Impact of radiomics features, pulmonary emphysema score and muscle mass on the rate of pneumothorax and chest tube insertion in CT-guided lung biopsies.

Iatrogenic pneumothorax is a relevant complication of computed tomography (CT)-guided percutaneous lung biopsy. The aim of the present study was to analyze the prognostic significance of texture analysis, emphysema score and muscle mass derived from CT-imaging to predict postinterventional pneumothorax after CT-guided lung biopsy. Consecutive patients undergoing CT-guided percutaneous lung biopsy between 2012 and 2021 were analyzed. Multivariate logistic regression analysis included clinical risk factors and CT-imaging features to detect associations with pneumothorax development. Overall, 479 patients (178 females, mean age 65 ± 11.7 years) underwent CT-guided percutaneous lung biopsy of which 180 patients (37.5%) developed pneumothorax including 55 patients (11.5%) requiring chest tube placement. Risk factors associated with pneumothorax were chronic-obstructive pulmonary disease (COPD) (p = 0.03), age (p = 0.02), total lung capacity (p < 0.01) and residual volume (p = 0.01) as well as interventional parameters needle length inside the lung (p < 0.001), target lesion attached to pleura (p = 0.04), and intervention duration (p < 0.001). The combined model demonstrated a prediction accuracy of the occurrence of pneumothorax with an AUC of 0.78 [95%CI: 0.70-0.86] with a resulting sensitivity 0.80 and a specificity of 0.66. In conclusion, radiomics features of the target lesion and the lung lobe CT-emphysema score are predictive for the occurrence of pneumothorax and need for chest insertion after CT-guided lung biopsy.

Computed Tomography-Defined Body Composition as Prognostic Parameter in Acute Mesenteric Ischemia.

INTRODUCTION: Body composition comprising low-skeletal muscle mass (LSMM) and subcutaneous and visceral adipose tissue (SAT and VAT) can be assessed by using cross-sectional imaging modalities. Previous analyses suggest that these parameters harbor prognostic relevance in various diseases. Aim of this study was to analyze possible associations of body composition parameters on mortality in patients with clinically suspected acute mesenteric ischemia (AMI). METHODS: All patients with clinically suspected AMI were retrospectively assessed between 2016 and 2020. Overall, 137 patients (52 female patients, 37.9%) with a median age of 71 years were included in the present analysis. For all patients, the preoperative abdominal computed tomography (CT) was used to calculate LSMM, VAT, and SAT. RESULTS: Overall, 94 patients (68.6%) of the patient cohort died within 30 days within a median of 2 days, range 1-39 days. Of these, 27 patients (19.7%) died within 24 h. According to the CT, 101 patients (73.7%) were classified as being visceral obese, 102 patients (74.5%) as being sarcopenic, and 69 patients (50.4%) as being sarcopenic obese. Skeletal muscle index (SMI) was lower in non-survivors compared to survivors (37.5 ± 12.4 cm2/m2 vs. 44.1 ± 13.9 cm2/m2, p = 0.01). There were no associations between body composition parameters with mortality in days (SMI r = 0.07, p = 0.48, SAT r = -0.03, p = 0.77, and VAT r = 0.04, p = 0.68, respectively). In Cox regression analysis, a nonsignificant trend for visceral obesity was observed (HR: 0.62, 95% CI: 0.36-1.05, p = 0.07). CONCLUSION: SMI might be a valuable CT-based parameter, which could help discriminate between survivors and non-survivors. Further studies are needed to elucidate the associations between body composition and survival in patients with AMI.

CT Texture analysis and CT scores for characterization of fluid collections.

BACKGROUND: Texture analysis derived from Computed tomography (CT) might be able to better characterize fluid collections undergoing CT-guided percutaneous drainage treatment. The present study tested, whether texture analysis can reflect microbiology results in fluid collections suspicious for septic focus. METHODS: Overall, 320 patients with 402 fluid collections were included into this retrospective study. All fluid collections underwent CT-guided drainage treatment and were microbiologically evaluated. Clinically, serologically parameters and conventional imaging findings as well as textures features were included into the analysis. A new CT score was calculated based upon imaging features alone. Established CT scores were used as a reference standard. RESULTS: The present score achieved a sensitivity of 0.78, a specificity of 0.69, area under curve (AUC 0.82). The present score and the score by Gnannt et al. (AUC 0.81) were both statistically better than the score by Radosa et al. (AUC 0.75). Several texture features were statistically significant between infected fluid collections and sterile fluid collections, but these features were not significantly better compared with conventional imaging findings. CONCLUSIONS: Texture analysis is not superior to conventional imaging findings for characterizing fluid collections. A novel score was calculated based upon imaging parameters alone with similar diagnostic accuracy compared to established scores using imaging and clinical features.

MRI Texture Analysis of Inguinal Lymph Node Metastasis in Vulvar Cancer - Associations With Histopathology.

BACKGROUND/AIM: Texture analysis is a quantitative imaging technique that provides novel biomarkers beyond conventional image reading. This study aimed to investigate the correlation between texture parameters and histopathological features of lymph nodes in patients with vulvar cancer. PATIENTS AND METHODS: Overall, nine female patients (mean age 70.1±13.4 years, range=39-87 years) were included in the analysis. All patients had squamous cell carcinomas and underwent upfront surgery with inguinal lymph node resection. Immunohistochemical assessment was performed using several markers of the epithelial-mesenchymal transition. The presurgical magnetic resonance imaging (MRI) was analyzed with the MaZda package. RESULTS: In discrimination analysis, several parameters derived from T1-weighted images showed statistically significant differences between non-metastatic and metastatic lymph nodes. The highest statistical significance was reached by the texture feature "S(0,3)InvDfMom" (p=0.016). In correlation analysis, significant associations were found between MRI texture parameters derived from both T1-weighted and T2-weighted images and the investigated histopathological features. Notably, S(0,3)InvDfMom derived from T1-weighted images highly correlated with the Vimentin-score (r=0.908, p=0.001). CONCLUSION: Several associations between MRI texture analysis and immunohistochemical parameters were identified in metastasized lymph nodes of cases with vulvar cancer.

Diagnostic accuracy and reliability of CT-based Node-RADS for colon cancer.

OBJECTIVE: The Node-RADS classification was recently published as a classification system to better characterize lymph nodes in oncological imaging. The present analysis investigated the diagnostic benefit of the Node-RADS classification of staging computed tomography (CT) images to categorize and stage lymph nodes in patients with colon cancer. MATERIALS AND METHODS: All patients were surgically resected and the lymph nodes were histopathological analyzed. All investigated lymph nodes were scored in accordance to the Node-RADS classification by two experienced radiologists. Interreader variability was assessed with Cohen's kappa analysis, discrimination analysis was performed with Mann-Whitney-U test and diagnostic accuracy was assessed with receiver-operating characteristics (ROC) curve analysis. RESULTS: Overall, 108 patients (n = 49 females, 45.3%) with a mean age of 70.08 ± 14.34 years were included. In discrimination analysis, the total Node-RADS score showed statistically significant differences between N- and N + stage (for reader 1: mean 1.89 ± 1.09 score for N- versus 2.93 ± 1.62 score for N+, for reader 2: 1.33 ± 0.48 score for N- versus 3.65 ± 0.94 score for N+, p = 0.001, respectively). ROC curve analysis for lymph node discrimination showed an area under the curve of 0.68. A threshold value of 2 resulted in a sensitivity of 0.62 and a specificity of 0.71. CONCLUSION: Node-RADS score derived from staging CT shows only limited diagnostic accuracy to correctly predict nodal positivity in colon cancer. The interreader variability seems to be high and should question the clinical translation for this tumour entity.

Impact of quantitative CT texture analysis on the outcome of CT-guided bone biopsy.

Texture analysis can provide new imaging-based biomarkers. Texture analysis derived from computed tomography (CT) might be able to better characterize patients undergoing CT-guided percutaneous bone biopsy. The present study evaluated this and correlated texture features with bioptic outcome in patients undergoing CT-guided bone biopsy. Overall, 123 patients (89 female patients, 72.4 %) were included into the present study. All patients underwent CT-guided percutaneous bone biopsy with an 11 Gauge coaxial needle. Clinical parameters and quantitative imaging features were investigated. Random forest classifier was used to predict a positive biopsy result. Overall, 69 patients had osteolytic metastasis (56.1 %) and 54 had osteoblastic metastasis (43.9 %). The overall positive biopsy rate was 72 %. The developed radiomics model demonstrated a prediction accuracy of a positive biopsy result with an AUC of 0.75 [95 %CI 0.65 - 0.85]. In a subgroup of breast cancer patients, the model achieved an AUC of 0.85 [95 %CI 0.73 - 0.96]. In the subgroup of non-breast cancer patients, the signature achieved an AUC of 0.80 [95 %CI 0.60 - 0.99]. Quantitative CT imaging findings comprised of conventional and texture features can aid to predict the bioptic result of CT-guided bone biopsies. The developed radiomics signature aids in clinical decision-making, and could identify patients at risk for a negative biopsy.

Impact of CT texture analysis on complication rate in CT-guided liver biopsies.

Aim of the study: Texture analysis derived from computed tomography (CT) involves quantitative imaging parameters characterizing possible valuable associations with clinical purposes. Their prognostic capability in patients undergoing percutaneous CT-guided liver biopsy to identify associations with postinterventional bleeding complications and biopsy success is not sufficiently explored. Material and methods: Three hundred fifteen patients (124 female, 39%) with a mean age of 62.5 ±10.2 years underwent percutaneous CT-guided liver biopsy and were analyzed regarding clinical, procedure-related, and CT texture features. Results: Thirty patients (9.5%) presented with bleeding after biopsy (including two requiring interventional treatment), whereas 46 patients (14.6%) had negative biopsy successes. Distance of lesion from liver capsule was statistically significantly different in patients with and without bleeding (p = 0.015). Several texture features were statistically significantly different between the groups, S(0,1)SumAverg having the highest significance (p = 0.004). Regarding unsuccessful biopsy results, liver fibrosis was the only clinical feature with statistical significance (p = 0.049). Only two texture features (S(4,-4)InvDfMom and Teta3) were statistically different between the groups according to the biopsy result. Conclusions: Several CT texture features of the target lesion and the length from the capsule to the lesion were associated with bleeding complications after CT-guided percutaneous liver biopsy. This could be used to identify patients at risk at the beginning of the procedure.

Computed Tomography Embolus Texture Analysis as a Prognostic Marker of Acute Pulmonary Embolism.

Texture analysis is a quantitative imaging analysis that provides novel biomarkers beyond conventional image reading. Our aim was to use texture analysis of pulmonary emboli derived from thoracic computed tomography for prediction of mortality and prognosis of acute pulmonary embolism (PE). Overall, 216 patients (116 female, 53.7%) were included in the analysis. Texture analysis was calculated on axial slices of the contrast enhanced pulmonary angiography of the proximal embolus. Clinical scores, serological parameters, need for intubation, intensive care unit (ICU) admission and mortality was assessed and correlated with the texture features. In the correlation analysis, there were several associations with mortality in days, the highest for the parameter S(0,5)SumVarnc (r = -0.43, P < 0.001). Another parameter, S(3,-3)AngScMom correlated with sepsis-related organ failure assessment score (SOFA)-score (r = 0.31, P < 0.001). Several texture features correlated with venous lactate and glucose levels. In discrimination analysis, there were significant differences in regard to texture features between survivors and non-survivors and between patients with and without the need for ICU admission (P = 0.02, respectively). These results highlight the potential clinical benefit of texture features in patients with acute PE as novel imaging biomarkers. Further studies are needed to validate these results.

CT Texture Analysis and Node-RADS CT Score of Lymph Nodes in Patients With Perihilar Cholangiocarcinoma.

BACKGROUND/AIM: Texture analysis can provide quantitative imaging markers from computed tomography (CT) images. The Node-RADS classification was recently published as a classification system to better characterize lymph nodes in oncological imaging. The present analysis investigated the diagnostic benefit of CT texture analysis and the Node-RADS classification to categorize and stage lymph nodes in patients with perihilar cholangiocarcinoma. PATIENTS AND METHODS: Overall, 25 patients (n=9 females, 36%) with a mean age of 72.4±8.1 years were included. All patients were surgically resected and the lymph nodes were histopathologically analyzed. CT-texture analysis was performed with the Mazda package. All investigated lymph nodes were scored in accordance with the Node-RADS classification. RESULTS: Regarding lymph node discrimination (N- versus N+), Node-RADS classification achieved an area under the curve (AUC) of 0.86 resulting in a sensitivity of 78% and a specificity of 86%. Multiple investigated texture features were different between negative and positive lymph nodes. The "S(0,1)SumVarnc" achieved the best AUC of 0.75 resulting in a sensitivity of 0.91 and a specificity of 0.67. Correlation analysis showed various statistically significant associations between CT texture features and Node-RADS score. CONCLUSION: Several CT texture features and the Node-RADS score derived from preoperative staging CT were associated with the malignancy of the hilar lymph nodes and might aid for preoperative staging. This could change surgical treatment planning in hilar cholangiocarcinoma.

Computed tomography texture analysis to discriminate fungal and non-fungal infected fluid collections.

Purpose: Texture analysis of computed tomography (CT) can aid in characterization of fluid collections providing biomarkers. The present study tested whether texture analysis can discriminate between fungal or non-fungal infection in patients undergoing CT-guided percutaneous drainage treatment. Approach: Overall, 214 patients [(n=76 females, 35.5%); mean age 62±14 years and range 20 to 94 years] with 255 fluid collections were included in the analysis. All patients underwent CT-guided drainage treatment and were evaluated with microbiological analysis. CT texture analysis was performed with the MaZda package. Results: Only three of the investigated CT texture features were statistically significant different between the groups, namely kurtosis (p=0.04), S(3,3)InvDfMom (p=0.02), and S(5,-5)DifEntrp (p=0.003). These texture features were further investigated by the receiver operating characteristic curve. S(3,3)InvDfMom achieved the highest accuracy with an area under the curve of 0.62, resulting in a sensitivity of 0.66 and a specificity of 0.57. Conclusion: Some CT texture features were different between fungal and non-fungal infected fluid collections. The diagnostic overlap is large, which could reduce the clinical benefit. Further studies are needed to identify the possible diagnostic benefit of texture analysis in these patients.

Analysis of Periprocedural X-ray Exposure in Transarterial Radioembolization with Glass or Resin Microspheres.

Background: Transarterial Radioembolization (TARE) is an effective treatment option for both primary and secondary liver malignancies. However, challenging anatomical conditions can lead to prolonged fluoroscopy times (FT), elevated doses of periprocedural X-radiation (DAP), and increased use of contrast agents (CAs). In this study, we examined the influence of our radiologists' experience and the choice of microspheres on X-ray exposure and CA doses in TARE. Material and Methods: Datasets comprising 161 TARE and 164 preprocedural evaluation angiographies (TARE-EVA) were analyzed. Our study focused on assessing DAP, FT, and CA concerning both microsphere types, the radiologist's experience, and whether the same radiologist performed both the TARE-EVA and the actual TARE. Results: In TARE, the use of resin microspheres resulted in significantly higher FT and CA compared to glass microspheres (14.3 ± 1.6 min vs. 10.6 ± 1.1 min and 43 ± 2.2 mL vs. 33.6 ± 2.1 mL, p < 0.05), with no notable differences in DAP (p = 0.13). Experienced radiologists demonstrated reduced FT/DAP, with a 19% decrease in DAP and 53% in FT during the evaluation angiography (p < 0.05) and a 49% reduction in DAP during the actual TARE (p < 0.05), with no statistical differences in FT. Performing TARE and TARE-EVA under the same radiologist led to a 43% reduction in DAP and a 25% decrease in FT (p < 0.05, respectively). Conclusions: To mitigate X-radiation exposure, it is advisable for radiologists to undergo thorough training, and, ideally, the same radiologist should conduct both the TARE and the TARE-EVA. While the use of glass spheres may decrease intraarterial CA, it does not significantly impact periprocedural X-ray exposure.

CT texture analysis and node-RADS CT score of mediastinal lymph nodes - diagnostic performance in lung cancer patients.

BACKGROUND: Texture analysis derived from computed tomography (CT) can provide clinically relevant imaging biomarkers. Node-RADS is a recently proposed classification to categorize lymph nodes in radiological images. The present study sought to investigate the diagnostic abilities of CT texture analysis and Node-RADS to discriminate benign from malignant mediastinal lymph nodes in patients with lung cancer. METHODS: Ninety-one patients (n = 32 females, 35%) with a mean age of 64.8 ± 10.8 years were included in this retrospective study. Texture analysis was performed using the free available Mazda software. All lymph nodes were scored accordingly to the Node-RADS classification. All primary tumors and all investigated mediastinal lymph nodes were histopathologically confirmed during clinical workup. RESULTS: In discrimination analysis, Node-RADS score showed statistically significant differences between N0 and N1-3 (p < 0.001). Multiple texture features were different between benign and malignant lymph nodes: S(1,0)AngScMom, S(1,0)SumEntrp, S(1,0)Entropy, S(0,1)SumAverg. Correlation analysis revealed positive associations between the texture features with Node-RADS score: S(4,0)Entropy (r = 0.72, p < 0.001), S(3,0) Entropy (r = 0.72, p < 0.001), S(2,2)Entropy (r = 0.72, p < 0.001). CONCLUSIONS: Several texture features and Node-RADS derived from CT were associated with the malignancy of mediastinal lymph nodes and might therefore be helpful for discrimination purposes. Both of the two quantitative assessments could be translated and used in clinical routine.

Magnetic Resonance Imaging of Peritoneal Carcinomatosis: Evaluation of High b-Value Computed Diffusion-Weighted Imaging.

Over the last few years, diffusion-weighted imaging (DWI) has become increasingly relevant in the diagnostic assessment of peritoneal carcinomatosis. The aim of this study was to investigate the benefits of high-b DWI (c-DWI) compared to standard DWI in patients with peritoneal carcinomatosis. A cohort of 40 patients with peritoneal carcinomatosis were included in this retrospective study. DWI was performed with b-values of 50, 400, and 800 or 1000 s/mm² on a 1.5-T magnetic resonance imaging (MRI) scanner. C-DWI was calculated using a mono-exponential model with high b-values of 1000, 2000, 3000, 4000, and 5000 s/mm². All c-DWI images with high b-values were compared in terms of volume, detectability of peritoneal lesions, and image quality with the DWI sequence acquired with a b-value of 800 or 1000 s/mm² by two readers. In the group with a b-value of 800 s/mm², there was no statistically significant difference in terms of lesion volume. In the second group with a b-value of 1000 s/mm², peritoneal carcinomatosis lesions were statistically significantly larger than in the c-DWI with a- high b-value of 2000 s/mm² (median 7 cm³, range 1−26 cm³vs. median 6 cm³, range 1−83 cm³, p < 0.05). In both groups, there was a marked decrease in the detectability of peritoneal lesions starting at b = 2000 s/mm². In addition, image quality decreased noticeably from c-DWI at b = 3000 s/mm². In both groups, all images with high b-values at b = 4000 s/mm² and 5000 s/mm² were not diagnostically valuable due to poor image quality. The c-DWI technique offers good diagnostic performance without additional scanning time. High c-DWI b-values up to b = 1000 s/mm² provide comparable detectability of peritoneal carcinomatosis compared to standard DWI. Higher b-values over 1500 s/mm² result in lower image quality, which might lead to misdiagnosis.

Differential Diagnosis Between Alzheimer's Disease-Related Depression and Pseudo-Dementia in Depression: A New Indication for Amyloid-ß Imaging?

BACKGROUND: Alzheimer's disease and depression can start with combined cognitive and depressive symptoms [1, 2]. Accurate differential diagnosis is desired to initiate specific treatment. OBJECTIVE: We investigated whether amyloid-ß PET imaging can discriminate both entities. METHODS: This retrospective observational study included 39 patients (20 female, age = 70±11years) with both cognitive and depressive symptoms who underwent amyloid-ß PET imaging and in whom clinical follow-up data was available. Amyloid-ß PET was carried out applying [18F]Florbetaben or [11C]PiB. The PET images were analyzed by standardized visual and relative-quantitative evaluation. Based on clinical follow-up (median of 2.4 years [range 0.3 to 7.0 years, IQR = 3.7 years] after amyloid PET imaging which was not considered in obtaining a definite diagnosis), discrimination ability between AD-related depression and pseudo-dementia in depression/depression with other comorbidities was determined. RESULTS: Visually, all 10 patients with pseudo-dementia in depression and all 15 patients with other depression were rated as amyloid-ß-negative; 2 of 14 patients with AD-related depression were rated amyloid-ß-negative. ROC curve analysis of the unified composite standardized uptake value ratios (cSUVRs) was able to discriminate pseudo-dementia in depression from AD-related depression with high accuracy (AUC = 0.92). Optimal [18F]Florbetaben discrimination cSUVR threshold was 1.34. In congruence with the visual PET analysis, the resulting sensitivity of the relative-quantitative analysis was 86% with a specificity of 100%. CONCLUSION: Amyloid-ß PET can differentiate AD-related depression and pseudo-dementia in depression. Prospective clinical studies are warranted to confirm this result and to potentially broaden the spectrum of clinical applications for amyloid-ß PET imaging.

CT Texture Analysis of Pulmonary Neuroendocrine Tumors-Associations with Tumor Grading and Proliferation.

Texture analysis derived from computed tomography (CT) might be able to provide clinically relevant imaging biomarkers and might be associated with histopathological features in tumors. The present study sought to elucidate the possible associations between texture features derived from CT images with proliferation index Ki-67 and grading in pulmonary neuroendocrine tumors. Overall, 38 patients (n = 22 females, 58%) with a mean age of 60.8 ± 15.2 years were included into this retrospective study. The texture analysis was performed using the free available Mazda software. All tumors were histopathologically confirmed. In discrimination analysis, "S(1,1)SumEntrp" was significantly different between typical and atypical carcinoids (mean 1.74 ± 0.11 versus 1.79 ± 0.14, p = 0.007). The correlation analysis revealed a moderate positive association between Ki-67 index with the first order parameter kurtosis (r = 0.66, p = 0.001). Several other texture features were associated with the Ki-67 index, the highest correlation coefficient showed "S(4,4)InvDfMom" (r = 0.59, p = 0.004). Several texture features derived from CT were associated with the proliferation index Ki-67 and might therefore be a valuable novel biomarker in pulmonary neuroendocrine tumors. "Sumentrp" might be a promising parameter to aid in the discrimination between typical and atypical carcinoids.