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.

The role of parametric feature maps to correct different volume of interest sizes: an in vivo liver MRI study.

BACKGROUND: Different volume of interest (VOI) sizes influence radiomic features. This study examined if translating images into feature maps before feature sampling could compensate for these effects in liver magnetic resonance imaging (MRI). METHODS: T1- and T2-weighted sequences from three different scanners (two 3-T scanners, one 1.5-T scanner) of 66 patients with normal abdominal MRI were included retrospectively. Three differently sized VOIs (10, 20, and 30 mm in diameter) were drawn in the liver parenchyma (right lobe), excluding adjacent structures. Ninety-three features were extracted conventionally using PyRadiomics. All images were also converted to 93 parametric feature maps using a pretested software. Agreement between the three VOI sizes was assessed with overall concordance correlation coefficients (OCCCs), while OCCCs > 0.85 were rated reproducible. OCCCs were calculated twice: for the VOI sizes of 10, 20, and 30 mm and for those of 20 and 30 mm. RESULTS: When extracted from original images, only 4 out of the 93 features were reproducible across all VOI sizes in T1- and T2-weighted images. When the smallest VOI was excluded, 5 features (T1-weighted) and 7 features (T2-weighted) were reproducible. Extraction from parametric maps increased the number of reproducible features to 9 (T1- and T2-weighted) across all VOIs. Excluding the 10-mm VOI, reproducibility improved to 16 (T1-weighted) and 55 features (T2-weighted). The stability of all other features also increased in feature maps. CONCLUSIONS: Translating images into parametric maps before feature extraction improves reproducibility across different VOI sizes in normal liver MRI. RELEVANCE STATEMENT: The size of the segmented VOI influences the feature quantity of radiomics, while software-based conversion of images into parametric feature maps before feature sampling improves reproducibility across different VOI sizes in MRI of normal liver tissue. KEY POINTS: • Parametric feature maps can compensate for different VOI sizes. • The effect seems dependent on the VOI sizes and the MRI sequence. • Feature maps can visualize features throughout the entire image stack.

First successful treatment of Clostridium perfringens-associated emphysematous hepatitis: a case report.

Emphysematous diseases of the abdomen are rare with an often inconspicuous presentation of symptoms and rapid lethal outcome if untreated. We report the first successfully treated case of Clostridium perfringens-associated emphysematous hepatitis. In the emergency room, a 79-year-old man presented with shortness of breath and deteriorated general condition since the morning of admission. Initial CT scans showed a small but rapidly expanding gas collection in liver segment 6. Emergency surgery with atypical liver resection was performed immediately. With early resection and prolonged administration of antibiotics in the presence of sepsis, the patient recovered successfully and was discharged 37 days after admission. As in our case, prompt diagnosis with early surgical treatment is crucial for the management of emphysematous hepatitis.

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.

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.

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.

Diagnostic Performance and Reliability of Non-Enhanced Imaging Characterization Quotients for the Differentiation of Infectious and Malignant Pulmonary Nodules in Hematological Patients Using 3T MRI.

PURPOSE: To evaluate the diagnostic performance and reliability of non-enhanced imaging characterization quotients (NICQs) derived from magnetic resonance imaging (MRI) in the differential diagnosis of pulmonary nodules in hematological patients. MATERIALS AND METHODS: A total of 83 lesions in 45 consecutive hematological patients were analyzed (10 bacterial pneumonias, 16 fungal pneumonias, 19 pulmonary lymphoma manifestations). The MRI protocol included T2-weighted single-shot fast spin echo (FSE) and T1-weighted gradient echo (GRE) sequences. T2-based T2-NICQmean and T2-NICQ90th were calculated from signal intensities measured in the lesion, muscle, and fat ((SILesion - SIMuscle)/(SIFat - SIMuscle) * 100), and simple T1-based T1-Qmean from signal intensities of the lesion and muscle (SILesion/SIMuscle). Images were read by one radiologist with > 7 years and one with 1 year of experience. For statistical evaluation the Kruskal-Wallis or Mann-Whitney U-test, receiver operating characteristic (ROC) analysis with calculation of areas under the curve (AUC), and intraclass correlation coefficients (ICCs) were used. RESULTS: Medians of T2-NICQs differed significantly when comparing infectious lesions and lymphoma manifestations in general (T2-NICQmean 20.33 vs. 10.14; T2-NICQ90th 34.96 vs. 25.52) or fungal lesions and lymphoma manifestations in particular (T2-NICQmean 19.00 vs. 10.14; T2-NICQ90th 34.49 vs. 25.25). The AUCs for T2-NICQs on the per-patient level ranged from 0.73 to 0.79. ICCs were at least > 0.85, except for intrarater testing of T2-NICQ90th (0.79). CONCLUSION: The overall diagnostic performance of T2-NICQs is adequate for differentiating infectious and fungal lesions from lymphoma manifestations. The results show good to excellent intra- and interrater agreement. We therefore consider NICQs helpful in the diagnostic workup of pulmonary nodules in hematological patients. KEY POINTS: · Non-enhanced Imaging Characterization Quotients provide a fast and pragmatic approach for assessing pulmonary lesions in hematological patients.. · The diagnostic performance of Non-enhanced Imaging Characterization Quotients is adequate for differentiating infectious and fungal infiltrates from lymphoma manifestations.. · Non-enhanced Imaging Characterization Quotients show good to excellent intra- and interrater agreement.. CITATION FORMAT: · Nagel SN, Kim D, Wylutzki T et al. Diagnostic Performance and Reliability of Non-Enhanced Imaging Characterization Quotients for the Differentiation of Infectious and Malignant Pulmonary Nodules in Hematological Patients Using 3T MRI. Fortschr Röntgenstr 2020; 192: 327 - 334.

Magnetic resonance imaging features of craniofacial fibrous dysplasia.

PURPOSE: To assess the value of magnetic resonance imaging (MRI) in detecting craniofacial fibrous dysplasia (CFD) and diagnosing and differentiating it from intraosseous meningioma. Additionally, the MRI appearance of the typical computed tomography (CT) imaging feature, the ground glass phenomenon, was evaluated. MATERIAL AND METHODS: MRI datasets of 32 patients with CFD were analysed retrospectively. Detectability in MRI was assessed by analysis of 10 randomly selected patients with CFD and 10 normal controls by two blinded readers. Changes of affected bone, internal lesion structure, T1 and T2 signal intensity, and contrast enhancement of the lesion in general and ground glass areas in particular were assessed. Ten patients with intraosseous meningioma (one in each) served as differential diagnosis for CFD. RESULTS: All 10 CFD lesions were reliably detected in MRI. In 32 patients 36 CFD lesions were evaluated. In 66.7% CFD were iso- to hypointense in T1 and hyperintense in T2; this proportion was similar for ground glass areas (65.7%). Ground glass areas were more homogeneously structured than the whole CFD lesion in both T1 (100% vs. 56%, respectively) and T2 (91% vs. 61%, respectively). Contrast enhancement was found in 97% of complete CFD lesions and 93% of ground glass areas. The accuracy for CFD vs. intraosseous meningioma was 100% for 'no soft-tissue component' and 98% for 'bone broadening' in MRI. CONCLUSIONS: Distinct morphological changes of CFD are reliably detected in MRI and allow differentiation from intraosseous meningioma. Areas with ground glass phenomenon in CT show a predominantly homogenous internal structure in MRI with contrast enhancement.

Pulmonary MRI at 3T: Non-enhanced pulmonary magnetic resonance Imaging Characterization Quotients for differentiation of infectious and malignant lesions.

OBJECTIVE: To investigate 3T pulmonary magnetic resonance imaging (MRI) for characterization of solid pulmonary lesions in immunocompromised patients and to differentiate infectious from malignant lesions. MATERIALS AND METHODS: Thirty-eight pulmonary lesions in 29 patients were evaluated. Seventeen patients were immunocompromised (11 infections and 6 lymphomas) and 12 served as controls (4 bacterial pneumonias, 8 solid tumors). Ten of the 15 infections were acute. Signal intensities (SI) were measured in the lesion, chest wall muscle, and subcutaneous fat. Scaled SIs as Non-enhanced Imaging Characterization Quotients ((SILesion-SIMuscle)/(SIFat-SIMuscle)*100) were calculated from the T2-weighted images using the mean SI (T2-NICQmean) or the 90th percentile of SI (T2-NICQ90th) of the lesion. Simple quotients were calculated by dividing the SI of the lesion by the SI of chest wall muscle (e.g. T1-Qmean: SILesion/SIMuscle). RESULTS: Infectious pulmonary lesions showed a higher T2-NICQmean (40.1 [14.6-56.0] vs. 20.9 [2.4-30.1], p<0.05) and T2-NICQ90th (74.3 [43.8-91.6] vs. 38.5 [15.8-48.1], p<0.01) than malignant lesions. T1-Qmean was higher in malignant lesions (0.85 [0.68-0.94] vs. 0.93 [0.87-1.09], p<0.05). Considering infections only, T2-NICQ90th was lower when anti-infectious treatment was administered >24h prior to MRI (81.8 [71.8-97.6] vs. 41.4 [26.6-51.1], p<0.01). Using Youden's index (YI), the optimal cutoff to differentiate infectious from malignant lesions was 43.1 for T2-NICQmean (YI=0.42, 0.47 sensitivity, 0.95 specificity) and 55.5 for T2-NICQ90th (YI=0.61, 0.71 sensitivity, 0.91 specificity). Combining T2-NICQ90th and T1-Qmean increased diagnostic performance (YI=0.72, 0.77 sensitivity, 0.95 specificity). CONCLUSION: Considering each quotient alone, T2-NICQ90th showed the best diagnostic performance and could allow differentiation of acute infectious from malignant pulmonary lesions with high specificity. Combining T2-NICQ90th with T1-Qmean increased overall performance, especially regarding sensitivity.