related immediate, early, and late complications were recorded until removal of the device, patient's death, or completion of follow-up period. Application times and durations for chemotherapy or PN were determined. RESULTS: No immediate complications were observed. First use of the port system for chemotherapy was within 12 days (± 25 days, range 0-84 days) and within 17 hours (± 22 hours, range 0-72 hours) for PN on average. During the application of PN, no delay or interruption of chemotherapy was observed. The port catheter was used for the simultaneous application of chemotherapy and PN for a total of 1,216 hours. One port catheter was removed after 30 days due to suspected port infection. CONCLUSION: Central venous double-lumen port systems as a therapeutic option in patients requiring chemotherapy and PN can increase safety during those simultaneous applications, while offering improved patient comfort.