Assessing tumor volumetric reduction with consideration for setup errors based on mathematical tumor model and microdosimetric kinetic model in single-isocenter VMAT for brain metastases.

The volumetric reduction rate (VRR) was evaluated with consideration for six degrees-of-freedom (6DoF) patient setup errors based on a mathematical tumor model in single-isocenter volumetric modulated arc therapy (SI-VMAT) for brain metastases. Simulated gross tumor volumes (GTV) of 1.0 cm and dose distribution were created (27 Gy/3 fractions). The distance between the GTV center and isocenter (d) was set at 0-10 cm. The GTV was translated within 0-1.0 mm (Trans) and rotated within 0-1.0° (Rot) in the three axis directions using affine transformation. The tumor growth volume was calculated using a multicomponent mathematical model (MCTM), and lethal effects of irradiation and repair from damage during irradiation were calculated by a microdosimetric kinetic model (MKM) for non-small cell lung cancer (NSCLC) A549 and NCI-H460 (H460) cells. The VRRs were calculated 5 days after the end of irradiation using the physical dose to the GTV for varying d and 6DoF setup errors. The tolerance value of VRR, the GTV volume reduction rate, was set at 5%, based on the pre-irradiation GTV volume. With the exception of the only one A549 condition where (Trans, Rot) = (1.0 mm, 1.0°) was repeated for 3 fractions, all conditions met all the tolerance VRR values for A549 and H460 cells with varying d from 0 to 10 cm. Evaluation based on the mathematical tumor model suggested that if the 6DoF setup errors at each irradiation could be kept within 1.0 mm and 1.0°, there would be little effect on tumor volume regardless of the distance from the isocenter in SI-VMAT.

Association between pre-treatment computed tomography findings and post-treatment persistent decrease in lung perfusion blood volume.

The purpose of this study was to evaluate pre-treatment CT findings in patients with acute pulmonary embolism (PE) and determine the imaging findings associated with residual hypoperfused segments in post-treatment lung perfused blood volume (LPBV). We evaluated 91 patients with acute PE who underwent dual-energy CT before and after treatment. The location of thrombi (proximal or distal) and patency of the pulmonary artery (occlusive or non-occlusive) were recorded using pre-treatment computed tomography pulmonary angiography (CTPA). Residual hypoperfusion was defined as a perfusion-decreased area seen in both the pre- and post-treatment LPBVs. The association of the location of the thrombus and vascular patency of pre-treatment CTPA with residual hypoperfusion on a segmental and patient basis was examined. In the segment-based analysis, the proportion of residual hypoperfusion in the proximal group was significantly higher than that in the peripheral group (33/125 [26.4%] vs. 9/87 [10.3%], P = 0.004). Patient-based analysis also showed that the proportion of residual hypoperfusion in patients with pre-treatment proximal thrombus was significantly higher than those without (16/42 [38.1%] vs. 3/25 (12.0%); P = 0.022). Pre-treatment vascular patency was not significantly associated with residual hypoperfusion (P > 0.05). Therefore, careful follow-up is necessary, especially in patients with proximal thrombi.

Prognostic Value and Pathological Correlation of Peritumoral Radiomics in Surgically Resected Non-Small Cell Lung Cancer.

RATIONALE AND OBJECTIVES: To determine the additional value of peritumoral radiomics in predicting overall survival (OS) in surgically resected non-small cell lung cancer (NSCLC) and its correlation with pathological findings. METHODS: A total of 526 patients with surgically resected NSCLC were included (191 training, 160 internal validation, and 175 external validation cohorts). CT images were used to segment the gross tumor volume (GTV) and peritumoral volume (PTV) within distances of 3, 6, 9 mm from the tumor boundary (PTV3, PTV6, and PTV9), and radiomic features were extracted. Four prognostic models for OS (GTV, GTV + PTV3, GTV + PTV6, and GTV + PTV9) were constructed using the training cohort. The prognostic ability and feature importance were evaluated using the validation cohorts. Pathological findings were compared between the two patient groups (n = 30 for each) having the top 30 and bottom 30 values of the most important peritumoral feature. RESULTS: The GTV+ PTV3 models exhibited the highest predictive ability, which was higher than that of the GTV model in the internal validation cohort (C-index: 0.666 vs. 0.616, P = 0.027) and external validation cohort (C-index: 0.705 vs. 0.656, P = 0.048). The most important feature was GLDM_Dependence_Entropy, extracted from PTV3. High peritumoral GLDM_Dependence_Entropy was associated with a high proportion of invasive histological types, tumor spread through air spaces, and tumor-infiltrating lymphocytes (all P < 0.05). CONCLUSION: The GTV and PTV3 combination demonstrated a higher prognostic ability, compared to GTV alone. Peritumoral radiomic features may be associated with various pathological prognostic factors.

Successful Catheter Ablation for Paroxysmal Supraventricular Tachycardia with Two Alternating Cycle Lengths.

A 62-year-old male was transferred to our hospital complaining of palpitations. His heart rate was 185/min. Electrocardiogram showed a narrow QRS regular tachycardia and the tachycardia changed spontaneously to another narrow QRS tachycardia with two alternating cycle lengths. The arrhythmia was stopped by the administration of adenosine triphosphate. Findings from electrophysiological study suggested that there was an accessory pathway (AP) and dual atrioventricular (AV) nodal pathways. After AP ablation, any other tachyarrythmias were not induced. We supposed that the tachycardia was paroxysmal supraventricular tachycardia involving AP and anterograde conduction alternating between slow and fast AV nodal pathways.

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.

Successful left ventricular lead placement by way of an azygos vein for a patient performing cardiac resynchronization therapy implantation with an occluded left subclavian vein: A case report.

Central venous obstruction following pacemaker implantation is not uncommon and can prove challenging in the case of a system upgrade to a cardiac resynchronization therapy pacemaker (CRT-P). We describe the case of a patient who underwent a successful upgrading procedure of a pacemaker to a CRT-P in the presence of an occluded left subclavian vein and superior vena cava, using collateral veins that drained into right atrium.

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.

Quantitative MR texture analysis for the differentiation of uterine smooth muscle tumors with high signal intensity on T2-weighted imaging.

The purpose of this study was to distinguish leiomyosarcomas/smooth muscle tumors of uncertain malignant potential (STUMP) from leiomyomas with high signal intensity (SI) on T2-weighted imaging (T2WI) using quantitative MR texture analysis combined with patient characteristics and visual assessment. Thirty-one leiomyomas, 2 STUMPs, and 6 leiomyosarcomas showing high SI on T2WI were included. First, we searched for differences in patient characteristics and visual assessment between leiomyomas and leiomyosarcomas/STUMPs. We also compared the MR texture on T2WI and the apparent diffusion coefficient (ADC) to identify differences between leiomyomas and leiomyosarcomas/STUMPs. In the univariate analysis, significant differences between leiomyomas and leiomyosarcomas/STUMPs were observed in age, menopausal status, margin, hemorrhage, long diameter, T2-variance, T2-volume, ADC-variance, ADC-entropy, ADC-uniformity, ADC-90th and 95th percentile values, and ADC-volume (P < .05, respectively). There were significantly more postmenopausal patients with leiomyosarcomas/STUMPs than with leiomyomas, and leiomyosarcomas/STUMPs had more irregular margins, more frequent presence of hemorrhage and exhibited larger tumor diameters, T2-volume, T2-variance, ADC-volume, ADC-variance, ADC-entropy, and higher ADC-90th and 95th percentile values but lower ADC-uniformity. Multivariate analyses revealed that the independent differentiators were menopausal status, hemorrhage and ADC-entropy (P < .05, respectively). The area under the curve obtained by combining the 3 items was 0.980. The best cutoff value for ADC-entropy was 9.625 (sensitivity: 100%, specificity: 58%). The combination of menopausal status, hemorrhage, and ADC-entropy can help accurately distinguish leiomyosarcomas/STUMPs from leiomyomas with high SI on T2WI; however, external validation in a larger population is required because of the small sample size of our study.

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.

Mathematical model combined with microdosimetric kinetic model for tumor volume calculation in stereotactic body radiation therapy.

We proposed a new mathematical model that combines an ordinary differential equation (ODE) and microdosimetric kinetic model (MKM) to predict the tumor-cell lethal effect of Stereotactic body radiation therapy (SBRT) applied to non-small cell lung cancer (NSCLC). The tumor growth volume was calculated by the ODE in the multi-component mathematical model (MCM) for the cell lines NSCLC A549 and NCI-H460 (H460). The prescription doses 48 Gy/4 fr and 54 Gy/3 fr were used in the SBRT, and the effect of the SBRT on tumor cells was evaluated by the MKM. We also evaluated the effects of (1) linear quadratic model (LQM) and the MKM, (2) varying the ratio of active and quiescent tumors for the total tumor volume, and (3) the length of the dose-delivery time per fractionated dose (tinter) on the initial tumor volume. We used the ratio of the tumor volume at 1 day after the end of irradiation to the tumor volume before irradiation to define the radiation effectiveness value (REV). The combination of MKM and MCM significantly reduced REV at 48 Gy/4 fr compared to the combination of LQM and MCM. The ratio of active tumors and the prolonging of tinter affected the decrease in the REV for A549 and H460 cells. We evaluated the tumor volume considering a large fractionated dose and the dose-delivery time by combining the MKM with a mathematical model of tumor growth using an ODE in lung SBRT for NSCLC A549 and H460 cells.

Effectiveness of one-shot dual-energy subtraction chest radiography with flat-panel detector in distinguishing between calcified and non-calcified nodules.

The purpose of this study was to evaluate the added value of the soft tissue image obtained by the one-shot dual-energy subtraction (DES) method using a flat-panel detector compared with the standard image alone in distinguishing calcified from non-calcified nodules on chest radiographs. We evaluated 155 nodules (48 calcified and 107 non-calcified) in 139 patients. Five radiologists (readers 1 - 5) with 26, 14, 8, 6 and 3 years of experience, respectively, evaluated whether the nodules were calcified using chest radiography. CT was used as the gold standard of calcification and non-calcification. Accuracy and area under the receiver operating characteristic curve (AUC) were compared between analyses with and without soft tissue images. The misdiagnosis ratio (false positive plus false negative ratios) when nodules and bones overlapped was also examined. The accuracy of all radiologists increased after adding soft tissue images (readers 1 - 5: 89.7% vs. 92.3% [P = 0.206], 83.2% vs. 87.7% [P = 0.178], 79.4% vs. 92.3% [P < 0.001], 77.4% vs. 87.1% [P = 0.007], and 63.2% vs. 83.2% [P < 0.001], respectively). AUCs for all the readers improved, except for reader 2 (readers 1 - 5: 0.927 vs. 0.937 [P = 0.495], 0.853 vs. 0.834 [P = 0.624], 0.825 vs. 0.878 [P = 0.151], 0.808 vs. 0.896 [P < 0.001], and 0.694 vs. 0.846 [P < 0.001], respectively). The misdiagnosis ratio for nodules that overlapped with the bone decreased after adding soft tissue images in all readers (11.5% vs. 7.6% [P = 0.096], 17.6% vs. 12.2% [P = 0.144], 21.4% vs. 7.6% [P < 0.001], 22.1% vs. 14.5% [P = 0.050] and 35.9% vs. 16.0% [P < 0.001], respectively), particularly that of readers 3 - 5. In conclusion, the soft tissue images obtained using one-shot DES with a flat-panel detector have added value in distinguishing calcified from non-calcified nodules on chest radiographs, especially for less experienced radiologists.

Multicomponent mathematical model for tumor volume calculation with setup error using single-isocenter stereotactic radiotherapy for multiple brain metastases.

We evaluated the tumor residual volumes considering six degrees-of-freedom (6DoF) patient setup errors in stereotactic radiotherapy (SRT) with multicomponent mathematical model using single-isocenter irradiation for brain metastases. Simulated spherical gross tumor volumes (GTVs) with 1.0 (GTV 1), 2.0 (GTV 2), and 3.0 (GTV 3)-cm diameters were used. The distance between the GTV center and isocenter (d) was set at 0-10 cm. The GTV was simultaneously translated within 0-1.0 mm (T) and rotated within 0°-1.0° (R) in the three axis directions using affine transformation. We optimized the tumor growth model parameters using measurements of non-small cell lung cancer cell lines' (A549 and NCI-H460) growth. We calculated the GTV residual volume at the irradiation's end using the physical dose to the GTV when the GTV size, d, and 6DoF setup error varied. The d-values that satisfy tolerance values (10%, 35%, and 50%) of the GTV residual volume rate based on the pre-irradiation GTV volume were determined. The larger the tolerance value set for both cell lines, the longer the distance to satisfy the tolerance value. In GTV residual volume evaluations based on the multicomponent mathematical model on SRT with single-isocenter irradiation, the smaller the GTV size and the larger the distance and 6DoF setup error, the shorter the distance that satisfies the tolerance value might need to be.

Endoderm-derived islet1-expressing cells differentiate into endothelial cells to function as the vascular HSPC niche in zebrafish.

Endothelial cells (ECs) line blood vessels and serve as a niche for hematopoietic stem and progenitor cells (HSPCs). Recent data point to tissue-specific EC specialization as well as heterogeneity; however, it remains unclear how ECs acquire these properties. Here, by combining live-imaging-based lineage-tracing and single-cell transcriptomics in zebrafish embryos, we identify an unexpected origin for part of the vascular HSPC niche. We find that islet1 (isl1)-expressing cells are the progenitors of the venous ECs that constitute the majority of the HSPC niche. These isl1-expressing cells surprisingly originate from the endoderm and differentiate into ECs in a process dependent on Bmp-Smad signaling and subsequently requiring npas4l (cloche) function. Single-cell RNA sequencing analyses show that isl1-derived ECs express a set of genes that reflect their distinct origin. This study demonstrates that endothelial specialization in the HSPC niche is determined at least in part by the origin of the ECs.

A novel cell-based assay for the high-throughput screening of epithelial-mesenchymal transition inhibitors: Identification of approved and investigational drugs that inhibit epithelial-mesenchymal transition.

OBJECTIVES: Lung cancer with distant metastases is associated with a very poor prognosis, and epithelial-mesenchymal transition (EMT) contributes to cancer metastasis. Therefore, elucidation and inhibition of EMT signaling in lung cancer may be a new therapeutic strategy for improving the prognosis of patients. We constructed a high-throughput screening system for EMT inhibitors. Using this system, we aimed to identify compounds that indeed inhibit EMT. MATERIALS AND METHODS: We generated a luciferase reporter cell line using A549 human lung cancer cells and E-cadherin or vimentin as EMT markers. EMT was induced by transforming growth factor ß1 (TGF-ß1), and candidate EMT inhibitors were screened from a library of 2,350 compounds. The selected compounds were further tested using secondary assays to verify the inhibition of EMT and invasive capacity of cells. RESULTS: Values obtained by the assay were adjusted for the number of viable cells and scored by determining the difference between mean values of the positive and negative control groups. Four compounds were identified as novel candidate drugs. Among those, one (avagacestat) and two compounds (GDC-0879 and levothyroxine) improved the expression of E-cadherin and vimentin, respectively, in epithelial cells. GDC-0879 and levothyroxine also significantly inhibited the invasive capacity of cells. CONCLUSION: We systematically screened approved, investigational, and druggable compounds with inhibitory effects using a reporter assay, and identified candidate drugs for EMT inhibition.

Clinical outcomes of hybrid closed wedge high tibial osteotomy for advanced osteoarthritis of the knee compared with total knee arthroplasty.

PURPOSE: To evaluate clinical outcomes between hybrid closed wedge high tibial osteotomy (HCWHTO) and total knee arthroplasty (TKA) for advanced medial compartmental osteoarthritis of the knee (advanced knee OA). METHODS: In more than grade 3 OA based on the Kellgren-Lawrence classification, when patients' age was less than 60 years or activity level was more than level 5 based on the UCLA activity score, 22 knees (18 patients) underwent HCWHTO. The other 22 knees (18 patients) that underwent TKA were evaluated retrospectively. Muscle strength was evaluated preoperatively and at 1 year postoperatively. The visual analogue scale (VAS) and Japanese version of the Knee injury and Osteoarthritis Outcome Score (J-KOOS) were used to evaluate clinical outcomes preoperatively and at a mean 66-months follow-up. RESULTS: All postoperative muscle strength measures improved to preoperative equivalent levels in the HCWHTO group; they were significantly higher in the HCWHTO group than in the TKA group (p < .05). The VAS score and total J-KOOS significantly improved in both groups (HCWHTO, p = .001; TKA, p = .040); there were no significant differences in the scores between the groups at the final follow-up. Hybrid closed wedge HTO significantly improved the activities of daily living and sport/recreation scores, whereas TKA did not at the final follow-up. CONCLUSIONS: In advanced knee OA, HCWHTO led to improved muscle strength, and its midterm clinical outcomes were equivalent to those of TKA. To postpone or even to avoid TKA, HCWHTO is considered an appropriate treatment for young and high-activity patients with advanced knee OA. LEVEL OF EVIDENCE: Therapeutic Level III.

An extremely rare case of anterior mediastinal leiomyosarcoma: a case report.

We herein report an extremely rare case of leiomyosarcoma found in the anterior mediastinum. A 79-year-old man presented to our hospital with an anterior mediastinal mass incidentally found by chest computed tomography (CT) scan. Percutaneous needle biopsy revealed the presence of an undifferentiated sarcoma. Transsternal resection of the tumor with adjacent left mediastinal pleura was performed, and pathological analysis revealed a leiomyosarcoma, which was 11 cm in diameter, with bare margins. He was followed up on an outpatient basis with no adjuvant therapy. Although mediastinal lymph node recurrence was suspected on chest CT scan 18 months after surgery, the patient remained asymptomatic and rejected any additional antitumor treatments. He died of respiratory failure after incidental traumatic spinal injury about 30 months after tumor resection.

Role of intratumoral and peritumoral CT radiomics for the prediction of EGFR gene mutation in primary lung cancer.

OBJECTIVES: To determine the added value of combining intratumoral and peritumoral CT radiomics for the prediction of epidermal growth factor receptor (EGFR) gene mutations in primary lung cancer (PLC). METHODS: This study included 478 patients with PLC (348 adenocarcinomas and 130 other histological types) who underwent surgical resection and EGFR gene testing. Two radiologists performed segmentation of tumors and peritumoral regions using precontrast high-resolution CT images, and 398 radiomic features (212 intra- and 186 peritumoral features) were extracted. The peritumoral region was defined as the lung parenchyma within a distance of 3 mm from the tumor border. Model performance was estimated using Random Forest, a machine-learning algorithm. RESULTS: EGFR mutations were found in 162 tumors; 161 adenocarcinomas, and one pleomorphic carcinoma. After exclusion of poorly reproducible and redundant features, 32 radiomic features remained (14 intra- and 18 peritumoral features) and were included in the model building. For predicting EGFR mutations, combining intra- and peritumoral radiomics significantly improved the performance compared to intratumoral radiomics alone (AUC [area under the receiver operating characteristic curve], 0.774 vs 0.730; p < 0.001). Even in adenocarcinomas only, adding peritumoral radiomics significantly increased performance (AUC, 0.687 vs 0.630; p < 0.001). The predictive performance using radiomics and clinical features was significantly higher than that of clinical features alone (AUC, 0.826 vs 0.777; p = 0.005). CONCLUSIONS: Combining intra- and peritumoral radiomics improves the predictive accuracy of EGFR mutations and could be used to aid in decision-making of whether to perform biopsy for gene tests. ADVANCES IN KNOWLEDGE: Adding peritumoral to intratumoral radiomics yields greater accuracy than intratumoral radiomics alone in predicting EGFR mutations and may serve as a non-invasive method of predicting of the gene status in PLC.

The impact of target positioning error and tumor size on radiobiological parameters in robotic stereotactic radiosurgery for metastatic brain tumors.

This study aimed to evaluate the effect of target positioning error (TPE) on radiobiological parameters, such as tumor control probability (TCP) and normal tissue complication probability (NTCP), in stereotactic radiosurgery (SRS) for metastatic brain tumors of different sizes using CyberKnife. The reference SRS plans were created using the circular cone of the CyberKnife for each spherical gross tumor volume (GTV) with diameters (φ) of 5, 7.5, 10, 15, and 20 mm, contoured on computed tomography images of the head phantom. Subsequently, plans involving TPE were created by shifting the beam center by 0.1-2.0 mm in three dimensions relative to the reference plans using the same beam arrangements. Conformity index (CI), generalized equivalent uniform dose (gEUD)-based TCP, and NTCP of estimated brain necrosis were evaluated for each plan. When the gEUD parameter "a" was set to - 10, the CI and TCP for the reference plan at the φ5-mm GTV were 0.90 and 80.8%, respectively. The corresponding values for plans involving TPE of 0.5-mm, 1.0-mm, and 2.0-mm were 0.62 and 77.4%, 0.40 and 62.9%, and 0.12 and 7.2%, respectively. In contrast, the NTCP for all GTVs were the same. The TCP for the plans involving a TPE of 2-mm was 7.2% and 68.8% at the φ5-mm and φ20-mm GTV, respectively. The TPEs corresponding to a TCP reduction rate of 3% at the φ5-mm and φ20-mm GTV were 0.41 and 0.99 mm, respectively. TPE had a significant effect on TCP in SRS for metastatic brain tumors using CyberKnife, particularly for small GTVs.

Embedded Human Periodontal Ligament Stem Cells Spheroids Enhance Cementogenic Differentiation via Plasminogen Activator Inhibitor 1.

Spheroids reproduce the tissue structure that is found in vivo more accurately than classic two-dimensional (2D) monolayer cultures. We cultured human periodontal ligament stem cells (HPLSCs) as spheroids that were embedded in collagen gel to examine whether their cementogenic differentiation could be enhanced by treatment with recombinant human plasminogen activator inhibitor-1 (rhPAI-1). The upregulated expression of cementum protein 1 (CEMP1) and cementum attachment protein (CAP), established cementoblast markers, was observed in the 2D monolayer HPLSCs that were treated with rhPAI-1 for 3 weeks compared with that in the control and osteogenic-induction medium groups. In the embedded HPLSC spheroids, rhPAI-1 treatment induced interplay between the spheroids and collagenous extracellular matrix (ECM), indicating that disaggregated HPLSCs migrated and spread into the surrounding ECM 72 h after three-dimensional (3D) culture. Western blot and immunocytochemistry analyses showed that the CEMP1 expression levels were significantly upregulated in the rhPAI-1-treated embedded HPLSC spheroids compared with all the 2D monolayer HPLSCs groups and the 3D spheroid groups. Therefore, 3D collagen-embedded spheroid culture in combination with rhPAI-1 treatment may be useful for facilitating cementogenic differentiation of HPLSCs.

Femoral morphology affects postoperative alignment of the lower extremities in hybrid closed-wedge high tibial osteotomy.

INTRODUCTION: This study aimed to determine correction error predictors of lower extremitiy alignment after hybrid closed-wedge high tibial osteotomy (HCWHTO). MATERIALS AND METHODS: From 2011 to 2015, 102 knees in 75 patients with medial compartment knee osteoarthritis of the knee and varus knee deformities who underwent HCWHTO were evaluated in this retrospective study with a minimum 2-year follow-up. Preoperative radiological parameters including weight-bearing line ratio (WBL ratio), mechanical leg axis angle, mechanical lateral distal femoral angle (mLDFA), medial proximal tibial angle (MPTA), joint line convergence angle (JLCA), and JLCA under varus or valgus stress were measured. The knees were divided into the following three groups based on the WBL ratio on average 54 months after procedure: acceptable (WBL crossing the tibial plateau between 50 and 70%), under-correction (< 50%), and overcorrection (> 70%). A multiple regression analysis was performed to evaluate predictors that could influence postoperative WBL ratio and cut-off values of predictive preoperative factors was analysed. RESULTS: Significant differences in pre- and postoperative WBL ratios and mechanical leg axis angles were found. Preoperative mLDFA in the under-correction group (89.4° ± 2.1°) was significantly higher than that in the overcorrection group (87.4° ± 2.2°) (p = 0.015), while other preoperative parameters revealed no significant differences. The postoperative MPTA in the under-correction group (92.1° ± 3.7°) was significantly lower than that in the other two groups (p = 0.005 and p = 0.0001, respectively), while there was no significant change between the acceptable (94.6° ± 3.4°) and the overcorrection (96.7° ± 3.2°) groups. Multiple regression analysis revealed that mLDFA (ß = - 0.316; p = 0.010) had a significant impact on postoperative WBLR. The cut-off value for under-correction of mLDFA was 89.5°and sensitivity and specificity were 53.6 and 71.6%, respectively (p = 0.014). CONCLUSIONS: Preoperative mLDFA is significantly associated with postoperative alignment in HCWHTO. While postoperative MPTA is important, disregarding the preoperative mLDFA may bears a high risk of malcorrection. Varus alignment of the knee with larger mLDFA may be an indication for not only HCWHTO, but also for distal femoral osteotomy.