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.

Unsupervised Domain Adaptation for Low-Dose CT Reconstruction via Bayesian Uncertainty Alignment.

Low-dose computed tomography (LDCT) image reconstruction techniques can reduce patient radiation exposure while maintaining acceptable imaging quality. Deep learning (DL) is widely used in this problem, but the performance of testing data (also known as target domain) is often degraded in clinical scenarios due to the variations that were not encountered in training data (also known as source domain). Unsupervised domain adaptation (UDA) of LDCT reconstruction has been proposed to solve this problem through distribution alignment. However, existing UDA methods fail to explore the usage of uncertainty quantification, which is crucial for reliable intelligent medical systems in clinical scenarios with unexpected variations. Moreover, existing direct alignment for different patients would lead to content mismatch issues. To address these issues, we propose to leverage a probabilistic reconstruction framework to conduct a joint discrepancy minimization between source and target domains in both the latent and image spaces. In the latent space, we devise a Bayesian uncertainty alignment to reduce the epistemic gap between the two domains. This approach reduces the uncertainty level of target domain data, making it more likely to render well-reconstructed results on target domains. In the image space, we propose a sharpness-aware distribution alignment (SDA) to achieve a match of second-order information, which can ensure that the reconstructed images from the target domain have similar sharpness to normal-dose CT (NDCT) images from the source domain. Experimental results on two simulated datasets and one clinical low-dose imaging dataset show that our proposed method outperforms other methods in quantitative and visualized performance.

Identification and Characterization of Metastasis-Initiating Cells in ESCC in a Multi-Timepoint Pulmonary Metastasis Mouse Model.

Metastasis is the biggest obstacle to esophageal squamous cell carcinoma (ESCC) treatment. Single-cell RNA sequencing analyses are applied to investigate lung metastatic ESCC cells isolated from pulmonary metastasis mouse model at multiple timepoints to characterize early metastatic microenvironment. A small population of parental KYSE30 cell line (Cluster S) resembling metastasis-initiating cells (MICs) is identified because they survive and colonize at lung metastatic sites. Differential expression profile comparisons between Cluster S and other subpopulations identified a panel of 7 metastasis-initiating signature genes (MIS), including CD44 and TACSTD2, to represent MICs in ESCC. Functional studies demonstrated MICs (CD44high) exhibited significantly enhanced cell survival (resistances to oxidative stress and apoptosis), migration, invasion, stemness, and in vivo lung metastasis capabilities, while bioinformatics analyses revealed enhanced organ development, stress responses, and neuron development, potentially remodel early metastasis microenvironment. Meanwhile, early metastasizing cells demonstrate quasi-epithelial-mesenchymal phenotype to support both invasion and anchorage. Multiplex immunohistochemistry (mIHC) staining of 4 MISs (CD44, S100A14, RHOD, and TACSTD2) in ESCC clinical samples demonstrated differential MIS expression scores (dMISs) predict lymph node metastasis, overall survival, and risk of carcinothrombosis.

Stereotactic Body Radiotherapy and Liver Transplant for Liver Cancer: A Nonrandomized Controlled Trial.

Importance: Whether stereotactic body radiotherapy (SBRT) as a bridge to liver transplant for hepatocellular carcinoma (HCC) is effective and safe is still unknown. Objective: To investigate the feasibility of SBRT before deceased donor liver transplant (DDLT) for previously untreated unresectable HCC. Design, Setting, and Participants: In this phase 2 nonrandomized controlled trial conducted between June 1, 2015, and October 18, 2019, 32 eligible patients within UCSF (University of California, San Francisco) criteria underwent dual-tracer (18F-fluorodeoxyglucose and 11C-acetate [ACC]) positron emission tomography with computed tomography (PET-CT) and magnetic resonance imaging (MRI) with gadoxetate followed by SBRT of 35 to 50 Gy in 5 fractions, and the same imaging afterward while awaiting DDLT. Statistical analysis was performed on an intention-to-treat basis between October 1 and 31, 2023. Intervention: Patients received SBRT followed by DDLT when matched deceased donor grafts were available. Main Outcomes and Measures: Coprimary end points were progression-free survival (PFS) and objective response rates (ORRs) by the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST 1.1), modified RECIST (mRECIST), and PET Response Criteria in Solid Tumors (PERCIST). Secondary end points were local control rate, overall survival (OS), and safety. Results: A total of 32 patients (median age, 59 years [IQR, 54-63 years]; 22 men [68.8%]) with 56 lesions received SBRT. After a median follow-up of 74.6 months (IQR, 40.1-102.9 months), the median PFS was 17.6 months (95% CI, 6.6-28.6 months), and the median OS was 60.5 months (95% CI, 29.7-91.2 months). The 5-year PFS was 39.9% (95% CI, 19.9%-59.9%), and the 5-year OS was 51.3% (95% CI, 31.7%-70.9%). In terms of number of patients, ORRs were 62.5% ([n = 20] 95% CI, 54.2%-68.7%) by RECIST 1.1, 71.9% ([n = 23] 95% CI, 63.7%-79.0%) by mRECIST, and 78.1% ([n = 25] 95% CI, 73.2%-86.7%) by PERCIST. In terms of number of lesions, ORRs were 75.0% ([n = 42] 95% CI, 61.6%-80.8%) by RECIST 1.1, 83.9% ([n = 47] 95% CI, 74.7%-90.6%) by mRECIST, and 87.5% ([n = 49] 95% CI, 81.3%-98.6%) by PERCIST. Twenty patients with 36 lesions received DDLT, of whom 15 patients (75.0%) with 21 lesions (58.3%) exhibited pathologic complete response. Multivariable analyses revealed that pretreatment metabolic tumor volume (MTV) based on ACC (hazard ratio [HR], 1.06 [95% CI, 1.01-1.10]; P = .01) and complete metabolic response (CMR) by PERCIST (HR, 0.31 [95% CI, 0.10-0.96]; P = .04) were associated with PFS, while pretreatment MTV based on ACC (HR, 1.07 [95% CI, 1.03-1.16]; P = .01), total lesion activity based on ACC (HR, 1.01 [95% CI, 1.00-1.02]; P = .02), and CMR by PERCIST (HR, 0.21 [95% CI, 0.07-0.73]; P = .01) were associated with OS. Toxic effects associated with SBRT were reported for 9 patients (28.1%), with 1 grade 3 event. Conclusions and Relevance: This phase 2 nonrandomized controlled trial demonstrated promising survival and safety outcomes of SBRT before DDLT for unresectable HCC. Future randomized clinical trials are warranted.

Learning Robust Shape Regularization for Generalizable Medical Image Segmentation.

Generalizable medical image segmentation enables models to generalize to unseen target domains under domain shift issues. Recent progress demonstrates that the shape of the segmentation objective, with its high consistency and robustness across domains, can serve as a reliable regularization to aid the model for better cross-domain performance, where existing methods typically seek a shared framework to render segmentation maps and shape prior concurrently. However, due to the inherent texture and style preference of modern deep neural networks, the edge or silhouette of the extracted shape will inevitably be undermined by those domain-specific texture and style interferences of medical images under domain shifts. To address this limitation, we devise a novel framework with a separation between the shape regularization and the segmentation map. Specifically, we first customize a novel whitening transform-based probabilistic shape regularization extractor namely WT-PSE to suppress undesirable domain-specific texture and style interferences, leading to more robust and high-quality shape representations. Second, we deliver a Wasserstein distance-guided knowledge distillation scheme to help the WT-PSE to achieve more flexible shape extraction during the inference phase. Finally, by incorporating domain knowledge of medical images, we propose a novel instance-domain whitening transform method to facilitate a more stable training process with improved performance. Experiments demonstrate the performance of our proposed method on both multi-domain and single-domain generalization.

Enhanced mitophagy driven by ADAR1-GLI1 editing supports the self-renewal of cancer stem cells in HCC.

BACKGROUND AND AIMS: Deregulation of adenosine-to-inosine editing by adenosine deaminase acting on RNA 1 (ADAR1) leads to tumor-specific transcriptome diversity with prognostic values for HCC. However, ADAR1 editase-dependent mechanisms governing liver cancer stem cell (LCSC) generation and maintenance have remained elusive. APPROACH AND RESULTS: RNA-seq profiling identified ADAR1-responsive recoding editing events in HCC and showed editing frequency of GLI1 , rather than transcript abundance was clinically relevant. Functional differences in LCSC self-renewal and tumor aggressiveness between wild-type (GLI1 wt ) and edited GLI1 (GLI1 edit ) were elucidated. We showed that overediting of GLI1 induced an arginine-to-glycine (R701G) substitution, augmenting tumor-initiating potential and exhibiting a more aggressive phenotype. GLI1 R701G harbored weak affinity to SUFU, which in turn, promoted its cytoplasmic-to-nuclear translocation to support LCSC self-renewal by increased pluripotency gene expression. Moreover, editing predisposed to stabilize GLI1 by abrogating ß-TrCP-GLI1 interaction. Integrative analysis of single-cell transcriptome further revealed hyperactivated mitophagy in ADAR1-enriched LCSCs. GLI1 editing promoted a metabolic switch to oxidative phosphorylation to control stress and stem-like state through PINK1-Parkin-mediated mitophagy in HCC, thereby conferring exclusive metastatic and sorafenib-resistant capacities. CONCLUSIONS: Our findings demonstrate a novel role of ADAR1 as an active regulator for LCSCs properties through editing GLI1 in the highly heterogeneous HCC.

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.

ENOX2 inhibition enhances infiltration of effector memory T-cell and mediates response to chemotherapy in immune-quiescent nasopharyngeal carcinoma.

INTRODUCTION: The immunosuppressive tumor microenvironment is a major barrier for chemotherapy. Different chemosensitization approaches to reinstate immunological surveillance for cancers that are immune quiescent at the outset, have thus been devised. Cancer-specific ENOX2 expression is correlated with abnormal cell growth and has been proposed as a cellular target for anti-cancer activity. However, the potential effects of ENOX2 on the interaction between immune system and tumor cells remain elusive. OBJECTIVES: To understand the mechanisms by which tumor-intrinsic ENOX2-mediated alterations in anti-tumor activity of T-cells and response to chemotherapy. METHODS: In situ multiplexed immunohistochemistry with single cell and bulk RNA sequencing data from nasopharyngeal carcinoma (NPC) human tissues were used to define tumor phenotypes. Two NPC cell lines, with distinct ENOX2 expression, were used in a co-culture platform to study tumor-immune interactions between cancer cells/spheroids and T-cells. The effect of cisplatin treatment with ENOX2 inhibition by idronoxil (IDX) were tested in vitro and in vivo. Multi-parametric flow cytometry was used to characterize T-cell infiltrates in an NPC tumor humanized mouse model treated with combined treatment. RESULTS: NPC predominantly displayed an immune-excluded profile. This "cold-phenotype" was shown to exhibit higher ENOX2 expression and was associate with poorer progression-free survival (PFS). The therapeutic combination of IDX with cisplatin was effective in promoting CD8+ effector memory T cell (Tem) differentiation and mobilization. This Tem signature was highly cytotoxic, with Tem-mediated preferential lysis of higher ENOX2-expressing NPC cells. A combination-treated humanized mouse model showing dramatic shrinkage in tumors, were intra-tumoral Tem-enriched. CONCLUSION: Tumor-intrinsic ENOX2 expression is associated with tumor phenotype and PFS in NPC. Targeting ENOX2 with IDX and cisplatin impose qualitative control of T-cell response by preferentially increasing immune cells infiltration, Tem differentiation and tumor suppression. We suggest that ENOX2 inhibition may be a promising therapeutic strategy to enhance the effects of chemotherapy.

Single-Cell Secretion Analysis via Microfluidic Cell Membrane Immunosorbent Assay for Immune Profiling.

Single-cell multiplexed phenotypic analysis expands the biomarkers for diagnosis, heralding a new era of precision medicine. Cell secretions are the primary measures of immune function, but single-cell screening remains challenging. Here, a novel cell membrane-based assay was developed using cholesterol-linked antibodies (CLAbs), integrating immunosorbent assays and droplet microfluidics to develop a flexible high-throughput single-cell secretion assay for multiplexed phenotyping. CLAb-grafted single cells were encapsulated in water-in-oil droplets to capture their own secretions. Subsequently, the cells were extracted from droplets for fluorescence labeling and screening. Multiple secretions and surface proteins were simultaneously measured from single cells by flow cytometry. To validate the approach, THP-1 cells, THP-1-derived M1 macrophages, and dendritic cells were assayed, indicating the differentiation efficiency of THP-1 cells under different chemical stimulations. Moreover, peripheral blood mononuclear cells from healthy donors under various stimuli showed varied active immune cell populations (6.62-47.14%). The peripheral blood mononuclear cells (PBMCs) of nasopharyngeal carcinoma patients were analyzed to identify a higher percentage of actively cytokine-secreted single cells in the basal state (2.82 ± 1.48%), compared with that in the health donors (0.70 ± 0.29%).

Radiologic extranodal extension for nodal staging in nasopharyngeal carcinoma.

PURPOSE: Extranodal extension (ENE) has the potential to add value to the current nodal staging system (N8th) for predicting outcome in nasopharyngeal carcinoma (NPC). This study aimed to incorporate ENE, as well as cervical nodal necrosis (CNN) to the current stage N3 and evaluated their impact on outcome prediction. The findings were validated on an external cohort. METHODS & MATERIALS: Pre-treatment MRI of 750 patients from the internal cohort were retrospectively reviewed. Predictive values of six modified nodal staging systems that incorporated four patterns of ENE and two patterns of CNN to the current stage N3 for disease-free survival (DFS) were compared with that of N8th using multivariate cox-regression and concordance statistics in the internal cohort. Performance of stage N3 for predicting disease recurrence was calculated. An external cohort of 179 patients was used to validate the findings. RESULTS: Incorporation of advanced ENE, which infiltrates into adjacent muscle/skin/salivary glands outperformed the other five modifications for predicting outcomes (p < 0.01) and achieved a significantly higher c-index for 5-year DFS (0.69 vs 0.72) (p < 0.01) when compared with that of N8th staging system. By adding advanced ENE to the current N3 increased the sensitivity for predicting disease recurrence from 22.4 % to 47.1 %. The finding was validated in the external cohort (5-year DFS 0.65 vs. 0.72, p < 0.01; sensitivity of stage N3 increased from 14.0 % to 41.9 % for disease recurrence). CONCLUSION: Results from two centre cohorts confirmed that the radiological advanced ENE should be considered as a criterion for stage N3 disease in NPC.

Complications of Central Venous Access Devices Used in Palliative Care Settings for Terminally Ill Cancer Patients: A Systematic Review and Meta-Analysis.

(1) Background: Central venous access devices (CVADs) have been commonly employed during various courses of anticancer treatment. Currently, there are a few types of clinically available CVADs, which are associated with short-term and long-term complications. However, little is known about the complication rates when CVADs are used only in palliative care settings. We therefore performed a systematic review and meta-analysis of all the published literature to evaluate the complication rates of CVADs in this clinical setting. (2) Methods: A systematic review and meta-analysis were conducted to identify publications from PubMed/MEDLINE, Embase (Ovid), Scopus, Cochrane Library, CINAHL, Google Scholar, and trial registries. Publications reporting the complication rates of PICCs, central lines, and PORTs in palliative settings for terminally ill cancer patients were included, while those on the use of systemic anticancer therapy and peripheral venous catheters were excluded. The outcome measures included overall complication rate, rate of catheter-related bloodstream infection (CRBSI), and rate of thromboembolism (TE). This systematic review was registered with PROSPERO (CRD42023404489). (3) Results: Five publications with 327 patients were analyzed, including four studies on PICCs and one study on central lines. No studies on PORTs were eligible for analysis. The overall complication rate for PICCs (pooled estimate 7.02%, 95% CI 0.27-19.10) was higher than that for central lines (1.44%, 95% CI 0.30-4.14, p = 0.002). The risk of CRBSI with PICCs (2.03%, 95% CI 0.00-9.62) was also higher than that with central lines (0.96%, 95% CI 0.12-3.41, p = 0.046). PICCs also had a trend of a higher risk of TE (2.10%, 95% CI 0.00-12.22) compared to central lines (0.48%, 95% CI 0.01-2.64, p = 0.061). (4) Conclusions: PICCs for palliative cancer care were found to have greater complications than central lines. This might aid in the formulation of future recommendation guidelines on the choice of CVAD in this setting.

Nasopharynx Battlefield: Cellular Immune Responses Mediated by Midkine in Nasopharyngeal Carcinoma and COVID-19.

Clinical evidence suggests that the severe respiratory illness coronavirus disease 2019 (COVID-19) is often associated with a cytokine storm that results in dysregulated immune responses. Prolonged COVID-19 positivity is thought to disproportionately affect cancer patients. With COVID-19 disrupting the delivery of cancer care, it is crucial to gain momentum and awareness of the mechanistic intersection between these two diseases. This review discusses the role of the cytokine midkine (MK) as an immunomodulator in patients with COVID-19 and nasopharyngeal carcinoma (NPC), both of which affect the nasal cavity. We conducted a review and analysis of immunocellular similarities and differences based on clinical studies, research articles, and published transcriptomic datasets. We specifically focused on ligand-receptor pairs that could be used to infer intercellular communication, as well as the current medications used for each disease, including NPC patients who have contracted COVID-19. Based on our findings, we recommend close monitoring of the MK axis to maintain the desirable effects of therapeutic regimens in fighting both NPC and COVID-19 infections.

Safety, Tolerability, and Antitumor Activity of Zipalertinib Among Patients With Non-Small-Cell Lung Cancer Harboring Epidermal Growth Factor Receptor Exon 20 Insertions.

PURPOSE: Although several agents targeting epidermal growth factor receptor (EGFR) exon 20 insertions (ex20ins) have recently been approved by the US Food and Drug Administration, toxicities related to the inhibition of wild-type (WT) EGFR are common with these agents and affect overall tolerability. Zipalertinib (CLN-081, TAS6417) is an oral EGFR tyrosine kinase inhibitor (TKI) with a novel pyrrolopyrimidine scaffold leading to enhanced selectivity for EGFR ex20ins-mutant versus WT EGFR with potent inhibition of cell growth in EGFR ex20ins-positive cell lines. METHODS: This phase 1/2a study of zipalertinib enrolled patients with recurrent or metastatic EGFR ex20ins-mutant non-small-cell lung cancer (NSCLC) previously treated with platinum-based chemotherapy. RESULTS: Seventy-three patients were treated with zipalertinib at dose levels including 30, 45, 65, 100, and 150 mg orally twice a day. Patients were predominantly female (56%), had a median age of 64 years, and were heavily pretreated (median previous systemic therapies 2, range 1-9). Thirty six percent of patients had received previous non-ex20ins EGFR TKIs and 3/73 (4.1%) patients received previous EGFR ex20ins TKIs. The most frequently reported treatment-related adverse events of any grade included rash (80%), paronychia (32%), diarrhea (30%), and fatigue (21%). No cases of grade 3 or higher drug-related rash or diarrhea were observed at 100 mg twice a day or below. Objective responses occurred across all zipalertinib dose levels tested, with confirmed partial response (PR) observed in 28/73 (38.4%) response-evaluable patients. Confirmed PRs were seen in 16/39 (41%) response-evaluable patients at the dose of 100 mg twice a day. CONCLUSION: Zipalertinib has encouraging preliminary antitumor activity in heavily pretreated patients with EGFR ex20ins-mutant NSCLC, with an acceptable safety profile, including low frequency of high-grade diarrhea and rash.

Functions of double-negative B cells in autoimmune diseases, infections, and cancers.

Most mature B cells can be divided into four subtypes based on the expression of the surface markers IgD and CD27: IgD+ CD27- naïve B cells, IgD+ CD27+ unswitched memory B cells, IgD- CD27+ switched memory B cells, and IgD- CD27- double-negative (DN) B cells. Despite their small population size in normal peripheral blood, DN B cells play integral roles in various diseases. For example, they generate autoimmunity in autoimmune conditions, while these cells may generate both autoimmune and antipathogenic responses in COVID-19, or act in a purely antipathogenic capacity in malaria. Recently, DN B cells have been identified in nasopharyngeal carcinoma and non-small-cell lung cancers, where they may play an immunosuppressive role. The distinct functions that DN B cells play in different diseases suggest that they are a heterogeneous B-cell population. Therefore, further study of the mechanisms underlying the involvement of DN B cells in these diseases is essential for understanding their pathogenesis and the development of therapeutic strategies. Further research is thus warranted to characterize the DN B-cell population in detail.

Explainable machine learning via intra-tumoral radiomics feature mapping for patient stratification in adjuvant chemotherapy for locoregionally advanced nasopharyngeal carcinoma.

PURPOSE: This study aimed to discover intra-tumor heterogeneity signature and validate its predictive value for adjuvant chemotherapy (ACT) following concurrent chemoradiotherapy (CCRT) in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). MATERIALS AND METHODS: 397 LA-NPC patients were retrospectively enrolled. Pre-treatment contrast-enhanced T1-weighted (CET1-w) MR images, clinical variables, and follow-up were retrospectively collected. We identified single predictive radiomic feature from primary gross tumor volume (GTVnp) and defined predicted subvolume by calculating voxel-wised feature mapping and within GTVnp. We independently validate predictive value of identified feature and associated predicted subvolume. RESULTS: Only one radiomic feature, gldm_DependenceVariance in 3 mm-sigma LoG-filtered image, was discovered as a signature. In the high-risk group determined by the signature, patients received CCRT + ACT achieved 3-year disease free survival (DFS) rate of 90% versus 57% (HR, 0.20; 95%CI, 0.05-0.94; P = 0.007) for CCRT alone. The multivariate analysis showed patients receiving CCRT + ACT had a HR of 0.21 (95%CI: 0.06-0.68, P = 0.009) for DFS compared to those receiving CCRT alone. The predictive value can also be generalized to the subvolume with multivariate HR of 0.27 (P = 0.017) for DFS. CONCLUSION: The signature with its heterogeneity mapping could be a reliable and explainable ACT decision-making tool in clinical practice.

Consensus Statements on Precision Oncology in the China Greater Bay Area.

BACKGROUND: Next-generation sequencing comprehensive genomic panels (NGS CGPs) have enabled the delivery of tailor-made therapeutic approaches to improve survival outcomes in patients with cancer. Within the China Greater Bay Area (GBA), territorial differences in clinical practices and health care systems and strengthening collaboration warrant a regional consensus to consolidate the development and integration of precision oncology (PO). Therefore, the Precision Oncology Working Group (POWG) formulated standardized principles for the clinical application of molecular profiling, interpretation of genomic alterations, and alignment of actionable mutations with sequence-directed therapy to deliver clinical services of excellence and evidence-based care to patients with cancer in the China GBA. METHODS: Thirty experts used a modified Delphi method. The evidence extracted to support the statements was graded according to the GRADE system and reported according to the Revised Standards for Quality Improvement Reporting Excellence guidelines, version 2.0. RESULTS: The POWG reached consensus in six key statements: harmonization of reporting and quality assurance of NGS; molecular tumor board and clinical decision support systems for PO; education and training; research and real-world data collection, patient engagement, regulations, and financial reimbursement of PO treatment strategies; and clinical recommendations and implementation of PO in clinical practice. CONCLUSION: POWG consensus statements standardize the clinical application of NGS CGPs, streamline the interpretation of clinically significant genomic alterations, and align actionable mutations with sequence-directed therapies. The POWG consensus statements may harmonize the utility and delivery of PO in China's GBA.

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.

Predictive factors of delayed viral clearance of asymptomatic Omicron-related COVID-19 screened positive in patients with cancer receiving active anticancer treatment.

OBJECTIVES: We sought to identify the predictors of delayed viral clearance in patients with cancer with asymptomatic COVID-19 when the SARS-CoV-2 Omicron variants prevailed in Hong Kong. METHODS: All patients with cancer who were attending radiation therapy for head and neck malignancies or systemic anticancer therapy saved their deep throat saliva or nasopharyngeal swabs at least twice weekly for SARS-CoV-2 screening between January 1 and April 30, 2022. The multivariate analyses identified predictors of delayed viral clearance (or slow recovery), defined as >21 days for the cycle threshold values rising to ≥30 or undetectable in two consecutive samples saved within 72 hours. Three machine learning algorithms evaluated the prediction performance of the predictors. RESULTS: A total of 200 (15%) of 1309 patients tested positive for SARS-CoV-2. Age >65 years (P = 0.036), male sex (P = 0.003), high Charlson comorbidity index (P = 0.042), lung cancer (P = 0.018), immune checkpoint inhibitor (P = 0.036), and receipt of one or no dose of COVID-19 vaccine (P = 0.003) were significant predictors. The three machine learning algorithms revealed that the mean ± SD area-under-the-curve values predicting delayed viral clearance with the cut-off cycle threshold value ≥30 was 0.72 ± 0.11. CONCLUSION: We identified subgroups with delayed viral clearance that may benefit from targeted interventions.

Prognostic MicroRNA Fingerprints Predict Recurrence of Early-Stage Hepatocellular Carcinoma Following Hepatectomy.

Purpose: This study aims to develop liquid biopsy assays for early HCC diagnosis and prognosis. Methods: Twenty-three microRNAs were first consolidated as a panel (HCCseek-23 panel) based on their reported functions in HCC development. Serum samples were collected from 103 early-stage HCC patients before and after hepatectomy. Quantitative PCR and machine learning random forest models were applied to develop diagnostic and prognostic models. Results: For HCC diagnosis, HCCseek-23 panel demonstrated 81% sensitivity and 83% specificity for identifying HCC in the early-stage; it showed 93% sensitivity for identifying alpha-fetoprotein (AFP)-negative HCC. For HCC prognosis, the differential expressions of 8 microRNAs (HCCseek-8 panel: miR-145, miR-148a, miR-150, miR-221, miR-223, miR-23a, miR-374a, and miR-424) were significantly associated with disease-free survival (DFS) (Log-rank test p-value = 0.001). Further model improvement using these HCCseek-8 panel in combination with serum biomarkers (i.e. AFP, ALT, and AST) demonstrated a significant association with DFS (Log-rank p-value = 0.011 and Cox proportional hazards analyses p-value = 0.002). Conclusion: To the best of our knowledge, this is the first report to integrate circulating miRNAs, AST, ALT, AFP, and machine learning for predicting DFS in early HCC patients undergoing hepatectomy. In this setting, HCCSeek-23 panel is a promising circulating microRNA assay for diagnosis, while HCCSeek-8 panel is promising for prognosis to identify early HCC recurrence.

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.