Sports injury prevention programmes from the sports physical therapist's perspective: An international expert Delphi approach

ObjectiveTo provide consensus on how to plan, organize and implement exercise-based injury prevention program (IPP) in sports.DesignDelphi.SettingLimeSurvey platform.ParticipantsExperienced sports physical therapists from the International Federation of Sports Physical Therapy member countries.Main outcome measuresFactors related to sports IPP planning, organization and implementation.ResultsWe included 305 participants from 32 countries. IPP planning should be based on an athlete's injury history, on pre-season screening results, and on injury rates (respectively, 98%, 92%, 89% agreement). In total 97% participants agreed that IPP organization should depend on the athlete's age, 93% on the competition level, and 93% on the availability of low-cost materials. It was agreed that IPP should mainly be implemented in warm-up sessions delivered by the head or strength/conditioning coach, with physical training sessions and individual physical therapy sessions (respectively, 94%, 92%, 90% agreement).ConclusionStrong consensus was reached on (1) IPP based on the athlete's injury history, pre-season screening and evidence-based sports-specific injury rates; (2) IPP organization based on the athlete's age, competition level, and the availability of low-cost materials and (3) IPP implementation focussing on warm-up sessions implemented by the strength/conditioning coach, and/or individual prevention sessions by the physical therapist.     

Risk analysis for radiotherapy at the Universitätsklinikum Erlangen

PurposeRisk analysis is required by various laws and regulations in Germany and has an impact on each department of a large clinic. We provide an overview of the relevant laws and regulations in Germany and present the technical and organizational experience of introducing risk analysis in the Department of Radiation Oncology at the Universitätsklinikum Erlangen.MethodsRisk analysis was performed with an in-house developed extension of our intranet platform and ticketing system. Risks were classified according to occurrence and severity, each on a 5-level scale resulting into a risk matrix. An interdisciplinary team of six experienced members formed the core meeting weekly.ResultsA total of 38 risks and 50 measures have been identified in 41 1 h-meetings corresponding to approx. 260 working hours. Risk was distributed 8/20/13 to the categories critical (n = 8), monitoring (n = 20), and conditionally acceptable (n = 13). Risk analysis has been evaluated before and after introducing measures.ConclusionThe risk analysis method introduced has been successfully used in routine operations for over a year. Risk analysis takes time and effort. However, because experts from different disciplines meet each other every week, the overall workflow of the radiation oncology department can be improved efficiently and continuously.     

Oncologic outcomes of pathologic T4 and T3 colon cancer patients diagnosed with clinical T4 stage disease using preoperative computed tomography scan

BackgroundThe diagnostic accuracy of computed tomography (CT) for colon cancer is low, and the preoperative risk factors for locally advanced colon cancer are unknown. This study aimed to evaluate the correlation between preoperative CT scan findings and oncologic outcomes and to identify risk factors associated with locally advanced colon cancer.Materials and methodsPatients diagnosed with clinical stage (cT) 4 colon cancer based on preoperative CT scan findings who underwent curative surgery between January 2005 and December 2015 were retrospectively studied. Patients were divided according to pathologic stage (pT) into pT3 (n = 114) and pT4 (n = 102).ResultsThe disease-free survival rate was significantly different between the pT3 and pT4 groups (88.6% vs. 68.6%, p < 0.001). The overall survival rate of the pT3 group was significantly higher than that of the pT4 group (91.2% vs. 76.5%, p = 0.002). Perineural invasion and tumor budding were identified as preoperative risk factors predisposing to pT4 staging (p = 0.044, p = 0.001).ConclusionThe survival rate of pT3 patients was significantly higher than that of pT4 patients with a preoperative cT4 diagnosis. This suggests that when planning for neoadjuvant chemotherapy in locally advanced colon cancer, preoperative CT scan findings may overestimate clinical staging and lead to inappropriate treatment. Thus, there is a need for a new modality to evaluate local advancement in colon cancer.     

Effects of pomegranate supplement on menopausal symptoms and quality of life in menopausal women: A double-blind randomized placebo-controlled trial

BackgroundMenopausal symptoms have negative effects on the aspects of quality of life and impose a high cost on the health system. In traditional Persian medicine, pomegranate is recommended to alleviate menopausal symptoms.Material and methodsA randomized double-blind placebo-controlled trial was performed among 78 healthy women. Participants were interviewed three times: Before receiving the supplement/placebo, after completing the treatment, and after 3 weeks with no intervention. They filled out the demographic information sheet, modified-Kupperman index, and Menopause-Specific Quality of Life (MENQOL) questionnaires.ResultsThe mean scores of the modified-Kupperman index and MENQOL characteristics before and after the treatment and after the follow-up period were significantly different between pomegranate and placebo groups in both modified-Kupperman and MENQOL scores (p < 0.001).ConclusionThis study demonstrated that 4 weeks' treatment with the pomegranate supplement significantly ameliorates the irritating symptoms of menopause and improves the quality of life in menopausal women even after 4 weeks' medicine deprivation.     

An MRI sequence independent convolutional neural network for synthetic head CT generation in proton therapy

A magnetic resonance imaging (MRI) sequence independent deep learning technique was developed and validated to generate synthetic computed tomography (sCT) scans for MR guided proton therapy. 47 meningioma patients previously undergoing proton therapy based on pencil beam scanning were divided into training (33), validation (6), and test (8) cohorts. T₁, T₂, and contrast enhanced T₁ (T1CM) MRI sequences were used in combination with the planning CT (pCT) data to train a 3D U-Net architecture with ResNet-Blocks. A hyperparameter search was performed including two loss functions, two group sizes of normalisation, and depth of the network. Training outcome was compared between models trained for each individual MRI sequence and for all sequences combined. The performance was evaluated based on a metric and dosimetric analysis as well as spot difference maps. Furthermore, the influence of immobilisation masks that are not visible on MRIs was investigated. Based on the hyperparameter search, the final model was trained with fixed features per group for the group normalisation, six down-convolution steps, an input size of 128 × 192 × 192, and feature loss. For the test dataset for body/bone the mean absolute error (MAE) values were on average 79.8/216.3 Houndsfield unit (HU) when trained using T1 images, 71.1/186.1 HU for T2, and 82.9/236.4 HU for T1CM. The structural similarity metric (SSIM) ranged from 0.95 to 0.98 for all sequences. The investigated dose parameters of the target structures agreed within 1% between original proton treatment plans and plans recalculated on sCTs. The spot difference maps had peaks at ±0.2 cm and for 98% of all spots the difference was less than 1 cm. A novel MRI sequence independent sCT generator was developed, which suggests that the training phase of neural networks can be disengaged from specific MRI acquisition protocols. In contrast to previous studies, the patient cohort consisted exclusively of actual proton therapy patients (i.e. “real-world data”).     

Functional estrogen receptor signal transduction pathway activity and antihormonal therapy response in low-grade ovarian carcinoma

Background

Advanced low-grade ovarian carcinoma (LGOC) is difficult to treat. In several studies, high estrogen receptor (ER) protein expression was observed in patients with LGOC, which suggests that antihormonal therapy (AHT) is a treatment option. However, only a subgroup of patients respond to AHT, and this response cannot be adequately predicted by currently used immunohistochemistry (IHC). A possible explanation is that IHC only takes the ligand, but not the activity, of the whole signal transduction pathway (STP) into account. Therefore, in this study, the authors assessed whether functional STP activity can be an alternative tool to predict response to AHT in LGOC.

Methods

Tumor tissue samples were obtained from patients with primary or recurrent LGOC who subsequently received AHT. Histoscores of ER and progesterone receptor (PR) were determined. In addition, STP activity of the ER STP and of six other STPs known to play a role in ovarian cancer was assessed and compared with the STP activity of healthy postmenopausal fallopian tube epithelium.

Results

Patients who had normal ER STP activity had a progression-free survival (PFS) of 16.1 months. This was significantly shorter in patients who had low and very high ER STP activity, with a median PFS of 6.0 and 2.1 months, respectively (p < .001). Unlike ER histoscores, PR histoscores were strongly correlated to the ER STP activity and thus to PFS.

Conclusions

Aberrant low and very high functional ER STP activity and low PR histoscores in patients with LGOC indicate decreased response to AHT. ER IHC is not representative of functional ER STP activity and is not related to PFS.