Multiple roles of baicalin and baicalein in the regulation of colorectal cancer.

The prevalence of colorectal cancer is increasing worldwide, and despite advances in treatment, colorectal cancer (CRC) remains in the top three for mortality due to several issues, including drug resistance and low efficiency. There is increasing evidence that baicalin and baicalein, novel small molecule inhibitor extracts of the Chinese herb Scutellaria baicalensis, have better anti-colorectal cancer effects and are less likely to induce drug resistance in cancer cells. The present review article explains the anti-proliferative properties of baicalin and baicalein in the context of against CRC. Additionally, it explores the underlying mechanisms by which these compounds modulate diverse signaling pathways associated with apoptosis, cell proliferation, tumor angiogenesis, invasion, metastasis, and tumor microenvironment. Moreover, this review article highlights the inhibitory effect of colorectal inflammatory-cancer transformation and the near-term therapeutic strategy of using them as adjuvant agents in chemotherapy.

Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy.

MRI-guided radiotherapy systems enable beam gating by tracking the target on planar, two-dimensional cine images acquired during treatment. This study aims to evaluate how deep-learning (DL) models for target tracking that are trained on data from one fraction can be translated to subsequent fractions. Cine images were acquired for six patients treated on an MRI-guided radiotherapy platform (MRIdian, Viewray Inc.) with an onboard 0.35 T MRI scanner. Three DL models (U-net, attention U-net and nested U-net) for target tracking were trained using two training strategies: (1) uniform training using data obtained only from the first fraction with testing performed on data from subsequent fractions and (2) adaptive training in which training was updated each fraction by adding 20 samples from the current fraction with testing performed on the remaining images from that fraction. Tracking performance was compared between algorithms, models and training strategies by evaluating the Dice similarity coefficient (DSC) and 95% Hausdorff Distance (HD95) between automatically generated and manually specified contours. The mean DSC for all six patients in comparing manual contours and contours generated by the onboard algorithm (OBT) were 0.68 ± 0.16. Compared to OBT, the DSC values improved 17.0 - 19.3% for the three DL models with uniform training, and 24.7 - 25.7% for the models based on adaptive training. The HD95 values improved 50.6 - 54.5% for the models based on adaptive training. DL-based techniques achieved better tracking performance than the onboard, registration-based tracking approach. DL-based tracking performance improved when implementing an adaptive strategy that augments training data fraction-by-fraction.

Shared decision-making in the treatment of adolescents diagnosed with depression: A cross-sectional survey of mental health professionals in China.

WHAT IS ALREADY KNOWN?: SDM improves clinical outcomes by increasing attendance and treatment adherence in adolescents diagnosed with depression. SDM could reduce treatment disagreements and enhance consumers' and their families' satisfaction with mental healthcare services. Healthcare professionals are a critical part of SDM. However, MHPs' practices of SDM in the daily management of adolescents diagnosed with depression need to be clarified. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE?: From the viewpoints of MHPs, SDM was not extensively applied in the daily management of adolescents diagnosed with depression. MHPs who trust their consumers and have received training related to SDM are more likely to practice SDM in the daily management of adolescents diagnosed with depression. The positive preferences for providing information and family involvement in treatment decision-making are facilitators; working in closed inpatient mental health wards and open inpatient mental health wards are hindering factors for MHPs' practices of SDM. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: MHPs should encourage information sharing with consumers and their family members to help them participate in treatment decision-making actively. A trusting and friendly therapeutic relationship with consumers should be maintained in the daily management of adolescents diagnosed with depression. SDM-related training should be encouraged for MHPs to promote widespread SDM. ABSTRACT: INTRODUCTION: Shared decision-making (SDM) is an ideal model for a therapeutic relationship that can improve health outcomes. Healthcare professionals are a critical part of SDM, and they play an important role in the practices of SDM in the clinical setting. Evidence suggests that adolescents diagnosed with depression can benefit substantially from SDM. However, mental health professionals' (MHPs) practices of SDM for adolescents diagnosed with depression in China are not well-documented. AIM: This study aimed to investigate the practices of SDM for adolescents diagnosed with depression from the viewpoints of MHPs in China. METHOD: In this cross-sectional study, we recruited a total of 581 MHPs by convenience sampling. The Shared Decision-Making Questionnaire-Physician Version (SDM-Q-Doc) was used to evaluate the MHPs' practices of SDM for adolescents diagnosed with depression. RESULTS: The mean SDM-Q-Doc was 80.47 (±16.31). Within the six specific decision-making situations, most MHPs selected non-SDM (52.7%-71.6%). Substantial numbers of respondents believed that MHPs made the final decision, especially with regard to the development (37%) and adjustment of medication regimens (42%). The practice of SDM was predicted by MHPs' preference for providing information, their trust in consumers, preference for family involvement in treatment decision-making, working in an outpatient clinic and receiving SDM training (F = 23.582; p = .000; R2 = .198; adjusted R2 = .189). DISCUSSION: Although the MHPs' self-rated score of SDM-Q-Doc was high, SDM was not extensively applied in the daily management of adolescents diagnosed with depression. Thus, SDM needs to be further promoted by enhancing SDM-related training for MHPs, thereby actively promoting the involvement of families, facilitating the information sharing for consumers and families, and building an active, trusting consumer-practitioner relationship. IMPLICATIONS FOR PRACTICE: MHPs should prioritise information sharing with consumers and families, as well as build trusting and friendly therapeutic relationships. Family involvement in treatment decisions should be encouraged when adolescents diagnosed with depression are in need. Actively participating in training related to SDM is also important. Future high-quality evidence is still needed to explore the facilitators and barriers to SDM practices from a tripartite perspective of MHPs, adolescents diagnosed with depression and their families.

Toward real-time automatic treatment planning (RTTP) with a one-step 3D fluence map prediction method and (nonorthogonal) convolution technique.

PURPOSE: To establish and evaluate a (quasi) real-time automated treatment planning (RTTP) strategy utilizing a one-step full 3D fluence map prediction model based on a nonorthogonal convolution operation for rectal cancer radiotherapy. METHODS: The RTTP approach directly extracts 3D projections from volumetric CT and anatomical data according to the beam incident direction. A 3D deep learning model with a nonorthogonal convolution operation was established that takes projections in cone beam space as input, extracts the features along and around the ray-trace path, and outputs a predicted fluence map (PFM) for each beam. The PFM is then converted to the MLC sequence with deliverable MUs to generate the final treatment plan. A total of 314 rectal adenocarcinoma patients with 2198 projection data samples were used in model training and validation. An extra 20 patients were used to test the feasibility of the RTTP method by comparing the plan quality, efficiency, deliverability performance, and physician blinded review results with the manual plans. RESULTS: Overall, the RTTP plans met the clinical dose criteria for target coverage, conformity, homogeneity, and organ-at-risk dose sparing. Compared to manual plans, the RTTP plans showed increases in PTV D1% by only 2.33% (p < 0.001) and a decrease in PTV D99% by 0.45% (p < 0.05). The RTTP plans showed a dose increase in the bladder, with a V50 of 14.01 ± 11.75% vs. 10.74 ± 8.51%, respectively, and no significant increases in the femoral head with the mean dose. The planning efficiency was improved in RTTP planning, with 39 s vs. 944 s in fluence map generation; the deliverability performance was saved by 1.91% (p < 0.001) in total MU. According to the blinded plan review by our physician, 55% of RTTP plans can be directly used in clinical radiotherapy treatment. CONCLUSION: The quasi RTTP method improves the planning efficiency and deliverability performance while maintaining a plan quality close to that of the optimized manual plans in rectal radiotherapy.

[Dosimetric Impact of Titanium Alloy Implant in Spinal IMRT Plan].

The purpose of this study is to establish and apply a correction method for titanium alloy implant in spinal IMRT plan, a corrected CT-density table was revised from normal CT-density table to include the density of titanium alloy implant. Dose distribution after and before correction were calculated and compared to evaluate the dose deviation. Plans were also copied to a spinal cancer simulation phantom. A titanium alloy fixation system for spine was implanted in this phantom. Plans were recalculated and compared with the measurement result. The result of this study shows that the max dose of spinal cord showed significant difference after correction, and the deviation between calculation results and measurement results was reduced after correction. The method for expanding the range CT-density table, which means that the density of titanium alloy was included, can reduce the error in calculation.

Prevalence and Correlates of Weight Stigma among Postpartum Women in China.

Weight stigma is linked to a variety of psychological and health problems. In the postpartum period, women may be more likely to experience weight-based discrimination because of their changing social roles, weight, and the new functions their bodies fulfill. However, few studies have explored the issue of postpartum women's weight stigma. Thus, to investigate the prevalence and correlates of weight stigma for postpartum women in China, we conducted a cross-sectional study of 507 postpartum women. Results showed that almost one quarter (21.1%) of postpartum women claimed to have experienced perceived weight stigma (PWS). Two thirds (66.1%) scored at the mean and 14.8% at the highest levels of weight bias internalization (WBI). During the postnatal period, the conditions of those most likely to report experiences of weight-based discrimination included low income [b = -0.203, p = 0.004], occupation as a worker [b = 0.921, p = 0.017] or farmer [b = 0.826, p = 0.033], stress [b = 0.044, p = 0.035], depression [b = 0.057, p = 0.021], and higher WBIS [b = 0.018, p = 0.002]. In addition, postpartum women who lived alone [b = 7.511, p = 0.048], were overweight or obese [b = 5.443, p = 0.000], and had higher PWS [b = 0.897, p = 0.004] and anxiety symptoms [b = 0.219, p = 0.011] had higher levels of internalized weight stigma. Findings from this study provide a foundation to better understand characteristics of postpartum women in China who are at risk for weight stigma.

Combined Network Pharmacology and Cytology Experiments to Identify Potential Anti-Breast Cancer Targets and Mechanisms of Delphinidin.

Delphinidin is a type of anthocyanin monomer with antioxidant, anti-inflammatory, and anti-tumor effects. However, the biological mechanisms underlying its anti-breast cancer activity have not been thoroughly studied. We further studied the effect of delphinidin on breast cancer cells through comprehensive network pharmacology, cellular and molecular experiments. We acquired the know therapeutic targets of delphinidin and obtained differentially expressed genes (DEGs) of breast cancer using RTCGA. We used topological analysis to screen out the 106 core targets of delphinium anti-breast cancer and performed functional analysis. These genes were mainly enriched in the pathways in cancer, Progesterone-mediated oocyte maturation and cell cycle. Then, by taking the intersection of the three analyzed data sets, important core targets (EGFR, TOP2A and PTGS2) were obtained and molecular-docking was performed to validate the result. Additionally, In Vitro experiments, MCF-7 and BT-474 cell proliferation was inhibited in a dose-dependent manner by delphinidin and the expressions of EGFR, TOP2A and PTGS were reduced. Moreover, delphinidin influenced cell cycle, the expressions of cdk1 and cyclin B1 were reduced. Furthermore, delphinidin induced apoptosis by activating the MAPK-Signaling pathway. Collectively, our findings suggested that delphinidin may offer effective approaches in breast cancer prevention and therapy.Supplemental data for this article is available online at http://dx.doi.org/10.1080/01635581.2021.2012582.

Delphinidin induces cell cycle arrest and apoptosis in HER-2 positive breast cancer cell lines by regulating the NF-κB and MAPK signaling pathways.

Delphinidin is an anthocyanidin monomer, commonly found in vegetables and fruits, and has demonstrated antitumor effects in the HER-2-positive MDA-MB-453 breast cancer cell line, with low cytotoxicity on normal breast cells. However, the direct functional mechanisms underlying the effect of delphinidin on HER-2-positive breast cancer cells has not been fully characterized. In the present study, it was found that delphinidin could induce G2/M phase cell cycle arrest by inhibiting the protein expression level of cyclin B1 and Cdk1 in HER-2-positive breast cancer cell lines. In addition, delphinidin promoted the mitochondrial apoptosis pathway by inhibiting the ERK and NF-κB signaling pathway and activating the JNK signaling pathway. Therefore, delphinidin markedly suppressed the viability of the HER-2-positive breast cancer cell lines by modulating the cell cycle and inducing apoptosis. Overall, the findings from the present study demonstrated that delphinidin treatment could induce the mitochondrial apoptosis pathway in human HER-2-positive breast cancer cell lines, providing an experimental basis for the prevention and treatment of HER-2-positive breast cancer by flavonoids.

An atlas-guided automatic planning approach for rectal cancer intensity-modulated radiotherapy.

We try to develop an atlas-guided automatic planning (AGAP) approach and evaluate its feasibility and performance in rectal cancer intensity-modulated radiotherapy. The developed AGAP approach consisted of four independent modules: patient atlas, similar patient retrieval, beam morphing (BM), and plan fine-tuning (PFT) modules. The atlas was setup using anatomy and plan data from Pinnacle auto-planning (P-auto) plans. Given a new patient, the retrieval function searched the top similar patient by a generic Fourier descriptor algorithm and retrieved its plan information. The BM function generated an initial plan for the new patient by morphing the beam aperture from the top similar patient plan. The beam aperture and calculated dose of the initial plan were used to guide the new plan optimization in the PFT function. The AGAP approach was tested on 96 patients by the leave-one-out validation and plan quality was compared with the P-auto plans. The AGAP and P-auto plans had no statistical difference for target coverage and dose homogeneity in terms ofV100%(p = 0.76) and homogeneity index (p = 0.073), respectively. The CI index showed they had a statistically significant difference. But the ΔCI was both 0.02 compared to the perfect CI index of 1. The AGAP approach reduced the bladder mean dose by 152.1 cGy (p < 0.05) andV50by 0.9% (p < 0.05), and slightly increased the left and right femoral head mean dose by 70.1 cGy (p < 0.05) and 69.7 cGy (p < 0.05), respectively. This work developed an efficient and automatic approach that could fully automate the IMRT planning process in rectal cancer radiotherapy. It reduced the plan quality dependence on the planner experience and maintained the comparable plan quality with P-auto plans.

MV CBCT-Based Synthetic CT Generation Using a Deep Learning Method for Rectal Cancer Adaptive Radiotherapy.

Due to image quality limitations, online Megavoltage cone beam CT (MV CBCT), which represents real online patient anatomy, cannot be used to perform adaptive radiotherapy (ART). In this study, we used a deep learning method, the cycle-consistent adversarial network (CycleGAN), to improve the MV CBCT image quality and Hounsfield-unit (HU) accuracy for rectal cancer patients to make the generated synthetic CT (sCT) eligible for ART. Forty rectal cancer patients treated with the intensity modulated radiotherapy (IMRT) were involved in this study. The CT and MV CBCT images of 30 patients were used for model training, and the images of the remaining 10 patients were used for evaluation. Image quality, autosegmentation capability and dose calculation capability using the autoplanning technique of the generated sCT were evaluated. The mean absolute error (MAE) was reduced from 135.84 ± 41.59 HU for the CT and CBCT comparison to 52.99 ± 12.09 HU for the CT and sCT comparison. The structural similarity (SSIM) index for the CT and sCT comparison was 0.81 ± 0.03, which is a great improvement over the 0.44 ± 0.07 for the CT and CBCT comparison. The autosegmentation model performance on sCT for femoral heads was accurate and required almost no manual modification. For the CTV and bladder, although modification was needed for autocontouring, the Dice similarity coefficient (DSC) indices were high, at 0.93 and 0.94 for the CTV and bladder, respectively. For dose evaluation, the sCT-based plan has a much smaller dose deviation from the CT-based plan than that of the CBCT-based plan. The proposed method solved a key problem for rectal cancer ART realization based on MV CBCT. The generated sCT enables ART based on the actual patient anatomy at the treatment position.

The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer.

PURPOSE: To investigate the dosimetric impact of deep learning-based auto-segmentation of organs at risk (OARs) on nasopharyngeal and rectal cancer. METHODS AND MATERIALS: Twenty patients, including ten nasopharyngeal carcinoma (NPC) patients and ten rectal cancer patients, who received radiotherapy in our department were enrolled in this study. Two deep learning-based auto-segmentation systems, including an in-house developed system (FD) and a commercial product (UIH), were used to generate two auto-segmented OARs sets (OAR_FD and OAR_UIH). Treatment plans based on auto-segmented OARs and following our clinical requirements were generated for each patient on each OARs sets (Plan_FD and Plan_UIH). Geometric metrics (Hausdorff distance (HD), mean distance to agreement (MDA), the Dice similarity coefficient (DICE) and the Jaccard index) were calculated for geometric evaluation. The dosimetric impact was evaluated by comparing Plan_FD and Plan_UIH to original clinically approved plans (Plan_Manual) with dose-volume metrics and 3D gamma analysis. Spearman's correlation analysis was performed to investigate the correlation between dosimetric difference and geometric metrics. RESULTS: FD and UIH could provide similar geometric performance in parotids, temporal lobes, lens, and eyes (DICE, p > 0.05). OAR_FD had better geometric performance in the optic nerves, oral cavity, larynx, and femoral heads (DICE, p < 0.05). OAR_UIH had better geometric performance in the bladder (DICE, p < 0.05). In dosimetric analysis, both Plan_FD and Plan_UIH had nonsignificant dosimetric differences compared to Plan_Manual for most PTV and OARs dose-volume metrics. The only significant dosimetric difference was the max dose of the left temporal lobe for Plan_FD vs. Plan_Manual (p = 0.05). Only one significant correlation was found between the mean dose of the femoral head and its HD index (R = 0.4, p = 0.01), there is no OARs showed strong correlation between its dosimetric difference and all of four geometric metrics. CONCLUSIONS: Deep learning-based OARs auto-segmentation for NPC and rectal cancer has a nonsignificant impact on most PTV and OARs dose-volume metrics. Correlations between the auto-segmentation geometric metric and dosimetric difference were not observed for most OARs.

Intracranial Stereotactic Radiation Therapy With a Jawless Ring Gantry Linear Accelerator Equipped With New Dual Layer Multileaf Collimator.

PURPOSE: To test the feasibility of a simplified, robust, workflow for intracranial stereotactic radiation therapy (SRT) using a ring gantry linear accelerator (RGLA) equipped with a dual-layer stacked, staggered, and interdigitating multileaf collimator. MATERIALS AND METHODS: Twenty recent clinical SRT cases treated using a radiosurgery c-arm linear accelerator were anonymized. From these data sets, a new planning workflow was developed and used to replan these cases, which then were compared to their clinical counterparts. Population-based dose-volume histograms were analyzed for target coverage and sparing of healthy brain. All plans underwent plan review and quality assurance and were delivered on an end-to-end verification phantom using image guidance to simulate treatment. RESULTS: The RGLA plans were able to meet departmental standards for target coverage and organ-at-risk sparing and showed plan quality similar to the clinical plans. RGLA plans showed increases in the 50% isodose in the axial plane but decreases in the sagittal and coronal planes. There were no statistically significant differences in the homogeneity index or number of monitor units between the 2 systems. There were statistically significant increases in conformity and gradient indices, with median values of 1.09 versus 1.11 and 2.82 versus 3.13, respectively, for the c-arm versus RGLA plans. These differences were not believed to be clinically significant because they met clinical goals. The population-based dose-volume histograms showed target coverage and organ-at-risk sparing similar to that of the clinical plans. All plans were able to meet the departmental quality assurance requirements and were delivered under image guidance on an end-to-end phantom with measurements agreeing within 3% of the expected value. RGLA plans showed a median reduction in delivery time of ≈50%. CONCLUSIONS: This work describes a simplified and efficient workflow that could reduce treatment times and expand access to SRT to centers using an RGLA.

Implementation of the structural SIMilarity (SSIM) index as a quantitative evaluation tool for dose distribution error detection.

PURPOSE: To apply an imaging metric of the structural SIMilarity (SSIM) index to the radiotherapy dose verification field and evaluate its capability to reveal the different types of errors between two dose distributions. METHOD: The SSIM index consists of three sub-indices: luminance, contrast, and structure. Given two images, luminance analysis compares the local mean result, contrast analysis compares the local standard deviation, and the structure index represents the local Pearson correlation. Three test error patterns (absolute dose error, dose gradient error, and dose structure error) were designed to characterize the response of SSIM and its sub-indices and establish the correlation between the indices and different dose error types. After establishing the correlation, four radiotherapy plans (one MLC picket-fence test plan, one brain stereotactic radiotherapy plan, and two head-and-neck plans) were tested by computing each index and compared with the gamma analysis results to determine their similarities and differences. RESULTS: Among the three test error patterns, the luminance index decreased from 1 to 0.1 when the absolute dose agreement fell from 100% to 5%, the contrast index decreased from 1 to 0.36 when the dose gradient agreement fell from 100% to 10%, and the structure index decreased from 1 to 0.23 when the periodical dose pattern shifted (leading to a lower correlation). Thus, the luminance, contrast and structure index can detect the absolute dose error, gradient discrepancy, and dose structure error, respectively. For the four clinical cases, the sub-indices can reveal the type of error when gamma analysis only provided limited information. CONCLUSIONS: The correlation between the subcomponents of the SSIM index and the error types of the dose distribution were established. The SSIM index provides additional error information compared to that provided by gamma analysis.

Long-term Inter-protocol kV CBCT image quality assessment for a ring-gantry linac via automated QA approach.

We develop a fully automated QA process to compare the image quality of all kV CBCT protocols on a Halcyon linac with ring gantry design, and evaluate image quality stability over a 10-month period. A total of 19 imaging scan and reconstruction protocols were characterized with measurement on a newly released QUART phantom. A set of image analysis algorithms were developed and integrated into an automated analysis suite to derive key image quality metrics, including HU value accuracy on density inserts, HU uniformity using the background plate, high contrast resolution with the modulation transfer function (MTF) from the edge profiles, low contrast resolution using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), slice thickness with the air gap modules, and geometric accuracy with the diameter of the phantom. Image quality data over 10 months was tracked and analyzed to evaluate the stability of the Halcyon kV imaging system. The HU accuracy over all 19 protocols is within tolerance (±50HU). The maximum uniformity deviation is 12.2 HU. The SNR and CNR, depending on the protocol selected, range from 18.5-911.9 and 1.9-102.8, respectively. A much-improved SNR and CNR were observed for iterative reconstruction (iCBCT) modes and protocols designed for large subjects over low dose and fast scanning modes. The Head and Image Gently protocols have the greatest high contrast resolution with MTF10% over 1 lp/mm and MTF50% over 0.6 lp/mm. The iCBCT mode slightly improved the MTF10% and MTF50% compared to the Feldkamp-Davis-Kress approach. The slice thickness (maximum error of 0.31 mm) and geometry metrics (maximum error of 0.7 mm) are all within tolerance (±0.5 mm for slice thickness and ±1 mm for geometry metrics). The long-term study over 10-month showed no significant drift for all key image quality metrics, which indicated the kV CBCT image quality is stable over time.

An Artificial Intelligence-Based Full-Process Solution for Radiotherapy: A Proof of Concept Study on Rectal Cancer.

BACKGROUND AND PURPOSE: To develop an artificial intelligence-based full-process solution for rectal cancer radiotherapy. MATERIALS AND METHODS: A full-process solution that integrates autosegmentation and automatic treatment planning was developed under a single deep-learning framework. A convolutional neural network (CNN) was used to generate segmentations of the target and the organs at risk (OAR) as well as dose distribution. A script in Pinnacle that simulates the treatment planning process was used to execute plan optimization. A total of 172 rectal cancer patients were used for model training, and 18 patients were used for model validation. Another 40 rectal cancer patients were used for an end-to-end evaluation for both autosegmentation and treatment planning. The PTV and OAR segmentation was compared with manual segmentation. The planning results was evaluated by both objective and subjective assessment. RESULTS: The total time for full-process planning without contour modification was 7 min, and an additional 15 min may require for contour modification and re-optimization. The PTV DICE similarity coefficient was greater than 0.85 for all 40 patients in the evaluation dataset while the DICE indices of the OARs also indicated good performance. There were no significant differences between the auto plans and manual plans. The physician accepted 80% of the auto plans without any further operation. CONCLUSION: We developed a deep learning-based automatic solution for rectal cancer treatment that can improve the efficiency of treatment planning.

High-throughput analysis of the effects of different fish culture methods on antibiotic resistance gene abundances in a lake.

Freshwater lakes are important reservoirs for antibiotic resistance genes (ARGs). In this study, we determined the ARG profiles in water samples from Ying Lake, China, using high-throughput quantitative PCR. The high prevalence of ARGs suggested significant pollution with ARGs in the study area, where the ARG diversity and abundance were greater in an area with box-type fish farming than an area with fenced fish farming. Network analysis indicated the widespread co-occurrence of ARGs and mobile genetic elements. cphA-01, blalMP02, and blaCMY202 were identified as adequate indicator genes for estimating the total ARG abundances. Redundancy analysis indicated that changes in the microbial communities caused by variations in the physicochemical parameters with different fish culture methods mainly determined the ARGs in the lake system. Thus, analyzing the factors that affect ARGs provided novel insights into the mechanisms responsible for the maintenance and propagation of ARGs in a lake.

Are simple IMRT beams more robust against MLC error? Exploring the impact of MLC errors on planar quality assurance and plan quality for different complexity beams.

This study investigated the impact of beam complexities on planar quality assur-ance and plan quality robustness by introducing MLC errors in intensity-modulate radiation therapy. Forty patients' planar quality assurance (QA) plans were enrolled in this study, including 20 dynamic MLC (DMLC) IMRT plans and 20 static MLC (SMLC) IMRT plans. The total beam numbers were 150 and 160 for DMLC and SMLC, respectively. Six different magnitudes of MLC errors were introduced to these beams. Gamma pass rates were calculated by comparing error-free fluence and error-induced fluence. The plan quality variation was acquired by comparing PTV coverage. Eight complexity scores were calculated based on the beam flu-ence and the MLC sequence. The complexity scores include fractal dimension, monitor unit, modulation index, fluence map complexity, weighted average of field area, weighted average of field perimeter, and small aperture ratio (< 5 cm2 and < 50cm2). The Spearman's rank correlation coefficient was calculated to analyze the correlation between these scores and gamma pass rate and plan quality varia-tion. For planar QA, the most significant complexity index was fractal dimension for DMLC (p = -0.40) and weighted segment area for SMLC (p = 0.27) at low magnitude MLC error. For plan quality, the most significant complexity index was weighted segment perimeter for DMLC (p = 0.56) and weighted segment area for SMLC (p= 0.497) at low magnitude MLC error. The sensitivity of planar QA was weakly associated with the field complexity with low magnitude MLC error, but the plan quality robustness was associated with beam complexity. Plans with simple beams were more robust to MLC error.

Is internal target volume accurate for dose evaluation in lung cancer stereotactic body radiotherapy?

PURPOSE: 4DCT delineated internal target volume (ITV) was applied to determine the tumor motion and used as planning target in treatment planning in lung cancer stereotactic body radiotherapy (SBRT). This work is to study the accuracy of using ITV to predict the real target dose in lung cancer SBRT. MATERIALS AND METHODS: Both for phantom and patient cases, the ITV and gross tumor volumes (GTVs) were contoured on the maximum intensity projection (MIP) CT and ten CT phases, respectively. A SBRT plan was designed using ITV as the planning target on average projection (AVG) CT. This plan was copied to each CT phase and the dose distribution was recalculated. The GTV_4D dose was acquired through accumulating the GTV doses over all ten phases and regarded as the real target dose. To analyze the ITV dose error, the ITV dose was compared to the real target dose by endpoints of D99, D95, D1 (doses received by the 99%, 95% and 1% of the target volume), and dose coverage endpoint of V100(relative volume receiving at least the prescription dose). RESULTS: The phantom study shows that the ITV underestimates the real target dose by 9.47%~19.8% in D99, 4.43%~15.99% in D95, and underestimates the dose coverage by 5% in V100. The patient cases show that the ITV underestimates the real target dose and dose coverage by 3.8%~10.7% in D99, 4.7%~7.2% in D95, and 3.96%~6.59% in V100 in motion target cases. CONCLUSIONS: Cautions should be taken that ITV is not accurate enough to predict the real target dose in lung cancer SBRT with large tumor motions. Restricting the target motion or reducing the target dose heterogeneity could reduce the ITV dose underestimation effect in lung SBRT.

Dosimetric comparisons of VMAT, IMRT and 3DCRT for locally advanced rectal cancer with simultaneous integrated boost.

The simultaneous integrated boost radiotherapy for preoperative locally advanced rectal cancer (LARC) can improve the local control and overall survival rates. The purpose of this study is to compare the dosimetric differences among volumetric modulated arc therapy (VMAT), fixed-field intensity modulated radiotherapy (IMRT) and three-dimensional conformal radiotherapy (3DCRT) for the LARC. Ten LARC patients treated in our department using the simultaneous escalate strategy were retrospectively analyzed in this study. All patients had T3 with N+/- and were treated with IMRT. Two additional VMAT and 3DCRT plans were created for each patient. VMAT plans were designed using SmartArc planning module. Both IMRT and SmartArc had similar optimization objectives. The prescription was 50 Gy to the planning clinical target volume (PTV-C) and 56 Gy to the planning gross target volume (PTV-G). The target coverage and organs at risk (OARs) were compared for all the techniques. The paired, two-tailed Wilcoxon signed-rank test was applied for statistical analysis. Results of this study indicate that IMRT and SmartArc were all significantly superior to 3DCRT in most of the relevant values evaluated of target response, OARs and normal tissue sparing. They provided comparable dosimetric parameters for target volume. But IMRT shows better sparing for OARs and normal tissue.

Developing new extension of GafChromic RTQA2 film to patient quality assurance field using a plan-based calibration method.

GafChromic RTQA2 film is a type of radiochromic film designed for light field and radiation field alignment. The aim of this study is to extend the application of RTQA2 film to the measurement of patient specific quality assurance (QA) fields as a 2D relative dosimeter.Pre-irradiated and post-irradiated RTQA2 films were scanned in reflection mode using a flatbed scanner. A plan-based calibration (PBC) method utilized the mapping information of the calculated dose image and film grayscale image to create a dose versus pixel value calibration model. This model was used to calibrate the film grayscale image to the film relative dose image. The dose agreement between calculated and film dose images were analyzed by gamma analysis. To evaluate the feasibility of this method, eight clinically approved RapidArc cases (one abdomen cancer and seven head-and-neck cancer patients) were tested using this method. Moreover, three MLC gap errors and two MLC transmission errors were introduced to eight Rapidarc cases respectively to test the robustness of this method.The PBC method could overcome the film lot and post-exposure time variations of RTQA2 film to get a good 2D relative dose calibration result. The mean gamma passing rate of eight patients was 97.90% ± 1.7%, which showed good dose consistency between calculated and film dose images. In the error test, the PBC method could over-calibrate the film, which means some dose error in the film would be falsely corrected to keep the dose in film consistent with the dose in the calculated dose image. This would then lead to a false negative result in the gamma analysis. In these cases, the derivative curve of the dose calibration curve would be non-monotonic which would expose the dose abnormality.By using the PBC method, we extended the application of more economical RTQA2 film to patient specific QA. The robustness of the PBC method has been improved by analyzing the monotonicity of the derivative of the calibration curve.