UNASSIGNED: At our department we have a dedicated 1.5 Tesla MRI/HDR brachytherapy suite, which provides the possibility of repeated MRI scanning before, during and after applicator insertion and before and/or after irradiation for patients with advanced cervical cancer. In this study we analysed the effect of this adaptive workflow. We investigated the number of interventions, their impact on organ doses (OAR) and the respective dose differences between total prescribed and total delivered doses.
UNASSIGNED: Seventy patients with locally advanced cervical cancer FIGO2009 stages IB-IVA, treated from June 2016 till August 2020, were retrospectively analysed. The standard brachytherapy schedule consisted of two applicator insertions and delivery of three or four HDR fractions.OARs were recontoured on the repeated MRI scans. The D2cm3 dose difference between total prescribed and total delivered dose for bladder, rectum, sigmoid and bowel were calculated.
UNASSIGNED: In total 153 interventions were performed, 3 replacements of the applicator, 23 adaptations of needle positions, bladder filling was changed 74 times and repeated rectal degassing 53 times. The impact of the rectal interventions was on average -1.2 Gy EQD23. Dose differences between total delivered and total prescribed D2cm3 for bladder, rectum, sigmoid and bowel were -0.6, 0.3, 2.2 and -0.6 Gy EQD23, respectively.
UNASSIGNED: An MRI scanner integrated into the brachytherapy suite enables multiple interventions based on the scans before treatment planning and dose delivery. This allows for customized treatment according to the changing anatomy of the individual patient and a better estimation of the delivered dose.

UNASSIGNED: To evaluate organ at risk (OAR) auto-segmentation in the head and neck region of computed tomography images using two different commercially available deep-learning-based auto-segmentation (DLAS) tools in a single institutional clinical applications.
UNASSIGNED: Twenty-two OARs were manually contoured by clinicians according to published guidelines on planning computed tomography (pCT) images for 40 clinical head and neck cancer (HNC) cases. Automatic contours were generated for each patient using two deep-learning-based auto-segmentation models-Manteia AccuContour and MIM ProtégéAI. The accuracy and integrity of autocontours (ACs) were then compared to expert contours (ECs) using the Sørensen-Dice similarity coefficient (DSC) and Mean Distance (MD) metrics.
UNASSIGNED: ACs were generated for 22 OARs using AccuContour and 17 OARs using ProtégéAI with average contour generation time of 1 min/patient and 5 min/patient respectively. EC and AC agreement was highest for the mandible (DSC 0.90 ± 0.16) and (DSC 0.91 ± 0.03), and lowest for the chiasm (DSC 0.28 ± 0.14) and (DSC 0.30 ± 0.14) for AccuContour and ProtégéAI respectively. Using AccuContour, the average MD was<1mm for 10 of the 22 OARs contoured, 1-2mm for 6 OARs, and 2-3mm for 6 OARs. For ProtégéAI, the average mean distance was<1mm for 8 out of 17 OARs, 1-2mm for 6 OARs, and 2-3mm for 3 OARs.
UNASSIGNED: Both DLAS programs were proven to be valuable tools to significantly reduce the time required to generate large amounts of OAR contours in the head and neck region, even though manual editing of ACs is likely needed prior to implementation into treatment planning. The DSCs and MDs achieved were similar to those reported in other studies that evaluated various other DLAS solutions. Still, small volume structures with nonideal contrast in CT images, such as nerves, are very challenging and will require additional solutions to achieve sufficient results.

A neural network method was used to establish a dose prediction model for organs at risk (OARs) during intensity-modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC).
In total, 103 patients with NPC were randomly selected for IMRT. Suborgans were automatically generated for OARs using ring structures based on distance to the target using a MATLAB program and the corresponding volume of each suborgan was determined. The correlation between the volume of each suborgan and the dose to each OAR was analysed and neural network prediction models of the OAR dose were established using the MATLAB Neural Net Fitting application. The R-value and mean square error in the regression analysis were used to evaluate the prediction model.
The OAR dose was related to the volume of the corresponding sub-OAR. The average R-values for the normalised mean dose (Dnmean) to parallel organs and serial organs and the normalised maximum dose (Dn0) to serial organs in the training set were 0.880, 0.927 and 0.905, respectively. The mean square error for each OAR in the prediction model was low (ranging from 1.72 × 10-4 to 7.06 × 10-3).
The neural network-based model for predicting OAR dose during IMRT for NPC is simple, reliable and worth further investigation and application.

UNASSIGNED: Radiotherapy is one of the most important treatments for high-grade glioma (HGG), but the best way to delineate the target areas for radiotherapy remains controversial, so our aim was to compare the dosimetric differences in radiation treatment plans generated based on the European Organization for Research and Treatment of Cancer (EORTC) and National Research Group (NRG) consensus to provide evidence for optimal target delineation for HGG.
UNASSIGNED: We prospectively enrolled 13 patients with a confirmed HGG from our hospital and assessed dosimetric differences in radiotherapy treatment plans generated according to the EORTC and NRG-2019 guidelines. For each patient, two treatment plans were generated. Dosimetric parameters were compared by dose-volume histograms for each plan.
UNASSIGNED: The median volume for planning target volume (PTV) of EORTC plans, PTV1 of NRG-2019 plans, and PTV2 of NRG-2019 plans were 336.6 cm3 (range, 161.1-511.5 cm3), 365.3 cm3 (range, 123.4-535.0 cm3), and 263.2 cm3 (range, 116.8-497.7 cm3), respectively. Both treatment plans were found to have similar efficiency and evaluated as acceptable for patient treatment. Both treatment plans showed well conformal index and homogeneity index and were not statistically significantly different (P = 0.397 and P = 0.427, respectively). There was no significant difference in the volume percent of brain irradiated to 30, 46, and 60 Gy according to different target delineations (P = 0.397, P = 0.590, and P = 0.739, respectively). These two plans also showed no significant differences in the doses to the brain stem, optic chiasm, left and right optic nerves, left and right lens, left and right eyes, pituitary, and left and right temporal lobes (P = 0.858, P = 0.858, P = 0.701 and P = 0.794, P = 0.701 and P = 0.427, P = 0.489 and P = 0.898, P = 0.626, and P = 0.942 and P = 0.161, respectively).
UNASSIGNED: The NRG-2019 project did not increase the dose of organs at risk (OARs) radiation. This is a significant finding that further lays the groundwork for the application of the NRG-2019 consensus in the treatment of patients with HGGs.
UNASSIGNED: The effect of radiotherapy target area and glial fibrillary acidic protein (GFAP) on the prognosis of high-grade glioma and its mechanism, number ChiCTR2100046667. Registered 26 May 2021.

UNASSIGNED: To analyze the effects of different bladder and rectal volumes on the dose of organ at risks (OARs) and primary tumors following uniform preparation procedure.
UNASSIGNED: In this retrospective study, a total of 60 patients with cervical cancer treated with external beam radiation therapy (EBRT) combined with chemotherapy and brachytherapy (BT) during 2019-2022 were included (300 insertions). Then, tandem-ovoid applicators were placed and computed tomography (CT) scanning was performed after each insertion. Delineation of OARs and clinical target volumes (CTVs) were done according to GEC-ESTRO group recommendations. Finally, doses of high-risk clinical target volume (HR-CTV) and OARs were obtained from dose volume histogram (DVH) automatically generated by BT treatment planning system.
UNASSIGNED: Following a uniform preparation procedure, the median bladder volume of 68.36 cc (range, 29.9-235.68 cc) was in optimal agreement with the recommended bladder volume of ≤ 70 ml, which avoided more manipulation and possible risk of adverse events during general anesthesia. As the bladder filling volume increased, there was no corresponding increase in rectal, HR-CTV, and small bowel volumes, while the sigmoid colon volume decreased. The median rectal volume was 54.95 cc (range, 24.92-168.1 cc), and as the rectal volume increased, HR-CTV, sigmoid colon, and rectum volumes increased, and conversely, small bowel volume decreased. HR-CTV changes with volume affected the rectum, bladder, and HR-CTV, but not the sigmoid colon and small intestine.
UNASSIGNED: Following a uniform preparation procedure, the bladder and rectum can also be controlled to an optimal volume (B ≤ 70 cc, R ≈ 40 cc), which is related to the dose of the bladder, rectum, and sigmoid colon.

An important phase of radiation treatment planning is the accurate contouring of the organs at risk (OAR), which is necessary for the dose distribution calculation. The manual contouring approach currently used in clinical practice is tedious, time-consuming, and prone to inter and intra-observer variation. Therefore, a deep learning-based auto contouring tool can solve these issues by accurately delineating OARs on the computed tomography (CT) images. This paper proposes a two-stage deep learning-based segmentation model with an attention mechanism that automatically delineates OARs in thoracic CT images. After preprocessing the input CT volume, a 3D U-Net architecture will locate each organ to generate cropped images for the segmentation network. Next, two differently configured U-Net-based networks will perform the segmentation of large organs-left lung, right lung, heart, and small organs-esophagus and spinal cord, respectively. A post-processing step integrates all the individually-segmented organs to generate the final result. The suggested model outperformed the state-of-the-art approaches in terms of dice similarity coefficient (DSC) values for the lungs and the heart. It is worth mentioning that the proposed model achieved a dice score of 0.941, which is 1.1% higher than the best previous dice score, in the case of the heart, an important organ in the human body. Moreover, the clinical acceptance of the results is verified using dosimetric analysis. To delineate all five organs on a CT scan of size [Formula: see text], our model takes only 8.61 s. The proposed open-source automatic contouring tool can generate accurate contours in minimal time, consequently speeding up the treatment time and reducing the treatment cost.

The early postoperative recovery period following unicompartmental (UKA) and total knee arthroplasty (TKA) is an important area for research with increasingly sensitive metrics and new technologies. This study uses 2 recently developed patient-reported scores to compare the recovery following UKA and TKA.
Two consecutive cohorts of 37 UKAs and 33 TKAs completed the Oxford Arthroplasty Early Recovery Score (OARS) and the Oxford Arthroplasty Early Change Score (OACS) on days 1, 2, 3, 7, 14, and week 6. The Short Form-36 version 2 was also completed on weeks 1, 2, and 6. Improvements within cohorts and comparisons between cohorts were assessed.
For both UKA and TKA the speed of recovery was rapid early on and then progressively decreased. At all time points, the UKA cohort reported similar or significantly better scores than the TKA cohort. The overall OARS (P < .001) showed that UKA recovered, shown as improvement on the OARS, 2-3 times faster than TKA. OARS subscales demonstrated that UKA had better Function/Mobility (P = .003) particularly early in the recovery, and better Nausea/Feeling Unwell (P < .001) and Fatigue/Sleep (P = .009) later in the recovery. UKA also had less pain at 2 weeks (P = .03). There was no significant difference between UKA and TKA OACS. UKA had significantly better scores in 3 of the 8 Short Form-36 domains, with the largest difference being in Role-Emotional (P = .003).
The OARS is useful for the assessment of postoperative recovery. This study provides direct evidence that recovery following UKA is better and 2-3 times faster than following TKA. All differences may be explained by the less invasive nature of UKA.

This study aimed to evaluate variations in dose distribution within the target volume and dose received by the organs at risk (OARs) for different tangential field arrangements during three-dimensional (3D) conformal treatment planning for left-sided breast cancer. Computed tomography (CT) images of 25 breast cancer patients were included, and three different mono-isocentric half-block (MIHB) treatment plans-parallel central axis technique (PCAXT), posterior border parallel technique (PBPT), and parallel quadrant technique (PQUDT)-were considered for each patient. The dosimetric and geometric parameters related to each followed plan were then extracted for the planning target volume (PTV) and the OARs, and compared. The results showed no significant differences among the extracted dosimetric and geometric parameters of the OARs for the different plans, while the Dmax, V95%, homogeneity index (HI), and conformity index (CI) values related to the PTV were significantly different (P < 0.05). The lowest Dmax and V95% values inside the PTV were related to the PCAXT plan. The best HI was achieved with the PBPT plan, whereas the best CI was observed for the PCAXT plan. The best correlation between the geometric and dosimetric parameters of the OARs was between V5Gy-central lung distance for the ipsilateral lung and the V5Gy-maximum heart distance for the heart in all plans. These results demonstrate that variations in the tangential field arrangement at the posterior border for optimal coverage of the PTV may not considerably affect the dose received by the OARs.

To document the prevalence of functional impairment in middle-aged and older adults from rural regions and to determine urban-rural differences.
We have conducted a secondary analysis using data from an ongoing population-based cohort study, the Canadian Longitudinal Study on Aging (CLSA). We used a cross-sectional sample from the baseline wave of the \"tracking cohort.\" The definition of rurality was the same as the one used in the CLSA sampling frame and based on the 2006 census. This definition includes rural areas, defined as all territory lying outside of population centers, and population centers, which collectively cover all of Canada. We grouped these into \"Urban,\" \"Peri-urban,\" \"Mixed\" (areas with both rural and urban areas), and \"Rural,\" and compared functional status across these groups. Functional status was measured using the Older Americans Resource Survey (OARS) and categorized as not impaired versus having any functional impairment. Logistic regression models were constructed for the outcome of functional status and adjusted for covariates.
No differences were found in functional status between those living in rural, mixed, peri-urban, and urban areas in unadjusted analyses and in analyses adjusting for sociodemographic and health-related factors. There were no rural-urban differences in any of the individual items on the OARS scales.
We found no rural-urban differences in functional status.

UNASSIGNED: The aim of this paper is to describe the impact of COVID-19 on spine surgery services in a district general hospital in England in order to understand the spinal service provisions that may be required during a pandemic.
UNASSIGNED: A prospective cohort study was undertaken between 17 March 2020 and 30 April 2020 and compared with retrospective data from same time period in 2019. We compared the number of patients requiring acute hospital admission or orthopaedic referrals and indications of referrals from our admission sheets and obtained operative data from our theatre software.
UNASSIGNED: Between 17 March to 30 April 2020, there were 48 acute spine referrals as compared to 68 acute referrals during the same time period last year. In the 2019 period, 69% (47/68) of cases referred to the on-call team presented with back pain, radiculopathy or myelopathy compared to 43% (21/48) in the 2020 period. Almost 20% (14/68) of spine referrals consisted of spine trauma as compared to 35% (17/48) this year. There were no confirmed cases of cauda equine last year during this time. Overall, 150 spine cases were carried out during this time period last year, and 261 spine elective cases were cancelled since 17 March 2020.
UNASSIGNED: We recommend following steps can be helpful to deal with similar situations or new pandemics in future:24 hours on-call spine service during the pandemic.Clinical criteria in place to prioritize urgent spinal cases.Pre-screening spine patients before elective operating.Start of separate specialist trauma list for patients needing urgent surgeries.
UNASSIGNED: This paper highlights the impact of COVID-19 pandemic in a district general hospital of England. We demonstrate a decrease in hospital attendances of spine pathologies, despite an increase in emergency spine operations.Cite this article: Bone Joint Open 2020;1-6:281-286.