The long-term impact of cerebellar tumor resection on executive functioning, anxiety, and fear of pain: A mixed methodology pilot study.

This pilot study investigated the long-term impact of a surgery-only treatment (no exposure to other treatments, such as chemotherapy and radiation) for pediatric cerebellar low-grade gliomas on executive function, anxiety, and fear of pain (FOP) beliefs. Twelve patients who underwent surgical glioma resection during childhood (surgery age was 4-16 years, study visit age was 10-28 years), and 12 pain-free controls matched for age, sex, race, and handedness were tested. The spatial extent of resection was precisely mapped using magnetic resonance imaging (MRI). Executive function, anxiety, and FOP were assessed using validated self-report age-appropriate questionnaires for children and adults. Structured clinical interviews at a post-surgery follow-up visit were completed (average: 89 months, range: 20-99). No significant differences in FOP (FOPQ-C t[14 = 1.81, p = 0.09; FOPQ-III t[4] = 0.29, p = 0.79), executive function scores (BRIEF t[20] = 0.30, p = 0.28), or anxiety scores (MASC t[16] = 0.19, p = 0.85; MAQ t[4] = 1.80, p = 0.15) were found in pediatric or adult patients compared to pain-free controls. Clinical interviews mainly categorized pediatric patients as not anxious. One participant reported mild/subclinical anxiety, and one had moderate clinical anxiety. Neither psychologists nor patients endorsed impairments to executive functioning, anxiety, or FOP. Our pilot results suggest that pediatric cerebellar tumor survivors treated with surgery-only have favorable long-term functioning related to these themes. While these results are promising, they will need to be replicated in a larger patient sample.

From Dose Reduction to Contrast Maximization: Can Deep Learning Amplify the Impact of Contrast Media on Brain Magnetic Resonance Image Quality? A Reader Study.

OBJECTIVES: The aim of this study was to evaluate a deep learning method designed to increase the contrast-to-noise ratio in contrast-enhanced gradient echo T1-weighted brain magnetic resonance imaging (MRI) acquisitions. The processed images are quantitatively evaluated in terms of lesion detection performance. MATERIALS AND METHODS: A total of 250 multiparametric brain MRIs, acquired between November 2019 and March 2021 at Gustave Roussy Cancer Campus (Villejuif, France), were considered for inclusion in this retrospective monocentric study. Independent training (107 cases; age, 55 ± 14 years; 58 women) and test (79 cases; age, 59 ± 14 years; 41 women) samples were defined. Patients had glioma, brain metastasis, meningioma, or no enhancing lesion. Gradient echo and turbo spin echo with variable flip angles postcontrast T1 sequences were acquired in all cases. For the cases that formed the training sample, "low-dose" postcontrast gradient echo T1 images using 0.025 mmol/kg injections of contrast agent were also acquired. A deep neural network was trained to synthetically enhance the low-dose T1 acquisitions, taking standard-dose T1 MRI as reference. Once trained, the contrast enhancement network was used to process the test gradient echo T1 images. A read was then performed by 2 experienced neuroradiologists to evaluate the original and processed T1 MRI sequences in terms of contrast enhancement and lesion detection performance, taking the turbo spin echo sequences as reference. RESULTS: The processed images were superior to the original gradient echo and reference turbo spin echo T1 sequences in terms of contrast-to-noise ratio (44.5 vs 9.1 and 16.8; P < 0.001), lesion-to-brain ratio (1.66 vs 1.31 and 1.44; P < 0.001), and contrast enhancement percentage (112.4% vs 85.6% and 92.2%; P < 0.001) for cases with enhancing lesions. The overall image quality of processed T1 was preferred by both readers (graded 3.4/4 on average vs 2.7/4; P < 0.001). Finally, the proposed processing improved the average sensitivity of gradient echo T1 MRI from 88% to 96% for lesions larger than 10 mm ( P = 0.008), whereas no difference was found in terms of the false detection rate (0.02 per case in both cases; P > 0.99). The same effect was observed when considering all lesions larger than 5 mm: sensitivity increased from 70% to 85% ( P < 0.001), whereas false detection rates remained similar (0.04 vs 0.06 per case; P = 0.48). With all lesions included regardless of their size, sensitivities were 59% and 75% for original and processed T1 images, respectively ( P < 0.001), and the corresponding false detection rates were 0.05 and 0.14 per case, respectively ( P = 0.06). CONCLUSION: The proposed deep learning method successfully amplified the beneficial effects of contrast agent injection on gradient echo T1 image quality, contrast level, and lesion detection performance. In particular, the sensitivity of the MRI sequence was improved by up to 16%, whereas the false detection rate remained similar.

Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study.

MATERIALS AND METHODS: This monocentric retrospective study leveraged 200 multiparametric brain MRIs acquired between November 2019 and February 2020 at Gustave Roussy Cancer Campus (Villejuif, France). A total of 145 patients were included: 107 formed the training sample (55 ± 14 years, 58 women) and 38 the separate test sample (62 ± 12 years, 22 women). Patients had glioma, brain metastases, meningioma, or no enhancing lesion. T1, T2-FLAIR, diffusion-weighted imaging, low-dose, and standard-dose postcontrast T1 sequences were acquired. A deep network was trained to process the precontrast and low-dose sequences to predict "virtual" surrogate images for contrast-enhanced T1. Once trained, the deep learning method was evaluated on the test sample. The discrepancies between the predicted virtual images and the standard-dose MRIs were qualitatively and quantitatively evaluated using both automated voxel-wise metrics and a reader study, where 2 radiologists graded image qualities and marked all visible enhancing lesions. RESULTS: The automated analysis of the test brain MRIs computed a structural similarity index of 87.1% ± 4.8% between the predicted virtual sequences and the reference contrast-enhanced T1 MRIs, a peak signal-to-noise ratio of 31.6 ± 2.0 dB, and an area under the curve of 96.4% ± 3.1%. At Youden's operating point, the voxel-wise sensitivity (SE) and specificity were 96.4% and 94.8%, respectively. The reader study found that virtual images were preferred to standard-dose MRI in terms of image quality (P = 0.008). A total of 91 reference lesions were identified in the 38 test T1 sequences enhanced with full dose of contrast agent. On average across readers, the brain lesion SE of the virtual images was 83% for lesions larger than 10 mm (n = 42), and the associated false detection rate was 0.08 lesion/patient. The corresponding positive predictive value of detected lesions was 92%, and the F1 score was 88%. Lesion detection performance, however, dropped when smaller lesions were included: average SE was 67% for lesions larger than 5 mm (n = 74), and 56% with all lesions included regardless of their size. The false detection rate remained below 0.50 lesion/patient in all cases, and the positive predictive value remained above 73%. The composite F1 score was 63% at worst. CONCLUSIONS: The proposed deep learning method for virtual contrast-enhanced T1 brain MRI prediction showed very high quantitative performance when evaluated with standard voxel-wise metrics. The reader study demonstrated that, for lesions larger than 10 mm, good detection performance could be maintained despite a 4-fold division in contrast agent usage, unveiling a promising avenue for reducing the gadolinium exposure of returning patients. Small lesions proved, however, difficult to handle for the deep network, showing that full-dose injections remain essential for accurate first-line diagnosis in neuro-oncology.

C-Fiber Assays in the Cornea vs. Skin.

C-fibers are unmyelinated nerve fibers that transmit high threshold mechanical, thermal, and chemical signals that are associated with pain sensations. This review examines current literature on measuring altered peripheral nerve morphology and discusses the most relevant aspects of corneal microscopy, especially whether corneal imaging presents significant method advantages over skin biopsy. Given its relative merits, corneal confocal microscopy would seem to be a more practical and patient-centric approach than utilizing skin biopsies.

Aphasia outcome: the interactions between initial severity, lesion size and location.

OBJECTIVES: The outcome of aphasia at 3 months is variable in patients with moderate/severe stroke. The aim was to predict 3-month aphasia outcome using prediction models including initial severity in addition to the interaction between lesion size and location at the acute phase. METHODS: Patients with post-stroke aphasia (assessed by the Aphasia Rapid Test at day 7-ART D7) and MRI performed at day 1 were enrolled (n = 73). Good outcome at 3-months was defined by an Aphasia Handicap Score of 0-2. Each infarct lesion was overlapped with an area of interest in the left temporo-parietal region to compute an intersection index (proportion of the critical region damaged by the infarct). We tested ART D7, age, lesion volume, and intersection index as well as a combined variable lesion volume*intersection in a univariate analysis. Then, we performed a multivariate analysis to investigate which variables were independent predictors of good outcome. RESULTS: ART at D7, infarct volume, and the intersection index were univariate predictors of good outcome. In the multivariate analysis, ART D7 and "volume ≥ 50 ml or intersection index ≥ 20%" correctly classified 89% of the patients (p < 0.0001). When added to the model, the interaction between both variables was significant indicating that the impact of the size or site variable depends on the initial severity of aphasia. CONCLUSION: In patients with initially severe aphasia, large infarct size or critical damage in left temporoparietal junction is associated with poor language outcome at 3 months.

Pain affect disrupted in children with posterior cerebellar tumor resection.

Objectives: Damage to the posterior cerebellum can cause affective deficits in patients. In adults, cerebellar infarcts result in thermal hyperalgesia and affect descending modulation of pain. This study evaluated the effect of resection of low-grade cerebellar tumors on pain processing in human children. Methods: Twelve pediatric patients treated with surgery only for low-grade gliomas (8 females, 4 males; mean age = 13.8 ± 5.6) and twelve matched controls (8 females, 4 males; mean age = 13.8 ± 5.7) were evaluated using quantitative sensory testing and fMRI. Five patients had tumors localized to posterior cerebellar hemispheres, henceforth identified as Crus Patients. Results: Crus Patients had significantly lower pain tolerance to a cold pressor test than controls. No significant differences were detected between subject groups for heat and cold detection thresholds (HDT, CDT), and heat and cold pain thresholds (HPT, CPT). Crus Patients also showed significantly decreased fMRI responses to painful heat in anterior insula, which has been associated with pain affect. Interpretation: Damage to posterior cerebellar hemispheres disrupted affective pain processing and endogenous pain modulation, resulting in decreased pain tolerance to suprathreshold noxious stimuli. This suggests that surgical resection of this region in children may increase the risk of developing pain disorders.

Frequency of Hand Decontamination of Intraoperative Providers and Reduction of Postoperative Healthcare-Associated Infections: A Randomized Clinical Trial of a Novel Hand Hygiene System.

BACKGROUND Healthcare provider hands are an important source of intraoperative bacterial transmission events associated with postoperative infection development. OBJECTIVE To explore the efficacy of a novel hand hygiene improvement system leveraging provider proximity and individual and group performance feedback in reducing 30-day postoperative healthcare-associated infections via increased provider hourly hand decontamination events. DESIGN Randomized, prospective study. SETTING Dartmouth-Hitchcock Medical Center in New Hampshire and UMass Memorial Medical Center in Massachusetts. PATIENTS Patients undergoing surgery. METHODS Operating room environments were randomly assigned to usual intraoperative hand hygiene or to a personalized, body-worn hand hygiene system. Anesthesia and circulating nurse provider hourly hand decontamination events were continuously monitored and reported. All patients were followed prospectively for the development of 30-day postoperative healthcare-associated infections. RESULTS A total of 3,256 operating room environments and patients (1,620 control and 1,636 treatment) were enrolled. The mean (SD) provider hand decontamination event rate achieved was 4.3 (2.9) events per hour, an approximate 8-fold increase in hand decontamination events above that of conventional wall-mounted devices (0.57 events/hour); P<.001. Use of the hand hygiene system was not associated with a reduction in healthcare-associated infections (odds ratio, 1.07 [95% CI, 0.82-1.40], P=.626). CONCLUSIONS The hand hygiene system evaluated in this study increased the frequency of hand decontamination events without reducing 30-day postoperative healthcare-associated infections. Future work is indicated to optimize the efficacy of this hand hygiene improvement strategy. Infect Control Hosp Epidemiol 2016;37:888-895.