Neurolymphomatosis secondary to primary central nervous system lymphoma: illustrative case.

BACKGROUND: Neurolymphomatosis (NL) is a rare disease defined as an invasion of lymphoma into peripheral nerves, nerve roots, or nerve plexuses, including the cranial nerves. No clear treatment protocols have yet been defined for this pathology. OBSERVATIONS: A woman in her 40s had a primary central nervous system lymphoma diagnosed from an intracranial tumor biopsy and underwent chemotherapy and radiation therapy. After she complained of pain in the trunk and extremities, magnetic resonance imaging and [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) performed 25 months after initial diagnosis revealed multiple lesions in the nerve ganglia, plexuses, and peripheral nerves from the cervical to the sacral spinal cord. Cerebrospinal fluid cytology revealed atypical lymphocytes and lymphoma dissemination in the spinal cavity. Based on these findings, NL was diagnosed. An intrathecal antineoplastic regimen temporarily reduced abnormal uptake of FDG, but the lesion recurred. After additional high-dose methotrexate therapy, FDG accumulation in the previously identified lesions disappeared. However, peripheral neuropathic pain and paraplegia remained. The patient died 9 months after the initial diagnosis of NL. LESSONS: The authors reported a case of NL following primary central nervous system lymphoma. In this case, FDG-PET proved useful for diagnosis, and high-dose methotrexate therapy was temporarily effective. https://thejns.org/doi/suppl/10.3171/CASE24107.

Effective design of PEGylated polyion complex (PIC) nanoparticles for enhancing PIC internalisation in cells utilising block copolymer combinations with mismatched ionic chain lengths.

In nanomedicine, PEGylation of nanomaterials poses a dilemma since it inhibits their interaction with target cells and enables their retention in target tissues despite its biocompatibility and nonspecific internalisation suppression. PEGylated polypeptide-based polyion complexes (PICs) are fabricated via the self-assembly of PEGylated aniomers and homocatiomers based on electrostatic interactions. We propose that various parameters like block copolymer design and PIC domain characteristics can enhance the cell-PEGylated PIC interactions. Remarkably, the properties of the PIC domain were tuned by the matched/mismatched ionomer chain lengths, PIC domain crosslinking degree, chemical modification of cationic species after crosslinking, PIC morphologies (vesicles/micelles) and polyethylene glycol (PEG) chain lengths. Cellular internalisation of the prepared PICs was evaluated using HeLa cells. Consequently, mismatched ionomer chain lengths and vesicle morphology enhanced cell-PIC interactions, and the states of ion pairing, particularly cationic residues, affected the internalisation behaviours of PICs via acetylation or guanidinylation of amino groups on catiomers. This treatment attenuated the cell-PIC interactions, possibly because of reduced interaction of PICs with negatively charged species on the cell-surface, glycosaminoglycans. Moreover, morphology and PEG length were correlated with PIC internalisation, in which PICs with longer and denser PEG were internalised less effectively. Cell line dependency was tested using RAW 264.7 macrophage cells; PIC recognition could be maintained after capping amino groups on catiomers, indicating that the remaining anionic groups were still effectively recognised by the scavenger receptors of macrophages. Our strategy for tuning the physicochemical properties of the PEGylated PIC nanocarriers is promising for overcoming the PEG issue.

Prediction of patient-specific quality assurance for volumetric modulated arc therapy using radiomics-based machine learning with dose distribution.

PURPOSE: We sought to develop machine learning models to predict the results of patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), which were represented by several dose-evaluation metrics-including the gamma passing rates (GPRs)-and criteria based on the radiomic features of 3D dose distribution in a phantom. METHODS: A total of 4,250 radiomic features of 3D dose distribution in a cylindrical dummy phantom for 140 arcs from 106 clinical VMAT plans were extracted. We obtained the following dose-evaluation metrics: GPRs with global and local normalization, the dose difference (DD) in 1% and 2% passing rates (DD1% and DD2%) for 10% and 50% dose threshold, and the distance-to-agreement in 1-mm and 2-mm passing rates (DTA1 mm and DTA2 mm) for 0.5%/mm and 1.0%.mm dose gradient threshold determined by measurement using a diode array in patient-specific QA. The machine learning regression models for predicting the values of the dose-evaluation metrics using the radiomic features were developed based on the elastic net (EN) and extra trees (ET) models. The feature selection and tuning of hyperparameters were performed with nested cross-validation in which four-fold cross-validation is used within the inner loop, and the performance of each model was evaluated in terms of the root mean square error (RMSE), the mean absolute error (MAE), and Spearman's rank correlation coefficient. RESULTS: The RMSE and MAE for the developed machine learning models ranged from <1% to nearly <10% depending on the dose-evaluation metric, the criteria, and dose and dose gradient thresholds used for both machine learning models. It was advantageous to focus on high dose region for predicating global GPR, DDs, and DTAs. For certain metrics and criteria, it was possible to create models applicable for patients' heterogeneity by training only with dose distributions in phantom. CONCLUSIONS: The developed machine learning models showed high performance for predicting dose-evaluation metrics especially for high dose region depending on the metric and criteria. Our results demonstrate that the radiomic features of dose distribution can be considered good indicators of the plan complexity and useful in predicting measured dose evaluation metrics.

Deep learning-based detection and classification of multi-leaf collimator modeling errors in volumetric modulated radiation therapy.

PURPOSE: The purpose of this study was to create and evaluate deep learning-based models to detect and classify errors of multi-leaf collimator (MLC) modeling parameters in volumetric modulated radiation therapy (VMAT), namely the transmission factor (TF) and the dosimetric leaf gap (DLG). METHODS: A total of 33 clinical VMAT plans for prostate and head-and-neck cancer were used, assuming a cylindrical and homogeneous phantom, and error plans were created by altering the original value of the TF and the DLG by ± 10, 20, and 30% in the treatment planning system (TPS). The Gaussian filters of σ = 0.5 $\sigma = 0.5$ and 1.0 were applied to the planar dose maps of the error-free plan to mimic the measurement dose map, and thus dose difference maps between the error-free and error plans were obtained. We evaluated 3 deep learning-based models, created to perform the following detections/classifications: (1) error-free versus TF error, (2) error-free versus DLG error, and (3) TF versus DLG error. Models to classify the sign of the errors were also created and evaluated. A gamma analysis was performed for comparison. RESULTS: The detection and classification of TF and DLG error were feasible for σ = 0.5 $\sigma = 0.5$ ; however, a considerable reduction of accuracy was observed for σ = 1.0 $\sigma = 1.0$ depending on the magnitude of error and treatment site. The sign of errors was detectable by the specifically trained models for σ = 0.5 $\sigma = 0.5$ and 1.0. The gamma analysis could not detect errors. CONCLUSIONS: We demonstrated that the deep learning-based models could feasibly detect and classify TF and DLG errors in VMAT dose distributions, depending on the magnitude of the error, treatment site, and the degree of mimicked measurement doses.

Verification of Qfix Encompass™ couch modeling using the Acuros XB algorithm and HypeArc™ using a high-spatial-resolution two-dimensional diode array.

We modeled the Qfix Encompass™ immobilization system and further verified the calculated dose distribution of the AcurosXB (AXB) dose calculation algorithm using SRS MapCHECKⓇ (SRSMC) in the HyperArc™ (HA) clinical plan. An Encompass system with a StereoPHAN™ QA phantom was scanned by SOMATOM go.Sim and imported to an Eclipse™ treatment planning system to create a treatment plan for Encompass modeling. The Encompass modeling was performed in the StereoPHAN with a pinpoint ion chamber for 6 MV and 6 MV flattening filter free (6 MV FFF), and 2 × 2 cm2, 4 × 4 cm2, and 6 × 6 cm2 irradiation field sizes. The dose calculation algorithm used was AXB ver. 15.5 with a 1.0 mm calculation grid size. The Hounsfield unit (HU) values of the Encompass modeling were set to 400, -100, -200, and -300 for Encompass, and -400, -600, -700, and -800 for the Encompass base. We evaluated the dose distribution after Encompass modeling by SRSMC using gamma analysis in 12 patients. We adopted HU values of -200 for Encompass, -800 for Encompass base for 6 MV, and -200 for Encompass and -700 for Encompass. Base for 6 MV FFF was adopted as the HU values for the Encompass modeling based on the measurement results. The proposed Encompass modeling resulted in a mean pass rate evaluation >98% for both 6 MV and 6 MV FFF when the 1%/1 mm criterion was used, demonstrating that the proposed HU value can be adopted to calculate more accurate dose distributions.

Maximum distance in single-isocenter technique of stereotactic radiosurgery with rotational error using margin-based analysis.

Through geometrical simulation, we evaluated the effect of rotational error in patient setup on geometrical coverage and calculated the maximum distance between the isocenter and target, where the clinical PTV margin secures geometrical coverage with a single-isocenter technique. We used simulated spherical GTVs with diameters of 1.0 (GTV 1), 1.5 (GTV 2), 2.0 (GTV 3), and 3.0 cm (GTV 4). The location of the target center was set such that the distance between the target and isocenter ranged from 0 to 15 cm. We created geometrical coverage vectors so that each target was entirely covered by 100% of the prescribed dose. The vectors of the target positions were simultaneously rotated within a range of 0°-2.0° around the x-, y-, and z-axes. For each rotational error, the reduction in geometrical coverage of the targets was calculated and compared with that obtained for a rotational error of 0°. The tolerance value of the geometrical coverage reduction was defined as 5% of the GTV. The maximum distance that satisfied the 5% tolerance value for different values of rotational error at a clinical PTV margin of 0.1 cm was calculated. When the rotational errors were 0.5° for a 0.1 cm PTV margin, the maximum distances were as follows: GTV 1: 7.6 cm; GTV 2: 10.9 cm; GTV 3: 14.3 cm; and GTV 4: 21.4 cm. It might be advisable to exclude targets that are > 7.6 cm away from the isocenter with a single-isocenter technique to satisfy the tolerance value for all GTVs.

Detecting MLC modeling errors using radiomics-based machine learning in patient-specific QA with an EPID for intensity-modulated radiation therapy.

PURPOSE: We sought to develop machine learning models to detect multileaf collimator (MLC) modeling errors with the use of radiomic features of fluence maps measured in patient-specific quality assurance (QA) for intensity-modulated radiation therapy (IMRT) with an electric portal imaging device (EPID). METHODS: Fluence maps measured with EPID for 38 beams from 19 clinical IMRT plans were assessed. Plans with various degrees of error in MLC modeling parameters [i.e., MLC transmission factor (TF) and dosimetric leaf gap (DLG)] and plans with an MLC positional error for comparison were created. For a total of 152 error plans for each type of error, we calculated fluence difference maps for each beam by subtracting the calculated maps from the measured maps. A total of 837 radiomic features were extracted from each fluence difference map, and we determined the number of features used for the training dataset in the machine learning models by using random forest regression. Machine learning models using the five typical algorithms [decision tree, k-nearest neighbor (kNN), support vector machine (SVM), logistic regression, and random forest] for binary classification between the error-free plan and the plan with the corresponding error for each type of error were developed. We used part of the total dataset to perform fourfold cross-validation to tune the models, and we used the remaining test dataset to evaluate the performance of the developed models. A gamma analysis was also performed between the measured and calculated fluence maps with the criteria of 3%/2 and 2%/2 mm for all of the types of error. RESULTS: The radiomic features and its optimal number were similar for the models for the TF and the DLG error detection, which was different from the MLC positional error. The highest sensitivity was obtained as 0.913 for the TF error with SVM and logistic regression, 0.978 for the DLG error with kNN and SVM, and 1.000 for the MLC positional error with kNN, SVM, and random forest. The highest specificity was obtained as 1.000 for the TF error with a decision tree, SVM, and logistic regression, 1.000 for the DLG error with a decision tree, logistic regression, and random forest, and 0.909 for the MLC positional error with a decision tree and logistic regression. The gamma analysis showed the poorest performance in which sensitivities were 0.737 for the TF error and the DLG error and 0.882 for the MLC positional error for 3%/2 mm. The addition of another type of error to fluence maps significantly reduced the sensitivity for the TF and the DLG error, whereas no effect was observed for the MLC positional error detection. CONCLUSIONS: Compared to the conventional gamma analysis, the radiomics-based machine learning models showed higher sensitivity and specificity in detecting a single type of the MLC modeling error and the MLC positional error. Although the developed models need further improvement for detecting multiple types of error, radiomics-based IMRT QA was shown to be a promising approach for detecting the MLC modeling error.

Effect of setup error in the single-isocenter technique on stereotactic radiosurgery for multiple brain metastases.

In conventional stereotactic radiosurgery (SRS), treatment of multiple brain metastases using multiple isocenters is time-consuming resulting in long dose delivery times for patients. A single-isocenter technique has been developed which enables the simultaneous irradiation of multiple targets at one isocenter. This technique requires accurate positioning of the patient to ensure optimal dose coverage. We evaluated the effect of six degrees of freedom (6DoF) setup errors in patient setups on SRS dose distributions for multiple brain metastases using a single-isocenter technique. We used simulated spherical gross tumor volumes (GTVs) with diameters ranging from 1.0 to 3.0 cm. The distance from the isocenter to the target's center was varied from 0 to 15 cm. We created dose distributions so that each target was entirely covered by 100% of the prescribed dose. The target's position vectors were rotated from 0°-2.0° and translated from 0-1.0 mm with respect to the three axes in space. The reduction in dose coverage for the targets for each setup error was calculated and compared with zero setup error. The calculated margins for the GTV necessary to satisfy the tolerance values for loss of GTV coverage of 3% to 10% were defined as coverage-based margins. In addition, the maximum isocenter to target distance for different 6DoF setup errors was calculated to satisfy the tolerance values. The dose coverage reduction and coverage-based margins increased as the target diameter decreased, and the distance and 6DoF setup error increased. An increase in setup error when a single-isocenter technique is used may increase the risk of missing the tumor; this risk increases with increasing distance from the isocenter and decreasing tumor size.

Dosimetric comparison of analytic anisotropic algorithm and Acuros XB algorithm in VMAT plans for high-grade glioma.

PURPOSE: To investigate the dosimetric impact between the anisotropic analytical algorithm (AAA) and the Acuros XB (AXB) algorithm in volumetric-modulated arc therapy (VMAT) plans for high-grade glioma (HGG). METHODS: We used a heterogeneous phantom to quantify the agreement between the measured and calculated doses from the AAA and from the AXB. We then analyzed 14 patients with HGG treated by VMAT, using the AAA. We newly created AXB plans for each corresponding AAA plan under the following conditions: (1) re-calculation for the same number of monitor units with an identical beam and leaf setup, and (2) re-optimization under the same conditions of dose constraints. The dose coverage for the planning target volume (PTV) was evaluated by dividing the coverage into the skull, air, and soft-tissue regions. RESULTS: Compared to the results obtained with the AAA, the AXB results were in good agreement with the measured profiles. The dose differences in the PTV between the AAA and re-calculated AXB plans were large in the skull region contained in the target. The dose difference in the PTV in both types of plan was significantly correlated with the volume of the skull contained in the target (r = 0.71, p = 0.0042). A re-optimized AXB plan's dose difference was lower vs. the re-calculated AXB plan's. CONCLUSIONS: We observed dose differences between the AAA and AXB plans, in particular in the cases in which the skull region of the target was large. Considering the phantom measurement results, the AXB algorithm should be used in VMAT plans for HGG.

[Investigation of Estimation Accuracy of Phantom Scatter Factor by Clarkson Method Considering Depth in MLC Irregular Field].

In monitor unit (MU) independent verification by calculation for irregular field (MLC field) using multileaf collimator in X-ray therapy, it has become common to use collimator scatter factor (Sc) and phantom scatter factor (Sp) instead of total scatter factor (Sc, p). It is usually expressed as Sc, p (A)=Sc (A)×Sp (A), and the field size A is considered but the depth d is not. Sc is data of in-air output, and measure with a mini-phantom at constant depth to remove electron contamination. On the other hand, Sp is obtained from measurement data of Sc, p and Sc, and can be expressed as Sc, p (d, A)=Sc (constant depth, A)×Sp (d, A) at an arbitrary depth d, thus Sp depends on the depth of Sc, p. Therefore, Sp needs to consider depth. In addition, a linear accelerator equipped with the tertiary MLC has two field sizes, that are collimator field by upper and lower collimators and MLC field by tertiary MLC below them. In MU independent verification by calculation, it is often used that the estimated value of Sp obtained by converting MLC field to equivalent square field and referring to data of Sp in square field. To convert the MLC field to equivalent square field, a conversion formula from sector radius r to equivalent square field L by Clarkson's sector integration (Clarkson method) is used. In this study, using 24 types of MLC fields to evaluate estimation accuracy due to the difference of conversion formula in Clarkson method, we estimated value of Sp using r=0.5611L of B-Clarkson method and using r=0.5580L of A-Clarkson method. And the difference with the measured value of Sp obtained by measuring Sc, p and Sc in the same MLC fields was compared. While, to evaluate estimation accuracy due to the different depths using these Clarkson methods, the difference between estimated value and measured value of Sp similarly obtained at depth of 5, 10 and 15 cm was compared. As results, estimated value of Sp using A-Clarkson method than using B-Clarkson method was close to measured value, and it was the same trend at depth of 5, 10 and 15 cm. Therefore, it was suggested that estimation accuracy of Sp by A-Clarkson method is higher than B-Clarkson method when verifying beams with different depths in MU independent verification by calculation for MLC field.

[Investigation of the Influence of the Conversion Method to Equivalent Square Field on the Depth Direction of Phantom Scatter Factor].

In X-ray therapy, equivalent square field (side of equivalent square field) is important because it influences the accuracy of independent verification of monitor unit (MU) by calculation. To calculate the side of equivalent square field for rectangular fields, we often use a table of domestic standard measurement method (Day's method), or A/P method calculated by area-perimeter ratio. The sides of equivalent square fields of these methods are assumed to be unchanged by depth and energy, but there are reports that it is not valid. Therefore, the depth dependency of side of equivalent square fields of Day's method, A/P method, and area ratio correction (ARC) method was compared by measuring phantom scatter factors (Sp). From the analysis of Sp measured at different depths, the estimated value of Sp on the equivalent square side of the Day's method and A/P method had a depth dependency that the difference from the measured value was large when the measurement depth was deep. The estimated value of Sp on the equivalent square side of the ARC method had a small difference from the measured value even when the measurement depth was deep, and the depth dependency was small compared with the Day's method and the A/P method. Side of equivalent square field of ARC method had a smaller difference of depth dependency than in the case of Day's method and A/P method. Therefore, in the independent verification of MU for rectangular field, using the equivalent square side of the ARC method is better.

The impact of the three degrees-of-freedom fiducial marker-based setup compared to soft tissue-based setup in hypofractionated intensity-modulated radiotherapy for prostate cancer.

PURPOSE: We evaluated the setup accuracy of a three-degree-of-freedom fiducial marker (3DOF-FM)-based setup compared to a soft tissue (ST)-based setup in hypofractionated intensity-modulated radiotherapy (IMRT) for prostate cancer. MATERIALS AND METHODS: We analyzed the setup accuracy for 17 consecutive prostate cancer patients with three implanted FMs who underwent hypofractionated IMRT. The 3DOF-ST-based setup using cone-beam computed tomography (CT) was performed after a six DOF-bony structure (BS)-based setup using an ExacTrac x-ray system. The 3DOF-FM-based matching using the ExacTrac x-ray system was done during the BS- and ST-based setups. We determined the mean absolute differences and the correlation between the FM- and ST-based translational shifts relative to the BS-based setup position. The rotational mean shifts detected by the ExacTrac x-ray system were also evaluated. RESULTS: The mean differences in the anterior-posterior (AP), superior-inferior (SI), and left-right (LR) dimensions were 0.69, 0.0, and 0.30 mm, respectively. The Pearson correlation coefficients for both shifts were 0.92 for AP, 0.91 for SI, and 0.68 for LR. The percentages of shift agreements within 2 mm were 85% for AP, 93% for SI, and 99% for LR. The absolute values of rotational shifts were 0.1° for AP, 0.3°, and 1.2° for LR. CONCLUSIONS: The setup accuracy of the 3DOF-FM-based setup has the potential to be interchangeable with a ST-based setup. Our data are likely to be useful in clinical practice along with the popularization of the hypofractionated IMRT in prostate cancer.

Persistent ventricular preexcitation despite right bundle branch block.

A 44-year-old man with a history of ventricular preexcitation and supraventricular tachycardia was evaluated. The baseline electrocardiogram exhibited ventricular preexcitation with a normal PR interval and a minimally negative delta wave in lead V1 and positive delta waves in the inferior leads. The administration of adenosine resulted in a progressive prolongation of the PR interval with a fixed preexcitation degree, suggesting the presence of antegrade conduction over the fasciculo-ventricular pathway. When complete right bundle branch block occurred, the degree of preexcitation never changed. These findings suggested that the fasciculo-ventricular pathway was likely to be connected to the left-sided His-Purkinje system.

[A Case of Advanced Rectal Cancer in Which Long-Term Disease-Free Survival Was Achieved by Multidisciplinary Therapy].

The is a case involving a 55-year-old man with advanced rectal cancer(type 3). MRI showed urinary tract and regional lymph node metastases without distant metastasis. The tumor was reduced(PR)after neoadjuvant chemotherapy(mFOL FOX6 plus Bmab, 4 courses). The patient underwent an abdominoperineal resection. Because infiltration of the tumor into the lower urinary tract was deep, it was also resected and repaired. The clip was placed to mark the repaired region. Pathological examination revealed that excision stump at the anterior wall of the urethra was cancer positive without lymph node metastasis. He was then administered chemotherapy(mFOLFOX6 4 courses)and irradiated 60 Gy in both sides of the inguinal lymph node to prevent metastasis to the pelvicdomain. One year and 6 months postoperatively, as the left inguinal lymph node swelled at 3.7 cm irregularly, he further received chemotherapy(FOLFIRI 8 courses). The size of the lymph node became normal with a good response to FOLFIRI. Six years postoperatively, he remains alive and well with no evidence of recurrence.

Successful percutaneous epicardial catheter ablation of ventricular tachycardia arising from the crux of the heart in a patient with prior coronary artery bypass grafting.

A 63-year-old man with a history of remote inferior myocardial infarction and coronary artery bypass grafting (CABG) underwent catheter ablation of ventricular tachycardia (VT). Epicardial catheter ablation of the VT was successful at the crux of the heart despite limited mapping within the pericardial space due to pericardial adhesion. Percutaneous subxiphoidal pericardial approach is usually impossible in patients with a history of open heart surgery due to pericardial adhesions. This report suggested that epicardial VT arising from the crux of the heart could be successfully treated by catheter ablation via subxiphoidal pericardial approach despite pericardial adhesions complicated by prior CABG.

A study on a dental device for the prevention of mucosal dose enhancement caused by backscatter radiation from dental alloy during external beam radiotherapy.

The changes in dose distribution caused by backscatter radiation from a common commercial dental alloy (Au-Ag-Pd dental alloy; DA) were investigated to identify the optimal material and thicknesses of a dental device (DD) for effective prevention of mucositis. To this end, 1 cm3 of DA was irradiated with a 6-MV X-ray beam (100 MU) in a field size of 10 × 10 cm2 using a Novalis TX linear accelerator. Ethylene vinyl acetate copolymer, polyolefin elastomer, and polyethylene terephthalate (PET) were selected as DD materials. The depth dose along the central axis was determined with respect to the presence/absence of DA and DDs at thicknesses of 1-10 mm using a parallel-plate ionization chamber. The dose in the absence of DDs showed the lowest value at a distance of 5 mm from the DA surface and gradually increased with distance between the measurement point and the DA surface for distances of ≥5 mm. Except for PET, no significant difference between the DA dose curves for the presence and absence of DDs was observed. In the dose curve, PET showed a slightly higher dose for DA with DD than for DA without DD for thicknesses of ≥4 mm. The findings herein suggest that the optimal DD material for preventing local dose enhancement of the mucosa caused by DA backscatter radiation should have a relatively low atomic number and physical density and that optimal DD thickness should be chosen considering backscatter radiation and percentage depth dose.

ASSOCIATION BETWEEN THE RISK OF TESTICULAR TORSION AMONG ACUTE SCROTUM AND AMBIENT TEMPERATURE.

(Objectives) Testicular torsion (TT) is a socially and clinically important urological emergency condition because delayed diagnosis and treatment can lead to testicular loss. Although a possible association between TT and low ambient temperature has been argued, the clinical significance of the association has not been fully elucidated. We retrospectively collected acute scrotum cases and investigated the association between the risk of TT among acute scrotums and ambient temperatures on the day of onset. (Patients and methods) We studied 105 consecutive acute scrotum patients with suspected TT who underwent urgent surgical exploration between October 2004 and October 2014. The patients' age, residential area, time and date of onset, laboratory findings, and operative findings were collected from their medical records. Climate data, including daily mean ambient temperature (DMAT), diurnal temperature change (DTC), humidity, and atmospheric pressure at the time of onset, were obtained from the Japan Meteorological Agency website. The chi-square and Wilcoxon rank sum tests were used to evaluate statistical differences. Logistic regression analysis used to identify significant predictors of TT. (Results) The median age of the patients was 13 years (range, 1-43 years). The affected side was the right/left/bilateral side in 46/58/1 of the patients. Surgical exploration revealed TT in 67 patients. The remaining 38 non-TT patients included 12 with testicular appendage torsions, 12 with epididymal appendage torsions, 9 with epididymitis, 2 with orchitis, 2 with idiopathic hematomas, and 1 with allergic purpura. The median DMATs at the day of onset were 10.8°C (1.8-29.4°C) in the TT patients and 19.4°C (1.9-29.1°C) in the non-TT patients. The incidence of TT among the patients with acute scrotum explored surgically (TT incidence) in days with DMATs <15°C (80%) was significantly higher than that in days with DMATs ≥ 15°C (45%; p<0.001). During days with DMATs ≥15°C, the TT incidence in days with DTCs ≥10°C (62%) was significantly higher than that in days with DTCs <10°C (32%; p=0.037). Multivariate analysis revealed higher age (≥14), low serum C-reactive protein level (<0.5 ng/ml) and low DMAT (<15°C) were significant risk factor for TT in patients with acute scrotum undergoing surgery. (Conclusions) It should be noted that in this study, the onset of acute scrotum during days with low ambient temperatures or large DTCs was associated with a moderate to high possibility of TT.

Development of a membrane impregnated with a poly(dimethylsiloxane)/poly(ethylene glycol) copolymer for a high-throughput screening of the permeability of drugs, cosmetics, and other chemicals across the human skin.

We aimed to develop a high-throughput screening (HTS) system for preliminary predictions of human skin permeability by using an artificial membrane that can mimic the permeation behaviour of lipophilic and hydrophilic compounds across the human skin. In this study, we synthesized a copolymer containing poly(dimethylsiloxane) (PDMS) and poly(ethylene glycol) (PEG) 6000 and impregnated it onto a supportive membrane filter to prepare a PDMS/PEG 6000 copolymer-impregnated membrane. In addition, we synthesized another polymer without PEG units and used it to prepare an impregnated membrane for determining the role of PEG 6000 units in the PDMS/PEG 6000 copolymer-impregnated membrane. The permeation characteristics of the impregnated membranes were evaluated on the basis of the permeability coefficients of 12 model compounds with different lipophilicities, by using a 2-chamber diffusion cell, and these permeability coefficients were compared with those across the human skin. We obtained a good correlation between the permeability coefficients across the PDMS/PEG 6000 copolymer-impregnated membrane and human skin. Further, we evaluated the permeation characteristics of a 96-well plate model of the PDMS/PEG 6000 copolymer by using 6 model compounds. We obtained an ideal correlation between the permeability coefficients across the PDMS/PEG 6000 copolymer using a 96-well plate and those across the human skin. Thus, the PDMS/PEG 6000 copolymer would be a good candidate for preliminary evaluation of the permeability of lipophilic and hydrophilic compounds across the human skin.