Evaluating Virtual Contrast-enhanced MRI (VCE-MRI) in Nasopharyngeal Carcinoma Radiotherapy: A Retrospective Analysis for Primary Gross Tumor Delineation.

PURPOSE: To investigate the potential of virtual contrast-enhanced MRI (VCE-MRI) for gross-tumor-volume (GTV) delineation of nasopharyngeal carcinoma (NPC) using multi-institutional data. METHODS AND MATERIALS: This study retrospectively retrieved T1-weighted (T1w), T2-weighted (T2w) MRI, gadolinium-based contrast-enhanced MRI (CE-MRI) and planning CT of 348 biopsy-proven NPC patients from three oncology centers. A multimodality-guided synergistic neural network (MMgSN-Net) was trained using 288 patients to leverage complementary features in T1w and T2w MRI for VCE-MRI synthesis, which was independently evaluated using 60 patients. Three board-certified radiation oncologists and two medical physicists participated in clinical evaluations in three aspects: image quality assessment of the synthetic VCE-MRI, VCE-MRI in assisting target volume delineation, and effectiveness of VCE-MRI-based contours in treatment planning. The image quality assessment includes distinguishability between VCE-MRI and CE-MRI, clarity of tumor-to-normal tissue interface and veracity of contrast enhancement in tumor invasion risk areas. Primary tumor delineation and treatment planning were manually performed by radiation oncologists and medical physicists, respectively. RESULTS: The mean accuracy to distinguish VCE-MRI from CE-MRI was 31.67%; no significant difference was observed in the clarity of tumor-to-normal tissue interface between VCE-MRI and CE-MRI; for the veracity of contrast enhancement in tumor invasion risk areas, an accuracy of 85.8% was obtained. The image quality assessment results suggest that the image quality of VCE-MRI is highly similar to real CE-MRI. The mean dosimetric difference of planning target volumes were less than 1Gy. CONCLUSIONS: The VCE-MRI is highly promising to replace the use of gadolinium-based CE-MRI in tumor delineation of NPC patients.

The Conductance Isotope Effect in Oligophenylene Imine Molecular Wires Depends on the Number and Spacing of 13C-Labeled Phenylene Rings.

We report a strong and structurally sensitive 13C intramolecular conductance isotope effect (CIE) for oligophenyleneimine (OPI) molecular wires connected to Au electrodes. Wires were built from Au surfaces beginning with the formation of 4-aminothiophenol self-assembled monolayers (SAMs) followed by subsequent condensation reactions with 13C-labeled terephthalaldehyde and phenylenediamine; in these monomers the phenylene rings were either completely 13C-labeled or the naturally abundant 12C isotopologues. Alternatively, perdeuterated versions of terephthalaldehyde and phenylenediamine were employed to make 2H(D)-labeled OPI wires. For 13C-isotopologues of short OPI wires (<4 nm) in length where the charge transport mechanism is tunneling, there was no measurable effect, i.e., 13C CIE ≈ 1, where CIE is defined as the ratio of labeled and unlabeled wire resistances, i.e., CIE = Rheavy/Rlight. However, for long OPI wires >4 nm, in which the transport mechanism is polaron hopping, a strong 13C CIE = 4-5 was observed. A much weaker inverse CIE < 1 was evident for the longest D-labeled wires. Importantly, the magnitude of the 13C CIE was sensitive to the number and spacing of 13C-labeled rings, i.e., the CIE was structurally sensitive. The structural sensitivity is intriguing because it may be employed to understand polaron hopping mechanisms and charge localization/delocalization in molecular wires. A preliminary theoretical analysis explored several possible explanations for the CIE, but so far a fully satisfactory explanation has not been identified. Nevertheless, the latest results unambiguously demonstrate structural sensitivity of the heavy atom CIE, offering directions for further utilization of this interesting effect.

Model Generalizability Investigation for GFCE-MRI Synthesis in NPC Radiotherapy Using Multi-Institutional Patient-Based Data Normalization.

Recently, deep learning has been demonstrated to be feasible in eliminating the use of gadoliniumbased contrast agents (GBCAs) through synthesizing gadolinium-free contrast-enhanced MRI (GFCE-MRI) from contrast-free MRI sequences, providing the community with an alternative to get rid of GBCAs-associated safety issues in patients. Nevertheless, generalizability assessment of the GFCE-MRI model has been largely challenged by the high inter-institutional heterogeneity of MRI data, on top of the scarcity of multi-institutional data itself. Although various data normalization methods have been adopted to address the heterogeneity issue, it has been limited to single-institutional investigation and there is no standard normalization approach presently. In this study, we aimed at investigating generalizability of GFCE-MRI model using data from seven institutions by manipulating heterogeneity of MRI data under five popular normalization approaches. Three state-of-the-art neural networks were applied to map from T1-weighted and T2-weighted MRI to contrast-enhanced MRI (CE-MRI) for GFCE-MRI synthesis in patients with nasopharyngeal carcinoma. MRI data from three institutions were used separately to generate three uni-institution models and jointly for a tri-institution model. The five normalization methods were applied to normalize the data of each model. MRI data from the remaining four institutions served as external cohorts for model generalizability assessment. Quality of GFCE-MRI was quantitatively evaluated against ground-truth CE-MRI using mean absolute error (MAE) and peak signal-to-noise ratio(PSNR). Results showed that performance of all uni-institution models remarkably dropped on the external cohorts. By contrast, model trained using multi-institutional data with Z-Score normalization yielded the best model generalizability improvement.

Respiratory-Correlated 4-Dimensional Magnetic Resonance Fingerprinting for Liver Cancer Radiation Therapy Motion Management.

PURPOSE: The objective of this study was to develop a respiratory-correlated (RC) 4-dimensional (4D) imaging technique based on magnetic resonance fingerprinting (MRF) (RC-4DMRF) for liver tumor motion management in radiation therapy. METHODS AND MATERIALS: Thirteen patients with liver cancer were prospectively enrolled in this study. k-space MRF signals of the liver were acquired during free-breathing using the fast acquisition with steady-state precession sequence on a 3T scanner. The signals were binned into 8 respiratory phases based on respiratory surrogates, and interphase displacement vector fields were estimated using a phase-specific low-rank optimization method. Hereafter, the tissue property maps, including T1 and T2 relaxation times, and proton density, were reconstructed using a pyramid motion-compensated method that alternatively optimized interphase displacement vector fields and subspace images. To evaluate the efficacy of RC-4DMRF, amplitude motion differences and Pearson correlation coefficients were determined to assess measurement agreement in tumor motion between RC-4DMRF and cine magnetic resonance imaging (MRI); mean absolute percentage errors of the RC-4DMRF-derived tissue maps were calculated to reveal tissue quantification accuracy using digital human phantom; and tumor-to-liver contrast-to-noise ratio of RC-4DMRF images was compared with that of planning CT and contrast-enhanced MRI (CE-MRI) images. A paired Student t test was used for statistical significance analysis with a P value threshold of .05. RESULTS: RC-4DMRF achieved excellent agreement in motion measurement with cine MRI, yielding the mean (± standard deviation) Pearson correlation coefficients of 0.95 ± 0.05 and 0.93 ± 0.09 and amplitude motion differences of 1.48 ± 1.06 mm and 0.81 ± 0.64 mm in the superior-inferior and anterior-posterior directions, respectively. Moreover, RC-4DMRF achieved high accuracy in tissue property quantification, with mean absolute percentage errors of 8.8%, 9.6%, and 5.0% for T1, T2, and proton density, respectively. Notably, the tumor contrast-to-noise ratio in RC-4DMRI-derived T1 maps (6.41 ± 3.37) was found to be the highest among all tissue property maps, approximately equal to that of CE-MRI (6.96 ± 1.01, P = .862), and substantially higher than that of planning CT (2.91 ± 1.97, P = .048). CONCLUSIONS: RC-4DMRF demonstrated high accuracy in respiratory motion measurement and tissue properties quantification, potentially facilitating tumor motion management in liver radiation therapy.

Radiomic feature repeatability and its impact on prognostic model generalizability: A multi-institutional study on nasopharyngeal carcinoma patients.

BACKGROUND AND PURPOSE: To investigate the radiomic feature (RF) repeatability via perturbation and its impact on cross-institutional prognostic model generalizability in Nasopharyngeal Carcinoma (NPC) patients. MATERIALS AND METHODS: 286 and 183 NPC patients from two institutions were included for model training and validation. Perturbations with random translations and rotations were applied to contrast-enhanced T1-weighted (CET1-w) MR images. RFs were extracted from primary tumor volume under a wide range of image filtering and discretization settings. RF repeatability was assessed by intraclass correlation coefficient (ICC), which was used to equally separate the RFs into low- and high-repeatable groups by the median value. After feature selection, multivariate Cox regression and Kaplan-Meier analysis were independently employed to develop and analyze prognostic models. Concordance index (C-index) and P-value from log-rank test were used to assess model performance. RESULTS: Most textural RFs from high-pass wavelet-filtered images were susceptible to image perturbations. It was more prominent when a smaller discretization bin number was used (e.g., 8, mean ICC = 0.69). Using high-repeatable RFs for model development yielded a significantly higher C-index (0.63) in the validation cohort than when only low-repeatable RFs were used (0.57, P = 0.024), suggesting higher model generalizability. Besides, significant risk stratification in the validation cohort was observed only when high-repeatable RFs were used (P < 0.001). CONCLUSION: Repeatability of RFs from high-pass wavelet-filtered CET1-w MR images of primary NPC tumor was poor, particularly when a smaller bin number was used. Exclusive use of high-repeatable RFs is suggested to safeguard model generalizability for wide-spreading clinical utilization.

Sequential transarterial chemoembolisation and stereotactic body radiotherapy followed by immunotherapy as conversion therapy for patients with locally advanced, unresectable hepatocellular carcinoma (START-FIT): a single-arm, phase 2 trial.

BACKGROUND: The synergy between locoregional therapies and immune checkpoint inhibitors has not been investigated as conversion therapy for unresectable hepatocellular carcinoma. We aimed to investigate the activity of sequential transarterial chemoembolisation (TACE) and stereotactic body radiotherapy followed by avelumab (an anti-PD-L1 drug) for locally advanced, unresectable hepatocellular carcinoma. METHODS: START-FIT was a single-arm, phase 2 trial in patients with locally advanced hepatocellular carcinoma who were not suitable for curative treatment, conducted in two hospitals in Hong Kong and one in Shenzhen, China. Eligible patients were those aged 18 years or older with an Eastern Cooperative Oncology Group performance status 0-1, Child-Pugh liver function score A5 to B7, tumour size of at least 5 cm, a maximum of three tumour lesions, and adequate hepatic, renal, and bone marrow function. Participants received TACE on day 1, followed by stereotactic body radiotherapy (27·5-40·0 Gy in five fractions) at day 28. Avelumab (10 mg/kg) was administered 14 days following stereotactic body radiotherapy and every 2 weeks thereafter. The primary endpoint was the proportion of patients deemed amenable to curative treatment, defined as those who had a sustained complete or partial treatment response for at least 2 months and if curative treatment could be performed (ie, resection, radiofrequency ablation, or transplantation), analysed by intention to treat. Safety was also analysed in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT03817736) and has been completed. FINDINGS: Between March 18, 2019, and Jan 27, 2021, 33 patients (32 [97%] men and one [3%] woman) were enrolled. The median sum of the largest diameters of lesions was 15·1 cm (IQR 8·3-14·9). 21 (64%) patients had macrovascular invasion (hepatic vein [n=13], branched portal vein [n=3], or both [n=5]). Median follow-up was 17·2 months (IQR 7·8-25·8). 18 (55%) patients were deemed amenable to curative treatment: four (12%) of 33 patients had curative treatment (resection [n=2] or radiofrequency ablation [n=2]), and 14 (42%) had a radiological complete response and opted for close surveillance. 11 (33%) of 33 patients had treatment-related adverse events that were grade 3 or worse. The most common treatment-related grade 3 or worse adverse event was transient increase in alanine aminotransferase or aspartate aminotransferase (five [15%]) after TACE. Five (15%) patients developed immune-related adverse events of grade 3 or worse (three had hepatitis, two had dermatitis). INTERPRETATION: To our knowledge, this is the first prospective trial using the combination of immunotherapy and locoregional treatment as conversion therapy for locally advanced unresectable hepatocellular carcinoma, with promising results. Future randomised trials with larger cohorts of patients are warranted. FUNDING: Merck.

Corrigendum: Investigation of a novel deep learning-based computed tomography perfusion mapping framework for functional lung avoidance radiotherapy.

[This corrects the article DOI: 10.3389/fonc.2021.644703.].

Treatment Outcomes of Computer Tomography-Guided Brachytherapy in Cervical Cancer in Hong Kong: A Retrospective Review.

(1) Background: To report the long-term clinical outcomes of computer-tomography (CT)-guided brachytherapy (BT) for locally advanced cervical cancer. (2) Methods: A total of 135 patients with FIGO stage IB-IVA cervical cancer treated with definitive radiotherapy +/- chemotherapy with an IGABT boost at Queen Mary Hospital, Hong Kong, between November 2013 and December 2019 were included. Treatment included pelvic radiotherapy 40 Gy/20 Fr/4 weeks +/- chemotherapy then CT-guided BT (7 Gy × 4 Fr) and a sequential parametrial boost. The primary outcome was local control. Secondary outcomes were pelvic control, distant metastasis-free survival, overall survival (OS) and late toxicities. (3) Results: The median follow-up was 53.6 months (3.0-99.6 months). The five-year local control, pelvic control, distant metastasis-free survival and OS rates were 90.7%, 84.3%, 80.0% and 87.2%, respectively. The incidence of G3/4 long-term toxicities was 6.7%, including proctitis (2.2%), radiation cystitis (1.5%), bowel perforation (0.7%), ureteric stricture (0.7%) and vaginal stenosis and fistula (0.7%). Patients with adenocarcinomas had worse local control (HR 5.82, 95% CI 1.84-18.34, p = 0.003), pelvic control (HR 4.41, 95% CI 1.83-10.60, p = 0.001), distant metastasis-free survival (HR 2.83, 95% CI 1.17-6.84, p = 0.021) and OS (HR 4.38, 95% CI: 1.52-12.67, p = 0.003) rates. Distant metastasis-free survival was associated with HR-CTV volume ≥ 30 cm3 (HR 3.44, 95% CI 1.18-9.42, p = 0.025) and the presence of pelvic lymph node (HR 3.44, 95% CI 1.18-9.42, p = 0.025). OS was better in patients with concurrent chemotherapy (HR 4.33, 95% CI: 1.40-13.33, p = 0.011). (4) Conclusions: CT-guided BT for cervical cancer achieved excellent long-term local control and OS. Adenocarcinoma was associated with worse clinical outcomes. (4) Conclusion: CT-guided BT for cervical cancer achieved excellent long-term local control and OS. Adenocarcinoma was associated with worse clinical outcomes.

A Transfer Learning Framework for Deep Learning-Based CT-to-Perfusion Mapping on Lung Cancer Patients.

Purpose: Deep learning model has shown the feasibility of providing spatial lung perfusion information based on CT images. However, the performance of this method on lung cancer patients is yet to be investigated. This study aims to develop a transfer learning framework to evaluate the deep learning based CT-to-perfusion mapping method specifically on lung cancer patients. Methods: SPECT/CT perfusion scans of 33 lung cancer patients and 137 non-cancer patients were retrospectively collected from two hospitals. To adapt the deep learning model on lung cancer patients, a transfer learning framework was developed to utilize the features learned from the non-cancer patients. These images were processed to extract features from three-dimensional CT images and synthesize the corresponding CT-based perfusion images. A pre-trained model was first developed using a dataset of patients with lung diseases other than lung cancer, and subsequently fine-tuned specifically on lung cancer patients under three-fold cross-validation. A multi-level evaluation was performed between the CT-based perfusion images and ground-truth SPECT perfusion images in aspects of voxel-wise correlation using Spearman's correlation coefficient (R), function-wise similarity using Dice Similarity Coefficient (DSC), and lobe-wise agreement using mean perfusion value for each lobe of the lungs. Results: The fine-tuned model yielded a high voxel-wise correlation (0.8142 ± 0.0669) and outperformed the pre-trained model by approximately 8%. Evaluation of function-wise similarity indicated an average DSC value of 0.8112 ± 0.0484 (range: 0.6460-0.8984) for high-functional lungs and 0.8137 ± 0.0414 (range: 0.6743-0.8902) for low-functional lungs. Among the 33 lung cancer patients, high DSC values of greater than 0.7 were achieved for high functional volumes in 32 patients and low functional volumes in all patients. The correlations of the mean perfusion value on the left upper lobe, left lower lobe, right upper lobe, right middle lobe, and right lower lobe were 0.7314, 0.7134, 0.5108, 0.4765, and 0.7618, respectively. Conclusion: For lung cancer patients, the CT-based perfusion images synthesized by the transfer learning framework indicated a strong voxel-wise correlation and function-wise similarity with the SPECT perfusion images. This suggests the great potential of the deep learning method in providing regional-based functional information for functional lung avoidance radiation therapy.

Evaluation of Multisource Adaptive MRI Fusion for Gross Tumor Volume Delineation of Hepatocellular Carcinoma.

Purpose: Tumor delineation plays a critical role in radiotherapy for hepatocellular carcinoma (HCC) patients. The incorporation of MRI might improve the ability to correctly identify tumor boundaries and delineation consistency. In this study, we evaluated a novel Multisource Adaptive MRI Fusion (MAMF) method in HCC patients for tumor delineation. Methods: Ten patients with HCC were included in this study retrospectively. Contrast-enhanced T1-weighted MRI at portal-venous phase (T1WPP), contrast-enhanced T1-weighted MRI at 19-min delayed phase (T1WDP), T2-weighted (T2W), and diffusion-weighted MRI (DWI) were acquired on a 3T MRI scanner and imported to in-house-developed MAMF software to generate synthetic MR fusion images. The original multi-contrast MR image sets were registered to planning CT by deformable image registration (DIR) using MIM. Four observers independently delineated gross tumor volumes (GTVs) on the planning CT, four original MR image sets, and the fused MRI for all patients. Tumor contrast-to-noise ratio (CNR) and Dice similarity coefficient (DSC) of the GTVs between each observer and a reference observer were measured on the six image sets. Inter-observer and inter-patient mean, SD, and coefficient of variation (CV) of the DSC were evaluated. Results: Fused MRI showed the highest tumor CNR compared to planning CT and original MR sets in the ten patients. The mean ± SD tumor CNR was 0.72 ± 0.73, 3.66 ± 2.96, 4.13 ± 3.98, 4.10 ± 3.17, 5.25 ± 2.44, and 9.82 ± 4.19 for CT, T1WPP, T2W, DWI, T1WDP, and fused MRI, respectively. Fused MRI has the minimum inter-observer and inter-patient variations as compared to original MR sets and planning CT sets. GTV delineation inter-observer mean DSC across the ten patients was 0.81 ± 0.09, 0.85 ± 0.08, 0.88 ± 0.04, 0.89 ± 0.08, 0.90 ± 0.04, and 0.95 ± 0.02 for planning CT, T1WPP, T2W, DWI, T1WDP, and fused MRI, respectively. The patient mean inter-observer CV of DSC was 3.3%, 3.2%, 1.7%, 2.6%, 1.5%, and 0.9% for planning CT, T1WPP, T2W, DWI, T1WDP, and fused MRI, respectively. Conclusion: The results demonstrated that the fused MRI generated using the MAMF method can enhance tumor CNR and improve inter-observer consistency of GTV delineation in HCC as compared to planning CT and four commonly used MR image sets (T1WPP, T1WDP, T2W, and DWI). The MAMF method holds great promise in MRI applications in HCC radiotherapy treatment planning.

A Multi-Center Study of CT-Based Neck Nodal Radiomics for Predicting an Adaptive Radiotherapy Trigger of Ill-Fitted Thermoplastic Masks in Patients with Nasopharyngeal Carcinoma.

Significant lymph node shrinkage is common in patients with nasopharyngeal carcinoma (NPC) throughout radiotherapy (RT) treatment, causing ill-fitted thermoplastic masks (IfTMs). To deal with this, an ad hoc adaptive radiotherapy (ART) may be required to ensure accurate and safe radiation delivery and to maintain treatment efficacy. Presently, the entire procedure for evaluating an eligible ART candidate is time-consuming, resource-demanding, and highly inefficient. In the artificial intelligence paradigm, the pre-treatment identification of NPC patients at risk for IfTMs has become greatly demanding for achieving efficient ART eligibility screening, while no relevant studies have been reported. Hence, we aimed to investigate the capability of computed tomography (CT)-based neck nodal radiomics for predicting IfTM-triggered ART events in NPC patients via a multi-center setting. Contrast-enhanced CT and the clinical data of 124 and 58 NPC patients from Queen Elizabeth Hospital (QEH) and Queen Mary Hospital (QMH), respectively, were retrospectively analyzed. Radiomic (R), clinical (C), and combined (RC) models were developed using the ridge algorithm in the QEH cohort and evaluated in the QMH cohort using the median area under the receiver operating characteristics curve (AUC). Delong's test was employed for model comparison. Model performance was further assessed on 1000 replicates in both cohorts separately via bootstrapping. The R model yielded the highest "corrected" AUC of 0.784 (BCa 95%CI: 0.673-0.859) and 0.723 (BCa 95%CI: 0.534-0.859) in the QEH and QMH cohort following bootstrapping, respectively. Delong's test indicated that the R model performed significantly better than the C model in the QMH cohort (p < 0.0001), while demonstrating no significant difference compared to the RC model (p = 0.5773). To conclude, CT-based neck nodal radiomics was capable of predicting IfTM-triggered ART events in NPC patients in this multi-center study, outperforming the traditional clinical model. The findings of this study provide valuable insights for future study into developing an effective screening strategy for ART eligibility in NPC patients in the long run, ultimately alleviating the workload of clinical practitioners, streamlining ART procedural efficiency in clinics, and achieving personalized RT for NPC patients in the future.

Methodological quality of systematic reviews on Chinese herbal medicine: a methodological survey.

BACKGROUND: Systematic reviews (SRs) synthesise the best evidence of effectiveness and safety on Chinese herbal medicine (CHM). Decision-making should be supported by the high-quality evidence of prudently conducted SRs, but the trustworthiness of conclusions may be limited by poor methodological rigour. METHODS: This survey aimed to examine the methodological quality of a representative sample of SRs on CHM published during January 2018 to March 2020. We conducted literature search in Cochrane Database of Systematic Reviews, MEDLINE via Ovid, and EMBASE via Ovid. Eligible SRs must be in Chinese or English with at least one meta-analysis on the treatment effect of any CHM documented in the 2015 Chinese Pharmacopoeia. Two reviewers extracted the bibliographical characteristics of SRs and appraised their methodological quality using AMSTAR 2 (Assessing the Methodological Quality of Systematic Reviews 2). The associations between bibliographical characteristics and methodological quality were investigated using Kruskal-Wallis tests and Spearman's rank correlation coefficients. RESULTS: We sampled and appraised one hundred forty-eight SRs. Overall, one (0.7%) was of high methodological quality; zero (0%), four (2.7%), and one-hundred forty-three (96.6%) SRs were of moderate, low, and critically-low quality. Only thirteen SRs (8.8%) provided a pre-defined protocol; none (0%) provided justifications for including particular primary study designs; six (4.1%) conducted a comprehensive literature search; two (1.4%) provided a list of excluded studies; nine (6.1%) undertook meta-analysis with appropriate methods; and seven (4.7%) reported funding sources of included primary studies. Cochrane reviews had higher overall quality than non-Cochrane reviews (P < 0.001). SRs with European funding support were less likely to have critically-low quality when compared with their counterparts (P = 0.020). SRs conducted by more authors (rs = 0.23; P = 0.006) and published in higher impact factor journals (rs = 0.20; P = 0.044) were associated with higher methodological quality. CONCLUSIONS: Our results indicated that the methodological quality of SRs on CHM is low. Future authors should enhance the methodological quality through registering a priori protocols, justifying selection of study designs, conducting comprehensive literature search, providing a list of excluded studies with rationales, using appropriate method for meta-analyses, and reporting funding sources among primary studies.

Respiratory 4D-Gating F-18 FDG PET/CT Scan for Liver Malignancies: Feasibility in Liver Cancer Patient and Tumor Quantitative Analysis.

PURPOSE: To evaluate the potential clinical role and effectiveness of respiratory 4D-gating F-18 FDG PET/CT scan for liver malignancies, relative to routine (3D) F-18 FDG PET/CT scan. MATERIALS AND METHODS: This study presented a prospective clinical study of 16 patients who received F-18 FDG PET/CT scan for known or suspected malignant liver lesions. Ethics approvals were obtained from the ethics committees of the Hong Kong Baptist Hospital and The Hong Kong Polytechnic University. Liver lesions were compared between the gated and ungated image sets, in terms of 1) volume measurement of PET image, 2) accuracy of maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), and 3) accuracy of total lesion glycoses (TLG). Statistical analysis was performed by using a two-tailed paired Student t-test and Pearson correlation test. RESULTS: The study population consisted of 16 patients (9 males and 7 females; mean age of 65) with a total number of 89 lesions. The SUVmax and SUVmean measurement of the gated PET images was more accurate than that of the ungated PET images, compared to the static reference images. An average of 21.48% (p < 0.001) reduction of the tumor volume was also observed. The SUVmax and SUVmean of the gated PET images were improved by 19.81% (p < 0.001) and 25.53% (p < 0.001), compared to the ungated PET images. CONCLUSIONS: We have demonstrated the feasibility of implementing 4D PET/CT scan for liver malignancies in a prospective clinical study. The 4D PET/CT scan for liver malignancies could improve the quality of PET image by improving the SUV accuracy of the lesions and reducing image blurring. The improved accuracy in the classification and identification of liver tumors with 4D PET image would potentially lead to its increased utilization in target delineation of GTV, ITV, and PTV for liver radiotherapy treatment planning in the future.

Quantitative Spatial Characterization of Lymph Node Tumor for N Stage Improvement of Nasopharyngeal Carcinoma Patients.

This study aims to investigate the feasibility of improving the prognosis stratification of the N staging system of Nasopharyngeal Carcinoma (NPC) from quantitative spatial characterizations of metastatic lymph node (LN) for NPC in a multi-institutional setting. A total of 194 and 284 NPC patients were included from two local hospitals as the discovery and validation cohort. Spatial relationships between LN and the surrounding organs were quantified by both distance and angle histograms, followed by principal component analysis. Independent prognostic factors were identified and combined with the N stage into a new prognostic index by univariate and multivariate Cox regressions on disease-free survival (DFS). The new three-class risk stratification based on the constructed prognostic index demonstrated superior cross-institutional performance in DFS. The hazard ratios of the high-risk to low-risk group were 9.07 (p < 0.001) and 4.02 (p < 0.001) on training and validation, respectively, compared with 5.19 (p < 0.001) and 1.82 (p = 0.171) of N3 to N1. Our spatial characterizations of lymph node tumor anatomy improved the existing N-stage in NPC prognosis. Our quantitative approach may facilitate the discovery of new anatomical characteristics to improve patient staging in other diseases.

Photo-modulated supramolecular self-assembly of ortho-nitrobenzyl ester-based alkynylplatinum(II) 2,6-bis(N-alkylbenzimidazol-2'-yl)pyridine complexes.

The enhanced supramolecular self-assembly behaviors of photo-caged platinum(II) complexes have been triggered by applying light as the external stimulus. Distinct morphological transformation of the nanoaggregates has been observed in the photo-caged complexes before and after UV irradiation.

Low methodological quality of systematic reviews on acupuncture: a cross-sectional study.

BACKGROUND: While well-conducted systematic reviews (SRs) can provide the best evidence on the potential effectiveness of acupuncture, limitations on the methodological rigour of SRs may impact the trustworthiness of their conclusions. This cross-sectional study aimed to evaluate the methodological quality of a representative sample of SRs on acupuncture effectiveness. METHODS: Cochrane Database of Systematic Reviews, MEDLINE, and EMBASE were searched for SRs focusing on the treatment effect of manual acupuncture or electro-acupuncture published during January 2018 and March 2020. Eligible SRs must contain at least one meta-analysis and be published in English language. Two independent reviewers extracted the bibliographical characteristics of the included SRs with a pre-designed questionnaire and appraised the methodological quality of the studies with the validated AMSTAR 2 (A MeaSurement Tool to Assess systematic Reviews 2). The associations between bibliographical characteristics and methodological quality ratings were explored using Kruskal-Wallis rank tests and Spearman's rank correlation coefficients. RESULTS: A total of 106 SRs were appraised. Only one (0.9%) SR was of high overall methodological quality, zero (0%) was of moderate-quality, six (5.7%) and 99 (93.4%) were of low-quality and critically low-quality respectively. Among appraised SRs, only ten (9.4%) provided an a priori protocol, four (3.8%) conducted a comprehensive literature search, five (4.7%) provided a list of excluded studies, and six (5.7%) performed meta-analysis appropriately. Cochrane SRs, updated SRs, and SRs that did not search non-English databases had relatively higher overall quality. CONCLUSIONS: Methodological quality of SRs on acupuncture is unsatisfactory. Future reviewers should improve critical methodological aspects of publishing protocols, performing comprehensive search, providing a list of excluded studies with justifications for exclusion, and conducting appropriate meta-analyses. These recommendations can be implemented via enhancing the technical competency of reviewers in SR methodology through established education approaches as well as quality gatekeeping by journal editors and reviewers. Finally, for evidence users, skills in SR critical appraisal remain to be essential as relevant evidence may not be available in pre-appraised formats.

Investigation of a Novel Deep Learning-Based Computed Tomography Perfusion Mapping Framework for Functional Lung Avoidance Radiotherapy.

Functional lung avoidance radiation therapy aims to minimize dose delivery to the normal lung tissue while favoring dose deposition in the defective lung tissue based on the regional function information. However, the clinical acquisition of pulmonary functional images is resource-demanding, inconvenient, and technically challenging. This study aims to investigate the deep learning-based lung functional image synthesis from the CT domain. Forty-two pulmonary macro-aggregated albumin SPECT/CT perfusion scans were retrospectively collected from the hospital. A deep learning-based framework (including image preparation, image processing, and proposed convolutional neural network) was adopted to extract features from 3D CT images and synthesize perfusion as estimations of regional lung function. Ablation experiments were performed to assess the effects of each framework component by removing each element of the framework and analyzing the testing performances. Major results showed that the removal of the CT contrast enhancement component in the image processing resulted in the largest drop in framework performance, compared to the optimal performance (~12%). In the CNN part, all the three components (residual module, ROI attention, and skip attention) were approximately equally important to the framework performance; removing one of them resulted in a 3-5% decline in performance. The proposed CNN improved ~4% overall performance and ~350% computational efficiency, compared to the U-Net model. The deep convolutional neural network, in conjunction with image processing for feature enhancement, is capable of feature extraction from CT images for pulmonary perfusion synthesis. In the proposed framework, image processing, especially CT contrast enhancement, plays a crucial role in the perfusion synthesis. This CTPM framework provides insights for relevant research studies in the future and enables other researchers to leverage for the development of optimized CNN models for functional lung avoidance radiation therapy.

Multi-Organ Omics-Based Prediction for Adaptive Radiation Therapy Eligibility in Nasopharyngeal Carcinoma Patients Undergoing Concurrent Chemoradiotherapy.

PURPOSE: To investigate the role of different multi-organ omics-based prediction models for pre-treatment prediction of Adaptive Radiotherapy (ART) eligibility in patients with nasopharyngeal carcinoma (NPC). METHODS AND MATERIALS: Pre-treatment contrast-enhanced computed tomographic and magnetic resonance images, radiotherapy dose and contour data of 135 NPC patients treated at Hong Kong Queen Elizabeth Hospital were retrospectively analyzed for extraction of multi-omics features, namely Radiomics (R), Morphology (M), Dosiomics (D), and Contouromics (C), from a total of eight organ structures. During model development, patient cohort was divided into a training set and a hold-out test set in a ratio of 7 to 3 via 20 iterations. Four single-omics models (R, M, D, C) and four multi-omics models (RD, RC, RM, RMDC) were developed on the training data using Ridge and Multi-Kernel Learning (MKL) algorithm, respectively, under 10-fold cross validation, and evaluated on hold-out test data using average area under the receiver-operator-characteristics curve (AUC). The best-performing single-omics model was first determined by comparing the AUC distribution across the 20 iterations among the four single-omics models using two-sided student t-test, which was then retrained using MKL algorithm for a fair comparison with the four multi-omics models. RESULTS: The R model significantly outperformed all other three single-omics models (all p-value<0.0001), achieving an average AUC of 0.942 (95%CI: 0.938-0.946) and 0.918 (95%CI: 0.903-0.933) in training and hold-out test set, respectively. When trained with MKL, the R model (R_MKL) yielded an increased AUC of 0.984 (95%CI: 0.981-0.988) and 0.927 (95%CI: 0.905-0.948) in training and hold-out test set respectively, while demonstrating no significant difference as compared to all studied multi-omics models in the hold-out test sets. Intriguingly, Radiomic features accounted for the majority of the final selected features, ranging from 64% to 94%, in all the studied multi-omics models. CONCLUSIONS: Among all the studied models, the Radiomic model was found to play a dominant role for ART eligibility in NPC patients, and Radiomic features accounted for the largest proportion of features in all the multi-omics models.

A longitudinal study on the relationship among childhood emotional abuse, gratitude, and suicidal ideation of Chinese adolescents.

BACKGROUND AND OBJECTIVE: Suicidal ideation is a significant predictor of suicidal attempt. Based on the developmental psychopathology perspective and the resilience theory, this study examines whether trait gratitude mediates the relationship between childhood emotional abuse and adolescent suicidal ideation. PARTICIPANTS AND SETTING: A sample of 909 Grade 8 to Grade 9 adolescents aged 12-18 years in Hong Kong, a Special Administrative Region in China, was recruited from six secondary schools. METHOD: A two-wave longitudinal study was conducted. Participants completed the same measures on Gratitude Quesitonnaire-6, Suicidal Ideation Scale, emotional subscale of Child Abuse and Trauma Scale at two time points 12 months apart. RESULTS: Results of cross-lagged analyses showed that adolescents' suicidal ideation was positively associated with childhood emotional abuse and negatively associated with gratitude; further, the association between childhood emotional abuse and suicidal ideation was mediated by gratitude. CONCLUSIONS: Findings of this study implied that while exposure to parental emotional abuse might have an adverse impact on the development of gratitude, adolescents' current level of gratitude still exerts its protective effect by directly reducing their suicidal ideation. Gratitude or other resilience factors that might comprise additional mediating mechanisms from childhood emotional abuse to mental health problems in later life is worthy of further investigation.

Supramolecular Assembly of Phosphole Oxide Based Alkynylplatinum(II) 2,6-Bis(N-alkylbenzimidazol-2'-yl)pyridine Complexes-An Interplay of Hydrophobicity and Aromatic π-Surfaces.

A new class of phosphole oxide based alkynylplatinum(II) 2,6-bis(N-alkylbenzimidazol-2'-yl)pyridine (bzimpy) complexes were synthesized and characterized. Their self-assembly was driven by hydrophobic-hydrophobic and π-π stacking interactions. The self-assembly properties were also investigated by UV/Vis absorption spectroscopy, which revealed that the alkyl-chain length of the bzimpy moiety and the π-surface area of the alkynyl ligand have significant influence on the overall self-assembly process. The alkyl-chain length also affected the morphological structures of the aggregates, which were studied by transmission electron microscopy and scanning electron microscopy.