Search

Objective: Our aim is to define the capabilities of radiomics in predicting pseudoprogression from pre-treatment MR images in patients diagnosed with high-grade gliomas using T1 non-contrast-enhanced and contrast-enhanced images., Material & Methods: In this retrospective IRB-approved study, image segmentation of high-grade gliomas was semi-automatically performed using 3D Slicer. Non-contrast-enhanced T1-weighted images and contrast-enhanced T1-weighted images were used prior to surgical therapy or radio-chemotherapy. Imaging data was split into a training sample and an independent test sample at random. We extracted 107 radiomic features by use of PyRadiomics. Feature selection and model construction were performed using Generalized Boosted Regression Models (GBM)., Results: Our cohort included 124 patients (female: n = 53), diagnosed with progressive (n = 61) and pseudoprogressive disease (n = 63) of primary high-grade gliomas. Based on non-contrast-enhanced T1-weighted images of the independent test sample, the mean area under the curve (AUC), mean sensitivity, mean specificity and mean accuracy of our model were 0.651 [0.576, 0.761], 0.616 [0.417, 0.833], 0.578 [0.417, 0.750] and 0.597 [0.500, 0.708] to predict the development of pseudoprogression. In comparison, the independent test data of contrast-enhanced T1-weighted images yielded significantly higher values of AUC = 0.819 [0.760, 0.872], sensitivity = 0.817 [0.750, 0.833], specificity = 0.723 [0.583, 0.833] and accuracy = 0.770 [0.687, 0.833]., Conclusion: Our findings show that it is possible to predict pseudoprogression of high-grade gliomas with a Radiomics model using contrast-enhanced T1-weighted images with comparatively good discriminatory power. The use of a contrast agent results in a clear added value., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Our aim is to define the capabilities of radiomics and machine learning in predicting pseudoprogression development from pre-treatment MR images in a patient cohort diagnosed with high grade gliomas. In this retrospective analysis, we analysed 131 patients with high grade gliomas. Segmentation of the contrast enhancing parts of the tumor before administration of radio-chemotherapy was semi-automatically performed using the 3D Slicer open-source software platform (version 4.10) on T1 post contrast MR images. Imaging data was split into training data, test data and an independent validation sample at random. We extracted a total of 107 radiomic features by hand-delineated regions of interest (ROI). Feature selection and model construction were performed using Generalized Boosted Regression Models (GBM). 131 patients were included, of which 64 patients had a histopathologically proven progressive disease and 67 were diagnosed with mixed or pure pseudoprogression after initial treatment. Our Radiomics approach is able to predict the occurrence of pseudoprogression with an AUC, mean sensitivity, mean specificity and mean accuracy of 91.49% [86.27%, 95.89%], 79.92% [73.08%, 87.55%], 88.61% [85.19%, 94.44%] and 84.35% [80.19%, 90.57%] in the full development group, 78.51% [75.27%, 82.46%], 66.26% [57.95%, 73.02%], 78.31% [70.48%, 84.19%] and 72.40% [68.06%, 76.85%] in the testing group and finally 72.87% [70.18%, 76.28%], 71.75% [62.29%, 75.00%], 80.00% [69.23%, 84.62%] and 76.04% [69.90%, 80.00%] in the independent validation sample, respectively. Our results indicate that radiomics is a promising tool to predict pseudo-progression, thus potentially allowing to reduce the use of biopsies and invasive histopathology., (© 2022. The Author(s).)

Online supplemental material is available for this article.

Background: In this study, we investigated the hemodynamic changes in patients with aneurysmal subarachnoid hemorrhage (aSAH) during the intensive care unit and the effects of PiCCO on the hemodynamic clinical course during hydration and hypertension treatment., Methods: In our study, 15 adult aSAH patients, whose aneurysm had been treated by surgery or coiling, were examined for the signs of vasospasm in between the dates 03/01/2015 and 01/03/2016. The PICCO measurement was made at least twice in a day. Positive daily fluid balance was attempted to be at least 1000 mL and the value of the Global end-diastolic index (GEDI) was targeted to 680 to 800 mL/m2 for each patient. The values of mean arterial pressure (MAP), systolic arterial pressure (SAP), heart rate (HR), central venous pressure (CVP), and cardiac index (CI), GEDI, systemic vascular resistance index (SVRI), extravascular lung water index (ELWI) measured by PiCCO, and daily neurological outcome of patients and GCS values were recorded., Results: It had been observed that CVP value was randomly changing during the volume therapy, but the GEDI value determined by thermodilution was consistent. A positive correlation was detected between the period of reaching the hospital and the first measured value of SVRI. Low GEDI value was detected as a risk factor in the perspective of vasospasm, but an ideal GEDI value could not be determined., Conclusion: GEDI values were correlated with daily fluid balance. While low GEDI value was found as a risk factor, we could not determine an ideal GEDI value.

Objective: Surgical stress combined with general anaesthesia (GA) suppresses the immune system and leads to cancer cell growth and premature metastasis in major oncological interventions. Epidural analgesia decreases the need for inhalation agents and opioids during surgery by suppressing sympathetic and neuroendocrine responses in the postoperative period. This study aimed to compare the effects of combined general/epidural anaesthesia (GEA)+patient-controlled epidural analgesia (PCEA) and GA+IV patient-controlled analgesia (PCA) on serum tumour necrosis factor-alpha TNF-α), interleukin-1 beta (IL-1β) and interferon-gamma (IFN-γ) levels in patients undergoing radical cystectomy., Methods: Sixty-five patients were enrolled in this prospective study. Patients were randomly enrolled to the GEA group, i.e., combined GEA+ PCEA (0.1% bupivacaine+1 μg mL -1 fentanyl), and the GA group, namely combined GA+IV PCA (0.03 mg mL -1 morphine). To evaluate the cytokine response, blood samples were collected at preoperative, postoperative 1 st and 24 th hours., Results: There was no statistically significant difference in serum TNF-α, IL-1β and IFN-γ levels between groups GA and GEA at preoperative and postoperative 1 st hour and 24 th hour. Total remifentanil consumption was significantly lower and length of hospital stay was significantly shorter in the GEA group than in the GA group (p<0.05)., Conclusion: There is no difference between two anaesthesia methods in terms of serum cytokine levels; however, combined GEA+PCEA technique appeared to be superior to GA+IV PCA because of lower intraoperative narcotic analgesic consumption and shorter hospital stay., Competing Interests: Conflict of Interest: No conflict of interest was declared by the authors.