Pancreaticoduodenectomy with right hemicolectomy for advanced malignancy: a single UK hepatopancreaticobiliary centre experience.

AIM: Locally advanced intestinal neoplasms including colon cancer may require radical en bloc pancreaticoduodenectomy and right hemicolectomy (PD-RC) to achieve curative, margin-negative resection, but the safety and benefit of this uncommon procedure has not been established. The Association of Coloproctology of Great Britain and Ireland IMPACT initiative has also highlighted a lack of awareness about current services available within the UK for patients with advanced colorectal cancer and concerns about low-volume centres managing complex cases. Thus, we aimed to review the feasibility, safety and long-term outcomes of this procedure at a single high-volume hepatopancreaticobiliary surgery unit in the UK. METHOD: A retrospective cohort study was performed using a database of all consecutive patients with intestinal cancer who had been referred to our regional advanced multidisciplinary team and undergone PD-RC in a 7-year period (2013-2020). Clinico-pathological and outcome data were reviewed. RESULTS: Ten patients (mean age 54 ± 13, 8/10 men) were identified. Final histology revealed the primary tumour sites were colon (n = 7) and duodenum (n = 3). R0 resection was achieved in all cases. The major complication rate (Clavien-Dindo ≥ 3) was 10% (1/10) with no deaths within 90 days of surgery. The Kaplan-Meier estimated 5-year overall survival was 83.3% (95% CI 58.3%-100%). Univariate survival analysis identified perineural invasion and extra-colonic origin as predictors of poor survival (log-rank P < 0.05). CONCLUSION: En bloc PD-RC for locally advanced intestinal cancer can be performed safely with a high proportion of margin-negative resections and resultant long-term survival in carefully selected patients.

Personalized local SAR prediction for parallel transmit neuroimaging at 7T from a single T1-weighted dataset.

PURPOSE: Parallel RF transmission (PTx) is one of the key technologies enabling high quality imaging at ultra-high fields (≥7T). Compliance with regulatory limits on the local specific absorption rate (SAR) typically involves over-conservative safety margins to account for intersubject variability, which negatively affect the utilization of ultra-high field MR. In this work, we present a method to generate a subject-specific body model from a single T1-weighted dataset for personalized local SAR prediction in PTx neuroimaging at 7T. METHODS: Multi-contrast data were acquired at 7T (N = 10) to establish ground truth segmentations in eight tissue types. A 2.5D convolutional neural network was trained using the T1-weighted data as input in a leave-one-out cross-validation study. The segmentation accuracy was evaluated through local SAR simulations in a quadrature birdcage as well as a PTx coil model. RESULTS: The network-generated segmentations reached Dice coefficients of 86.7% ± 6.7% (mean ± SD) and showed to successfully address the severe intensity bias and contrast variations typical to 7T. Errors in peak local SAR obtained were below 3.0% in the quadrature birdcage. Results obtained in the PTx configuration indicated that a safety margin of 6.3% ensures conservative local SAR estimates in 95% of the random RF shims, compared to an average overestimation of 34% in the generic "one-size-fits-all" approach. CONCLUSION: A subject-specific body model can be automatically generated from a single T1-weighted dataset by means of deep learning, providing the necessary inputs for accurate and personalized local SAR predictions in PTx neuroimaging at 7T.

Deep neural-network based optimization for the design of a multi-element surface magnet for MRI applications.

We present a combination of a CNN-based encoder with an analytical forward map for solving inverse problems. We call it an encoder-analytic (EA) hybrid model. It does not require a dedicated training dataset and can train itself from the connected forward map in a direct learning fashion. A separate regularization term is not required either, since the forward map also acts as a regularizer. As it is not a generalization model it does not suffer from overfitting. We further show that the model can be customized to either find a specific target solution or one that follows a given heuristic. As an example, we apply this approach to the design of a multi-element surface magnet for low-field magnetic resonance imaging (MRI). We further show that the EA model can outperform the benchmark genetic algorithm model currently used for magnet design in MRI, obtaining almost 10 times better results.

Dendritic Cells Cross-Present Immunogenic Lentivector-Encoded Antigen from Transduced Cells to Prime Functional T Cell Immunity.

Recombinant lentiviral vectors (LVs) are highly effective vaccination vehicles that elicit protective T cell immunity in disease models. Dendritic cells (DCs) acquire antigen at sites of vaccination and migrate to draining lymph nodes, where they prime vaccine-specific T cells. The potency with which LVs activate CD8+ T cell immunity has been attributed to the transduction of DCs at the immunization site and durable presentation of LV-encoded antigens. However, it is not known how LV-encoded antigens continue to be presented to T cells once directly transduced DCs have turned over. Here, we report that LV-encoded antigen is efficiently cross-presented by DCs in vitro. We have further exploited the temporal depletion of DCs in the murine CD11c.DTR (diphtheria toxin receptor) model to demonstrate that repopulating DCs that were absent at the time of immunization cross-present LV-encoded antigen to T cells in vivo. Indirect presentation of antigen from transduced cells by DCs is sufficient to prime functional effector T cells that control tumor growth. These data suggest that DCs cross-present immunogenic antigen from LV-transduced cells, thereby facilitating prolonged activation of T cells in the absence of circulating LV particles. These are findings that may impact on the future design of LV vaccination strategies.

Traumatic optic neuropathy treatment trial (TONTT): open label, phase 3, multicenter, semi-experimental trial.

PURPOSE: Intravenously administered erythropoietin (EPO) was firstly commenced (phase 1) in patients with indirect traumatic optic neuropathy (TON) by this group in 2011. It was re-tested by another group (phase 2) in 2014. This multicenter clinical trial was designed to compare its effect with intravenous steroid and observation. METHODS: Included were TON patients ≥5 years of age and with trauma-treatment interval of ≤3 weeks. Follow-up visits were set at 1, 2, 3, 7, 14, 30, and at least 90 days after treatment. EPO and methylprednisolone were infused intravenously every day for three consecutive days. Primary outcome measure was change in the best corrected visual acuity (BCVA). Secondary outcomes included change in color vision and relative afferent pupillary defect (RAPD), side effects, and factors affecting the final visual improvement. RESULTS: Out of 120 patients, 100 (EPO: 69, steroid: 15, observation: 16) were finally included. All three groups showed a significant improvement of BCVA which was not significantly different between the groups (adjusted for pretreatment BCVA). Color vision was significantly improved in the EPO group. Late treatment (>3 days) (odds ratio = 2.53) and initial BCVA of NLP (odds ratio = 5.74) significantly worsened visual recovery. No side effect was observed in any group. CONCLUSION: EPO, steroid, and observation showed a significant improvement of BCVA in patients with TON. Initial BCVA of NLP and late treatment (>3 days) were significant risk factors for visual improvement.

Eighteen-point abobotulinum toxin a upper face rejuvenation: an eye plastic perspective on 845 subjects.

PURPOSE: To report the method and results of 18-point Abobotulinum toxin A (ABO-BTA, Dysport) upper face rejuvenation on 845 subjects. METHODS: In a retrospective chart review, all subjects (the first cycle of injection) with ABO-BTA upper face rejuvenation from 2003 to 2009 were included. Excluded were subjects with facial spastic disorders, injection after upper face lifting, and aberrant regeneration of facial nerves. Upper face rejuvenation included 18 points of injection at forehead creases (4), frown lines (5), bunny line (1), crow's feet (4 on both sides), and lower eyelid crease (4 on both sides). They were revisited in 10 to 14 days for assessment of the effects and possible touch-up injection. Demographics, year of injection, topical anesthetic usage, touch-up injection, and adverse effects (AE) were recorded. RESULTS: There were 845 subjects (85.8% women) whose age was below 40 in 49.3%. All but 68 (8%) were happy with the touch-up visit, 10 to 14 days after injection. Touch-up injection was performed in 8% of subjects mainly for the eyebrow asymmetry. AE (22/845, 2.6%) were bruise (15/845, 1.8%), blepharoptosis (3/845, 0.3%), remained eyebrow asymmetry after touch-up injection (2/845, 0.2%), and headache (2/845, 0.2%). They were significantly more in subjects with touch-up injection, younger than 40 years, and in the first and second year of experience (especially for the bruise). CONCLUSIONS: Eighteen-point ABO-BTA upper face rejuvenation had a low rate of AE in this series in which majority was bruise at the lateral canthal area. They were significantly more in the first years of experience, subjects younger than 40, and who had touch-up injections.

Comparison of the Efficacy of Tolterodine versus Oxybutynin in the Treatment of Children with Desmopressin-Resistant Enuresis: A Randomized Controlled Clinical Trial.

Background: Enuresis, defined as involuntary nocturnal urination without any underlying organic disorder in a child expected to control urination, poses a common problem. This study evaluated the effectiveness of Tolterodine and Oxybutynin in children presenting with primary desmopressin-resistant enuresis. Materials and Methods: A randomized clinical trial was undertaken involving 68 participants aged between 5 and 16 years, all suffering from primary enuresis. These patients were randomly assigned to one of two treatment groups for a three-month period: Group 1, treated with Oxybutynin and Desmopressin, and Group 2, treated with Tolterodine and Desmopressin. Data on demographics, clinical and laboratory findings, and subjective responses to treatment were gathered. The response was measured based on the frequency of wetting incidents per night and week and compared with pre-treatment data. Results: Patients were divided into two groups (30 patients in Group 1 and 38 patients in Group 2). The mean age of the patients was 88.97±27.09 months. In the first treatment group, 6 out of 30 patients (20%) experienced a complete treatment response, as did 5 out of 38 patients (13.2%) in the second treatment group. This difference between the groups was not statistically significant. Seven patients (23%) in the Oxybutynin group and 13 patients (34%) in the Tolterodine group reported a lack of response to treatment, a difference that also lacked statistical significance. Conclusion: For patients resistant to Desmopressin, the addition of anticholinergic drugs elicited a significant response in over half of the patients. However, no benefit was observed in using either Oxybutynin or Tolterodine in the treatment of Desmopressin-resistant enuresis.

The effect of selenium and zinc on CD4(+) count and opportunistic infections in HIV/AIDS patients: a randomized double blind trial.

Objectives: We assessed the effect of selenium and zinc supplementation on CD4 cell count and the risk of developing opportunistic infections.Methods: In a double blind clinical trial, 146 HIV(+) patients receiving combination antiretroviral therapy with CD4(+) >200/cubic millimeter were screened for comorbidities and opportunistic infections, and randomized to receive daily selenium (200 µg), zinc (50 mg) or placebo for 6 months, before a 3-month follow-up period. CD4 cell counts were measured in the 3th, 6th and 9th months. The serum selenium and zinc were measured in the 6th month. The incidence of opportunistic infection was assessed monthly for 6 months and at the end of the 9th month.Results: The final incidence of supplement deficiency for placebo, zinc and selenium were 46.7%, 44.7% and 50.0%, respectively. Overall compliance with supplementation was 99.42%. Although the changes from baseline were not statistically significant, zinc supplementation was significantly associated with reduced risk of opportunistic infections.Conclusion: Development of the opportunistic infections after zinc supplementation significantly decreased; however, significant improvement in CD4 count was not observed in this group.

Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.

PURPOSE: To develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity-Modulated Proton Therapy (IMPT) of prostate cancer using elastix software and deep learning. METHODS: A three-dimensional (3D) Convolutional Neural Network was trained for automatic bladder segmentation of the computed tomography (CT) scans. The automatic bladder segmentation alongside the computed tomography (CT) scan is jointly optimized to add explicit knowledge about the underlying anatomy to the registration algorithm. We included three datasets from different institutes and CT manufacturers. The first was used for training and testing the ConvNet, where the second and the third were used for evaluation of the proposed pipeline. The system performance was quantified geometrically using the dice similarity coefficient (DSC), the mean surface distance (MSD), and the 95% Hausdorff distance (HD). The propagated contours were validated clinically through generating the associated IMPT plans and compare it with the IMPT plans based on the manual delineations. Propagated contours were considered clinically acceptable if their treatment plans met the dosimetric coverage constraints on the manual contours. RESULTS: The bladder segmentation network achieved a DSC of 88% and 82% on the test datasets. The proposed registration pipeline achieved a MSD of 1.29 ± 0.39, 1.48 ± 1.16, and 1.49 ± 0.44 mm for the prostate, seminal vesicles, and lymph nodes, respectively, on the second dataset and a MSD of 2.31 ± 1.92 and 1.76 ± 1.39 mm for the prostate and seminal vesicles on the third dataset. The automatically propagated contours met the dose coverage constraints in 86%, 91%, and 99% of the cases for the prostate, seminal vesicles, and lymph nodes, respectively. A Conservative Success Rate (CSR) of 80% was obtained, compared to 65% when only using intensity-based registration. CONCLUSION: The proposed registration pipeline obtained highly promising results for generating treatment plans adapted to the daily anatomy. With 80% of the automatically generated treatment plans directly usable without manual correction, a substantial improvement in system robustness was reached compared to a previous approach. The proposed method therefore facilitates more precise proton therapy of prostate cancer, potentially leading to fewer treatment-related adverse side effects.

Brain tissue segmentation in MR images based on a hybrid of MRF and social algorithms.

Effective abnormality detection and diagnosis in Magnetic Resonance Images (MRIs) requires a robust segmentation strategy. Since manual segmentation is a time-consuming task which engages valuable human resources, automatic MRI segmentations received an enormous amount of attention. For this goal, various techniques have been applied. However, Markov Random Field (MRF) based algorithms have produced reasonable results in noisy images compared to other methods. MRF seeks a label field which minimizes an energy function. The traditional minimization method, simulated annealing (SA), uses Monte Carlo simulation to access the minimum solution with heavy computation burden. For this reason, MRFs are rarely used in real time processing environments. This paper proposed a novel method based on MRF and a hybrid of social algorithms that contain an ant colony optimization (ACO) and a Gossiping algorithm which can be used for segmenting single and multispectral MRIs in real time environments. Combining ACO with the Gossiping algorithm helps find the better path using neighborhood information. Therefore, this interaction causes the algorithm to converge to an optimum solution faster. Several experiments on phantom and real images were performed. Results indicate that the proposed algorithm outperforms the traditional MRF and hybrid of MRF-ACO in speed and accuracy.