Utility of diffusion tensor imaging and generalized q-sampling imaging for predicting short-term clinical effect of deep brain stimulation in Parkinson's disease.

PURPOSE: To assess whether diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) metrics could preoperatively predict the clinical outcome of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). METHODS: In this single-center retrospective study, from September 2021 to March 2023, preoperative DTI and GQI examinations of 44 patients who underwent DBS surgery, were analyzed. To evaluate motor functions, the Unified Parkinson's Disease Rating Scale (UPDRS) during on- and off-medication and Parkinson's Disease Questionnaire-39 (PDQ-39) scales were used before and three months after DBS surgery. The study population was divided into two groups according to the improvement rate of scales: ≥ 50% and < 50%. Five target regions, reported to be affected in PD, were investigated. The parameters having statistically significant difference were subjected to a receiver operating characteristic (ROC) analysis. RESULTS: Quantitative anisotropy (qa) values from globus pallidus externus, globus pallidus internus (qa_Gpi), and substantia nigra exhibited significant distributional difference between groups in terms of the improvement rate of UPDRS-3 scale during on-medication (p = 0.003, p = 0.0003, and p = 0.0008, respectively). In ROC analysis, the best parameter in predicting DBS response included qa_Gpi with a cut-off value of 0.01370 achieved an area under the ROC curve, accuracy, sensitivity, and specificity of 0.810, 73%, 62.5%, and 85%, respectively. Optimal cut-off values of ≥ 0.01864 and ≤ 0.01162 yielded a sensitivity and specificity of 100%, respectively. CONCLUSION: The imaging parameters acquired from GQI, particularly qa_Gpi, may have the ability to non-invasively predict the clinical outcome of DBS surgery.

Reproducibility of rCBV in glioblastomas using T2*-weighted perfusion MRI: an evaluation of sampling, normalization, and experience.

PURPOSE: The reproducibility of relative cerebral blood volume (rCBV) measurements among readers with different levels of experience is a concern. This study aimed to investigate the inter-reader reproducibility of rCBV measurement of glioblastomas using the hotspot method in dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) with various strategies. METHODS: In this institutional review board-approved single-center study, 30 patients with glioblastoma were retrospectively evaluated with DSC-MRI at a 3.0 Tesla scanner. Three groups of reviewers, including neuroradiologists, general radiologists, and radiology residents, calculated the rCBV based on the number of regions of interest (ROIs) and reference areas. For statistical analysis of feature reproducibility, the intraclass correlation coefficient (ICC) and Bland-Altman plots were used. Analyses were made among individuals, reader groups, reader-group pooling, and a population that contained all of them. RESULTS: For individuals, the highest inter-reader reproducibility was observed between neuroradiologists [ICC: 0.527; 95% confidence interval (CI): 0.21-0.74] and between residents (ICC: 0.513; 95% CI: 0.20-0.73). There was poor reproducibility in the analyses of individuals with different levels of experience (ICC range: 0.296-0.335) and in reader-wise and group-wise pooling (ICC range: 0.296-0.335 and 0.397-0.427, respectively). However, an increase in ICC values was observed when five ROIs were used. In an analysis of all strategies, the ICC for the centrum semiovale was significantly higher than that for contralateral white matter (P < 0.001). CONCLUSION: The inter-reader reproducibility of rCBV measurement was poor to moderate regardless of whether it was calculated by neuroradiologists, general radiologists, or residents, which may indicate the need for automated methods. Choosing five ROIs and using the centrum semiovale as a reference area may increase reliability for all users.

Influence of image preprocessing on the segmentation-based reproducibility of radiomic features: in vivo experiments on discretization and resampling parameters.

PURPOSE: To systematically investigate the impact of image preprocessing parameters on the segmentation-based reproducibility of magnetic resonance imaging (MRI) radiomic features. METHODS: The MRI scans of 50 patients were included from the multi-institutional Brain Tumor Segmentation 2021 public glioma dataset. Whole tumor volumes were manually segmented by two independent readers, with the participation of eight readers. Radiomic features were extracted from two sequences: T2-weighted (T2) and contrast-enhanced T1-weighted (T1ce). Two methods were considered for discretization: bin count (i.e., relative discretization) and bin width (i.e., absolute discretization). Ten discretization (five for each method) and five resampling parameters were varied while other parameters were fixed. The intraclass correlation coefficient (ICC) was used for reliability analysis based on two commonly used cut-off values (0.75 and 0.90). RESULTS: Image preprocessing parameters had a significant impact on the segmentation-based reproducibility of radiomic features. The bin width method yielded more reproducible features than the bin count method. In discretization experiments using the bin width on both sequences, according to the ICC cut-off values of 0.75 and 0.90, the rate of reproducible features ranged from 70% to 84% and from 35% to 57%, respectively, with an increasing percentage trend as parameter values decreased (from 84 to 5 for T2; 100 to 6 for T1ce). In the resampling experiments, these ranged from 53% to 74% and from 10% to 20%, respectively, with an increasing percentage trend from lower to higher parameter values (physical voxel size; from 1 x 1 x 1 to 2 x 2 x 2 mm3). CONCLUSION: The segmentation-based reproducibility of radiomic features appears to be substantially influenced by discretization and resampling parameters. Our findings indicate that the bin width method should be used for discretization and lower bin width and higher resampling values should be used to allow more reproducible features.

Publications poorly report the essential RadiOmics ParametERs (PROPER): A meta-research on quality of reporting.

PURPOSE: To investigate the quality of reporting in radiomics research, with a focus on the most basic technical parameters. METHODS: A PubMed literature search was conducted to identify original studies on radiomics (last search: January 2, 2023). Following a sample size calculation with an a priori power analysis, a random sample of the radiomic literature was collected. In addition to baseline characteristics, the key aspects of radiomic software, resampling, and discretization were evaluated. Agreement between raters was analyzed. Disagreements were resolved through consensus. RESULTS: A sample of 87 publications was evaluated. Most publications (89%; 77/87) were retrospective. They were conducted predominantly with private data (87%; 76/87) at a single institution (77%; 67/87) without external validation (90%; 78/87). 69% (60/87) of the papers reported the radiomic software used (p < 0.001), with nearly half (43%; 26/60) omitting the version. 37% (32/87) reported the resampling size (p = 0.018), while 22% (7/32) did not report using iso-voxel resampling. 34% (30/87) reported the discretization parameters (p < 0.01), but more than three-quarters (77%; 23/30) did not experiment with different discretization parameters. A wide range of discretization parameter values were reported. Most papers (79%; 69/87) failed to report all three essential items simultaneously (p < 0.001). CONCLUSION: Even the essential radiomic parameters that are usually displayed on the user interface of radiomic software tools were poorly reported in radiomics-related publications. This issue of transparency may require additional action from researchers, editors, and reviewers in the form of adopting more stringent reporting standards (e.g., checklists, guidelines).

Predicting Isocitrate Dehydrogenase Mutation Status of Grade 2-4 Gliomas with Diffusion Tensor Imaging (DTI) Parameters Derived from Model-Based DTI and Model-Free Q-Sampling Imaging Reconstructions.

OBJECTIVE: To determine whether diffusion tensor imaging (DTI) parameters acquired with model-based DTI and model-free generalized Q-sampling imaging (GQI) reconstructions may noninvasively predict isocitrate dehydrogenase (IDH) mutational status in patients with grade 2-4 gliomas. METHODS: Forty patients with known IDH genotype (28 IDH wild-type; 12 IDH mutant) who underwent preoperative DTI evaluation on a 3-Tesla magnetic resonance imaging scanner were analyzed retrospectively. Absolute values obtained from model-based and model-free reconstructions were compared. Using the intraclass correlation coefficient, interobserver agreement was assessed for various sampling techniques. Variables having statistically significant distributions between IDH groups were subjected to a receiver operating characteristic (ROC) analysis. Using multivariable logistic regression analysis, independent predictors, if present, were identified and a model was developed. RESULTS: Six imaging parameters (3 from model-based DTI and 3 from model-free GQI reconstructions) showed statistically significant differences between groups (P < 0.001, power >0.97), with very high correlation to each other (P < 0.001). Age difference between the groups was statistically significant (P < 0.001). The optimal logistic regression model comprised a GQI-based parameter and age, which were independent predictors as well, producing an area under the ROC curve, accuracy, sensitivity, and specificity of 0.926, 85%, 75%, and 89.3%, respectively. Using the GQI reconstruction feature alone with a cut-off of 1.60, an 85% of accuracy was also achieved with ROC analysis. CONCLUSIONS: The imaging parameters acquired from model-based DTI and model-free GQI reconstructions, combined with the clinical variable age, may have the ability to noninvasively predict the IDH genotype in gliomas, either alone or in particular combinations.

REliability of consensus-based segMentatIoN in raDiomic feature reproducibility (REMIND): A word of caution.

OBJECTIVE: To evaluate the reliability of consensus-based segmentation in terms of reproducibility of radiomic features. METHODS: In this retrospective study, three tumor data sets were investigated: breast cancer (n = 30), renal cell carcinoma (n = 30), and pituitary macroadenoma (n = 30). MRI was utilized for breast and pituitary data sets, while CT was used for renal data set. 12 readers participated in the segmentation process. Consensus segmentation was created by making corrections on a previous region or volume of interest. Four experiments were designed to evaluate the reproducibility of radiomic features. Reliability was assessed with intraclass correlation coefficient (ICC) with two cut-off values: 0.75 and 0.9. RESULTS: Considering the lower bound of the 95% confidence interval and the ICC threshold of 0.90, at least 61% of the radiomic features were not reproducible in the inter-consensus analysis. In the susceptibility experiment, at least half (54%) became non-reproducible when the first reader is replaced with a different reader. In the intra-consensus analysis, at least about one-third (32%) were non-reproducible when the same second reader segmented the image over the same first reader two weeks later. Compared to inter-reader analysis based on independent single readers, the inter-consensus analysis did not statistically significantly improve the rates of reproducible features in all data sets and analyses. CONCLUSIONS: Despite the positive connotation of the word "consensus", it is essential to REMIND that consensus-based segmentation has significant reproducibility issues. Therefore, the usage of consensus-based segmentation alone should be avoided unless a reliability analysis is performed, even if it is not practical in clinical settings.

Early senescence and production of senescence-associated cytokines are major determinants of radioresistance in head-and-neck squamous cell carcinoma.

Resistance against radio(chemo)therapy-induced cell death is a major determinant of oncological treatment failure and remains a perpetual clinical challenge. The underlying mechanisms are manifold and demand for comprehensive, cancer entity- and subtype-specific examination. In the present study, resistance against radiotherapy was systematically assessed in a panel of human head-and-neck squamous cell carcinoma (HNSCC) cell lines and xenotransplants derived thereof with the overarching aim to extract master regulators and potential candidates for mechanism-based pharmacological targeting. Clonogenic survival data were integrated with molecular and functional data on DNA damage repair and different cell fate decisions. A positive correlation between radioresistance and early induction of HNSCC cell senescence accompanied by NF-κB-dependent production of distinct senescence-associated cytokines, particularly ligands of the CXCR2 chemokine receptor, was identified. Time-lapse microscopy and medium transfer experiments disclosed the non-cell autonomous, paracrine nature of these mechanisms, and pharmacological interference with senescence-associated cytokine production by the NF-κB inhibitor metformin significantly improved radiotherapeutic performance in vitro and in vivo. With regard to clinical relevance, retrospective analyses of TCGA HNSCC data and an in-house HNSCC cohort revealed that elevated expression of CXCR2 and/or its ligands are associated with impaired treatment outcome. Collectively, our study identifies radiation-induced tumor cell senescence and the NF-κB-dependent production of distinct senescence-associated cytokines as critical drivers of radioresistance in HNSCC whose therapeutic targeting in the context of multi-modality treatment approaches should be further examined and may be of particular interest for the subgroup of patients with elevated expression of the CXCR2/ligand axis.

Evaluation of the Achilles Tendon Using B-Mode Ultrasound and Strain Elastography in Patients With Chronic Kidney Disease.

OBJECTIVES: To investigate the B-mode ultrasound (US) features and elasticity of the Achilles tendon in patients with chronic kidney disease (CKD) using US elastography and to compare them with those of healthy individuals. METHODS: From March 2019 through May 2019, 30 consecutive patients with variable stages of CKD and 30 healthy individuals were prospectively included in this study. Ultrasound and strain elastographic examinations were performed on both Achilles tendons of all individuals. Degrees of tendinopathy, if existed, were classified as defined by Archambault et al (J Clin Ultrasound 1998; 26:335-339), and thicknesses were documented with US. Strain ratios (SRs) were calculated by measuring the strain values from the Achilles tendon and Kager fat pad. Statistical differences in the SRs of Achilles tendons between the control group and patients with CKD were calculated. RESULTS: The 30 patients with CKD ranged in age from 24 to 73 years, and the 30 healthy individuals ranged in age from 25 to 78 years. Both distal and left middle thirds of the Achilles tendons were thicker in patients with CKD than in healthy individuals (P < .05). The mean SRs ± SDs in the patient group (4.71 ± 0.95 and 4.85 ± 1.47 on the right and left, respectively) were significantly higher (P < .05) than in healthy individuals (2.31 ± 0.42 and 2.65 ± 0.55 on the right and left), which indicated an increased stiffness of Achilles tendons in the patient group. CONCLUSIONS: As a semiquantitative and noninvasive imaging modality, strain elastography has the potential to detect the morphologic and elasticity changes of Achilles tendons in patients with CKD, which may give an opportunity to help physicians predict possible leading partial or complete tears.

Loss of p53 function at late stages of tumorigenesis confers ARF-dependent vulnerability to p53 reactivation therapy.

Cancer development is driven by activated oncogenes and loss of tumor suppressors. While oncogene inhibitors have entered routine clinical practice, tumor suppressor reactivation therapy remains to be established. For the most frequently inactivated tumor suppressor p53, genetic mouse models have demonstrated regression of p53-null tumors upon p53 reactivation. While this was shown in tumor models driven by p53 loss as the initiating lesion, many human tumors initially develop in the presence of wild-type p53, acquire aberrations in the p53 pathway to bypass p53-mediated tumor suppression, and inactivate p53 itself only at later stages during metastatic progression or therapy. To explore the efficacy of p53 reactivation in this scenario, we used a reversibly switchable p53 (p53ERTAM) mouse allele to generate Eµ-Myc-driven lymphomas in the presence of active p53 and, after full lymphoma establishment, switched off p53 to model late-stage p53 inactivation. Although these lymphomas had evolved in the presence of active p53, later loss and subsequent p53 reactivation surprisingly activated p53 target genes triggering massive apoptosis, tumor regression, and long-term cure of the majority of animals. Mechanistically, the reactivation response was dependent on Cdkn2a/p19Arf, which is commonly silenced in p53 wild-type lymphomas, but became reexpressed upon late-stage p53 inactivation. Likewise, human p53 wild-type tumor cells with CRISPR-engineered switchable p53ERTAM alleles responded to p53 reactivation when CDKN2A/p14ARF function was restored or mimicked with Mdm2 inhibitors. Together, these experiments provide genetic proof of concept that tumors can respond, in an ARF-dependent manner, to p53 reactivation even if p53 inactivation has occurred late during tumor evolution.

Residual apoptotic activity of a tumorigenic p53 mutant improves cancer therapy responses.

Engineered p53 mutant mice are valuable tools for delineating p53 functions in tumor suppression and cancer therapy. Here, we have introduced the R178E mutation into the Trp53 gene of mice to specifically ablate the cooperative nature of p53 DNA binding. Trp53R178E mice show no detectable target gene regulation and, at first sight, are largely indistinguishable from Trp53-/- mice. Surprisingly, stabilization of p53R178E in Mdm2-/- mice nevertheless triggers extensive apoptosis, indicative of residual wild-type activities. Although this apoptotic activity suffices to trigger lethality of Trp53R178E ;Mdm2-/- embryos, it proves insufficient for suppression of spontaneous and oncogene-driven tumorigenesis. Trp53R178E mice develop tumors indistinguishably from Trp53-/- mice and tumors retain and even stabilize the p53R178E protein, further attesting to the lack of significant tumor suppressor activity. However, Trp53R178E tumors exhibit remarkably better chemotherapy responses than Trp53-/- ones, resulting in enhanced eradication of p53-mutated tumor cells. Together, this provides genetic proof-of-principle evidence that a p53 mutant can be highly tumorigenic and yet retain apoptotic activity which provides a survival benefit in the context of cancer therapy.

Adenosine activates brown adipose tissue and recruits beige adipocytes via A2A receptors.

Brown adipose tissue (BAT) is specialized in energy expenditure, making it a potential target for anti-obesity therapies. Following exposure to cold, BAT is activated by the sympathetic nervous system with concomitant release of catecholamines and activation of ß-adrenergic receptors. Because BAT therapies based on cold exposure or ß-adrenergic agonists are clinically not feasible, alternative strategies must be explored. Purinergic co-transmission might be involved in sympathetic control of BAT and previous studies reported inhibitory effects of the purinergic transmitter adenosine in BAT from hamster or rat. However, the role of adenosine in human BAT is unknown. Here we show that adenosine activates human and murine brown adipocytes at low nanomolar concentrations. Adenosine is released in BAT during stimulation of sympathetic nerves as well as from brown adipocytes. The adenosine A2A receptor is the most abundant adenosine receptor in human and murine BAT. Pharmacological blockade or genetic loss of A2A receptors in mice causes a decrease in BAT-dependent thermogenesis, whereas treatment with A2A agonists significantly increases energy expenditure. Moreover, pharmacological stimulation of A2A receptors or injection of lentiviral vectors expressing the A2A receptor into white fat induces brown-like cells-so-called beige adipocytes. Importantly, mice fed a high-fat diet and treated with an A2A agonist are leaner with improved glucose tolerance. Taken together, our results demonstrate that adenosine-A2A signalling plays an unexpected physiological role in sympathetic BAT activation and protects mice from diet-induced obesity. Those findings reveal new possibilities for developing novel obesity therapies.

Archaebacterial tetraetherlipid liposomes.

Liposomes are widely investigated for their applicability as drug delivery systems. However, the unstable liposomal constitution is one of the greatest limitations, because the liposomes undergo fast elimination after application to the human body. In the presented study, novel archeal lipids were used to prepare liposomal formulations which were tested for their stability at elevated temperatures, at different pH-values and after heat sterilization.