Preoperative Classification of Peripheral Nerve Sheath Tumors on MRI Using Radiomics

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft-tissue tumors prevalent in neurofibromatosis type 1 (NF1) patients, posing a significant risk of metastasis and recurrence. Current magnetic resonance imaging (MRI) imaging lacks decisiveness in distinguishing benign peripheral nerve sheath tumors (BPNSTs) and MPNSTs, necessitating invasive biopsies. This study aims to develop a radiomics model using quantitative imaging features and machine learning to distinguish MPNSTs from BPNSTs. Clinical data and MRIs from MPNST and BPNST patients (2000–2019) were collected at a tertiary sarcoma referral center. Lesions were manually and semi-automatically segmented on MRI scans, and radiomics features were extracted using the Workflow for Optimal Radiomics Classification (WORC) algorithm, employing automated machine learning. The evaluation was conducted using a 100× random-split cross-validation. A total of 35 MPNSTs and 74 BPNSTs were included. The T1-weighted (T1w) MRI radiomics model outperformed others with an area under the curve (AUC) of 0.71. The incorporation of additional MRI scans did not enhance performance. Combining T1w MRI with clinical features achieved an AUC of 0.74. Experienced radiologists achieved AUCs of 0.75 and 0.66, respectively. Radiomics based on T1w MRI scans and clinical features show some ability to distinguish MPNSTs from BPNSTs, potentially aiding in the management of these tumors.</p

Preoperative Classification of Peripheral Nerve Sheath Tumors on MRI Using Radiomics

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft-tissue tumors prevalent in neurofibromatosis type 1 (NF1) patients, posing a significant risk of metastasis and recurrence. Current magnetic resonance imaging (MRI) imaging lacks decisiveness in distinguishing benign peripheral nerve sheath tumors (BPNSTs) and MPNSTs, necessitating invasive biopsies. This study aims to develop a radiomics model using quantitative imaging features and machine learning to distinguish MPNSTs from BPNSTs. Clinical data and MRIs from MPNST and BPNST patients (2000–2019) were collected at a tertiary sarcoma referral center. Lesions were manually and semi-automatically segmented on MRI scans, and radiomics features were extracted using the Workflow for Optimal Radiomics Classification (WORC) algorithm, employing automated machine learning. The evaluation was conducted using a 100× random-split cross-validation. A total of 35 MPNSTs and 74 BPNSTs were included. The T1-weighted (T1w) MRI radiomics model outperformed others with an area under the curve (AUC) of 0.71. The incorporation of additional MRI scans did not enhance performance. Combining T1w MRI with clinical features achieved an AUC of 0.74. Experienced radiologists achieved AUCs of 0.75 and 0.66, respectively. Radiomics based on T1w MRI scans and clinical features show some ability to distinguish MPNSTs from BPNSTs, potentially aiding in the management of these tumors.</p

Cognitive brain activity before and after surgery in meningioma patients

Neuropsychological studies have demonstrated that meningioma patients frequently exhibit cognitive deficits before surgery and show only limited improvement after surgery. Combining neuropsychological with functional imaging measurements can shed more light on the impact of surgery on cognitive brain function. We aimed to evaluate whether surgery affects cognitive brain activity in such a manner that it may mask possible changes in cognitive functioning measured by neuropsychological tests. Twenty-three meningioma patients participated in a fMRI measurement using a verbal working memory task as well as three neuropsychological tests focused on working memory, just before and 3 months after surgery. A region of interest based fMRI analysis was used to examine cognitive brain activity at these timepoints within the central executive network and default mode network. Neuropsychological assessment showed impaired cognitive functioning before as well as 3 months after surgery. Neuropsychological test scores, in-scanner task performance as well as brain activity within the central executive and default mode network were not significantly different between both timepoints. Our results indicate that surgery does not significantly affect cognitive brain activity in meningioma patients the first few months after surgery. Therefore, the lack of cognitive improvement after surgery is not likely the result of compensatory processes in the brain. Cognitive deficits that are already present before surgery appear to be persistent after surgery and a considerable recovery period. Our study shows potential leads that comprehensive cognitive evaluation can be of added value so that cognitive functioning may become a more prominent factor in clinical decision making

Preoperative Classification of Peripheral Nerve Sheath Tumors on MRI Using Radiomics

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft-tissue tumors prevalent in neurofibromatosis type 1 (NF1) patients, posing a significant risk of metastasis and recurrence. Current magnetic resonance imaging (MRI) imaging lacks decisiveness in distinguishing benign peripheral nerve sheath tumors (BPNSTs) and MPNSTs, necessitating invasive biopsies. This study aims to develop a radiomics model using quantitative imaging features and machine learning to distinguish MPNSTs from BPNSTs. Clinical data and MRIs from MPNST and BPNST patients (2000–2019) were collected at a tertiary sarcoma referral center. Lesions were manually and semi-automatically segmented on MRI scans, and radiomics features were extracted using the Workflow for Optimal Radiomics Classification (WORC) algorithm, employing automated machine learning. The evaluation was conducted using a 100× random-split cross-validation. A total of 35 MPNSTs and 74 BPNSTs were included. The T1-weighted (T1w) MRI radiomics model outperformed others with an area under the curve (AUC) of 0.71. The incorporation of additional MRI scans did not enhance performance. Combining T1w MRI with clinical features achieved an AUC of 0.74. Experienced radiologists achieved AUCs of 0.75 and 0.66, respectively. Radiomics based on T1w MRI scans and clinical features show some ability to distinguish MPNSTs from BPNSTs, potentially aiding in the management of these tumors

Involvement of the endocannabinoid system in reward processing in the human brain

Rationale Disturbed reward processing in humans has been associated with a number of disorders, such as depression, addiction, and attention-deficit hyperactivity disorder. The endocannabinoid (eCB) system has been implicated in reward processing in animals, but in humans, the relation between eCB functioning and reward is less clear. Objectives The current study uses functional magnetic resonance imaging (fMRI) to investigate the role of the eCB system in reward processing in humans by examining the effect of the eCB agonist Δ9-tetrahydrocannabinol (THC) on reward-related brain activity. Methods Eleven healthy males participated in a randomized placebo-controlled pharmacological fMRI study with administration of THC to challenge the eCB system. We compared anticipatory and feedback-related brain activity after placebo and THC, using a monetary incentive delay task. In this task, subjects are notified before each trial whether a correct response is rewarded (“reward trial”) or not (“neutral trial”). Results Subjects showed faster reaction times during reward trials compared to neutral trials, and this effect was not altered by THC. THC induced a widespread attenuation of the brain response to feedback in reward trials but not in neutral trials. Anticipatory brain activity was not affected. Conclusions These results suggest a role for the eCB system in the appreciation of rewards. The involvement of the eCB system in feedback processing may be relevant for disorders in which appreciation of natural rewards may be affected such as addiction

Effects of Δ9-tetrahydrocannabinol administration on human encoding and recall memory function: A pharmacological fMRI study

Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing evidence but suggest that administration of cannabinoid substances affects encoding rather than recall of information. In this study, we examined the effects of perturbation of the eCB system on memory function during both encoding and recall. We performed a pharmacological MRI study with a placebo-controlled, crossover design, investigating the effects of Δ9-tetrahydrocannabinol (THC) inhalation on associative memory-related brain function in 13 healthy volunteers. Performance and brain activation during associative memory were assessed using a pictorial memory task, consisting of separate encoding and recall conditions. Administration of THC caused reductions in activity during encoding in the right insula, the right inferior frontal gyrus, and the left middle occipital gyrus and a network-wide increase in activity during recall, which was most prominent in bilateral cuneus and precuneus. THC administration did not affect task performance, but while during placebo recall activity significantly explained variance in performance, this effect disappeared after THC. These findings suggest eCB involvement in encoding of pictorial information. Increased precuneus activity could reflect impaired recall function, but the absence of THC effects on task performance suggests a compensatory mechanism. These results further emphasize the eCB system as a potential novel target for treatment of memory disorders and a promising target for development of new therapies to reduce memory deficits in humans

Repeat hepatectomy justified in patients with early recurrence of colorectal cancer liver metastases: A systematic review and meta-analysis

Background: The benefit of repeat hepatectomy in patients with early recurrence of colorectal cancer liver metastases (CRLM) is questioned, in particular in those suffering from recurrence within three to six months following initial hepatectomy. The aim of this review was therefore to assess whether disease-free interval was associated with overall survival in patients undergoing repeat hepatectomy for recurrent CRLM. Methods: A systematic review and meta-analysis was conducted, according to PRISMA guidelines. PubMed, Embase and Cochrane Library databases were searched from database inception to 6th June 2020. Observational studies describing results of repeat hepatectomy for recurrent CRLM, including (disease-free) interval between hepatic resections and overall survival were included. Patients undergoing repeat hepatectomy within three months or additional resection of extrahepatic disease were excluded from meta-analysis. Results: The initial search identified 2159 records, of which 28 were included for qualitative synthesis. A meta-analysis of 15 cohort studies was performed, comprising 1039 eligible patients. Median overall survival of 54.0 months [95 %-CI: 38.6–69.4] was observed after repeat hepatectomy in patients suffering from recurrent CRLM between three to six months compared to 53.0 months [95 %-CI: 44.3–61.6] for patients with recurrent CRLM between seven to twelve months (adjusted HR = 0.89, 95 %-CI: 0.66–1.18; p = 0.410), and 60.0 months [95 %-CI: 52.7–67.3] for patients with recurrent CRLM after twelve months (adjusted HR = 0.70, 95 %-CI: 0.53−0.92; p = 0.012). Conclusions: Disease-free interval is considered a prognostic factor for overall survival, but should not be used as selection criterion per se for repeat hepatectomy in patients suffering from recurrent CRLM

Default Mode Network in the Effects of Δ9-Tetrahydrocannabinol (THC) on Human Executive Function

<div><p>Evidence is increasing for involvement of the endocannabinoid system in cognitive functions including attention and executive function, as well as in psychiatric disorders characterized by cognitive deficits, such as schizophrenia. Executive function appears to be associated with both modulation of active networks and inhibition of activity in the default mode network. In the present study, we examined the role of the endocannabinoid system in executive function, focusing on both the associated brain network and the default mode network. A pharmacological functional magnetic resonance imaging (fMRI) study was conducted with a placebo-controlled, cross-over design, investigating effects of the endocannabinoid agonist Δ9-tetrahydrocannabinol (THC) on executive function in 20 healthy volunteers, using a continuous performance task with identical pairs. Task performance was impaired after THC administration, reflected in both an increase in false alarms and a reduction in detected targets. This was associated with reduced deactivation in a set of brain regions linked to the default mode network, including posterior cingulate cortex and angular gyrus. Less deactivation was significantly correlated with lower performance after THC. Regions that were activated by the continuous performance task, notably bilateral prefrontal and parietal cortex, did not show effects of THC. These findings suggest an important role for the endocannabinoid system in both default mode modulation and executive function. This may be relevant for psychiatric disorders associated with executive function deficits, such as schizophrenia and ADHD.</p></div

Task performance.

<p>The figure shows (left) the mean percentage of correctly identified targets, (middle) the mean percentage of false alarms, and (right) reaction times of correct responses after placebo and THC administration (n = 20; mean ± SEM). * Significant difference between THC and placebo (p<0.05).</p