Sung-Chao Chu

Background/Objectives: Novel hotspot displacement radiomic features (normalized hotspot-to-centroid distance [NHOC]/normalized hotspot-to-perimeter distance [NHOP]) are robust against image resampling and spatial resolution variations. However, their reproducibility under respiratory motion remains unvalidated. This study aimed to evaluate the reproducibility, reliability, and survival prognostic value of NHOC/NHOP features in thoracic ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) images with and without respiratory motion correction and to determine whether these features maintain stability and predictive performance for overall survival (OS) compared with respiratory-stable reference features. Methods: We analyzed 138 patients (203 lesions) who underwent ¹⁸F-FDG PET/CT with and without data-driven respiratory gating. Reproducibility and reliability were assessed using the coefficient of variation (CoV) and intraclass correlation coefficient (ICC), respectively. OS prediction was evaluated using Cox regression and concordance index (c-index) analyses. Results: Except for NHOCmax and NHOPpeak, which showed ICC values of 0.782 and 0.93, respectively, the novel morphological features generally exhibited poor reproducibility and moderate reliability (CoV > 20% and ICC < 0.75). In contrast, reference features (entropy-based and sphericity) demonstrated excellent robustness. Motion-corrected NHOCmax showed significant OS prediction for both spatially resampled and non-resampled images. No significant differences in c-indices were observed between motion-corrected and non-corrected features. Conclusions: The marked sensitivity of novel hotspot-displacement features to respiratory motion substantially limits their clinical applicability in thoracic disease. To ensure reproducibility and generalizability in future research, prioritizing inherently robust radiomic parameters, such as entropy-based features, is strongly recommended.

Fluorine-18 fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) is widely used to evaluate patients with cancer and to detect various inflammatory processes. Here, we report a rare case of a 53-year-old woman with breast cancer who developed generalized pain, weakness, rash, and edema over the trunk after the first cycle of neoadjuvant pembrolizumab and cytotoxic chemotherapeutic agents. ¹⁸F-FDG PET revealed diffusely increased uptake in the muscles without skeletal or visceral metastasis, aiding in the diagnosis of paraneoplastic and pembrolizumab-associated myositis and subsequent monitoring. This case underscores the value of ¹⁸F-FDG PET in differentiating myositis from tumor progression and monitoring treatment response in such cases.

Hormone receptor-positive metastatic breast cancer remains a major clinical burden and is characterized by sequential endocrine resistance over the disease course. In 2023, the Taiwan Breast Cancer Society (TBCS) published an expert consensus to support real-world decision-making in Taiwan. Subsequently, rapid advances in biomarker-informed strategies (e.g., estrogen receptor 1 and PI3K/AKT pathway alterations), endocrine partners, estrogen receptor (ER)-targeting agents (including oral selective ER degraders and emerging protein degraders), and the expanding role of antibody-drug conjugates based on human epidermal growth factor receptor 2 expression categories have materially increased the complexity of treatment selection and sequencing. Therefore, TBCS convened an expert panel to update the previous consensus while preserving its foundational framework and eight-chapter structure: risk evaluation and biomarker testing (I/II), first-line treatment selection (I/II), second-line treatment selection (I/II), and treatment options other than endocrine-based approaches (I/II). A multidisciplinary panel conducted a systematic literature review and iterative discussions using a modified Delphi process to identify the key clinical questions, update and refine statements where new evidence was practice-changing, and maintain continuity with the 2023 Consensus. The panel formulated updated recommendations, assigned levels of evidence and strengths of recommendations, and the key updates were integrated into practical treatment algorithms reflecting Taiwan's practice considerations. This updated consensus provides a continuity-based, yet evidence-responsive framework to facilitate the integration of emerging therapies into clinical practice in Taiwan and the Asia-Pacific region.

Currently, the second most commonly diagnosed cancer in the world is lung cancer, and 85% of cases are non-small cell lung cancer (NSCLC). With growing knowledge of oncogene drivers and cancer immunology, several novel therapeutics have emerged to improve the prognostic outcomes of NSCLC. However, treatment outcomes remain diverse, and an accurate tool to achieve precision medicine is an unmet need. Radiomics, a method of extracting medical imaging features, is promising for precision medicine. Among all radiomic tools, ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET)-based radiomics provides distinct information on glycolytic activity and heterogeneity. In this review, we collected relevant literature from PubMed and summarized the various applications of ¹⁸F-FDG PET-derived radiomics in improving the detection of metastasis, subtyping histopathologies, characterizing driver mutations, assessing treatment response, and evaluating survival outcomes of NSCLC. Furthermore, we reviewed the values of ¹⁸F-FDG PET-based deep learning. Finally, several challenges and caveats exist in the implementation of ¹⁸F-FDG PET-based radiomics for NSCLC. Implementing ¹⁸F-FDG PET-based radiomics in clinical practice is necessary to ensure reproducibility. Moreover, basic studies elucidating the underlying biological significance of ¹⁸F-FDG PET-based radiomics are lacking. Current inadequacies hamper immediate clinical adoption; however, radiomic studies are progressively addressing these issues. ¹⁸F-FDG PET-based radiomics remains an invaluable and indispensable aspect of precision medicine for NSCLC.

Background: In recent years, advancements in cancer treatment have enabled cancer cell inhibition, leading to improved patient outcomes. However, the side effects of chemotherapy, especially leukopenia, impact patients’ ability to tolerate their treatments and affect their quality of life. Traditional Chinese medicine is thought to provide complementary cancer treatment to improve the quality of life and prolong survival time among patients with cancer. Objective: This study aims to evaluate the effectiveness of Chinese herbal medicine (CHM) as a complementary treatment for neutropenia prevention and immunity modulation during chemotherapy in patients with breast cancer. Methods: We will conduct a real-world pragmatic clinical trial to evaluate the effectiveness of CHM as a supplementary therapy to prevent neutropenia in patients with breast cancer undergoing chemotherapy. Patients will be classified into CHM or non-CHM groups based on whether they received CHM during chemotherapy. Using generalized estimating equations or repeated measures ANOVA, we will assess differences in white blood cell counts, absolute neutrophil counts, immune cells, and programmed cell death protein 1 (PD-1) expression levels between the 2 groups. Results: This study was approved by the research ethics committee of Hualien Tzu Chi Hospital (IRB 110-168-A). The enrollment process began in September 2021 and will stop in December 2024. A total of 140 patients will be recruited. Data cleaning and analysis are expected to finish in the middle of 2025. Conclusions: Traditional Chinese medicine is the most commonly used complementary medicine, and it has been reported to significantly alleviate chemotherapy-related side effects. This study’s findings may contribute to developing effective interventions targeting chemotherapy-related neutropenia among patients with breast cancer in clinical practice. Trial Registration: International Traditional Medicine Clinical Trial Registry ITMCTR2023000054; https://tinyurl.com/yc353hes International Registered Report Identifier (IRRID): DERR1-10.2196/55662

Lethal toxin (LT) is the critical virulence factor of Bacillus anthracis, the causative agent of anthrax. One common symptom observed in patients with anthrax is thrombocytopenia, which has also been observed in mice injected with LT. Our previous study demonstrated that LT induces thrombocytopenia by suppressing megakaryopoiesis, but the precise molecular mechanisms behind this phenomenon remain unknown. In this study, we utilized 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced megakaryocytic differentiation in human erythroleukemia (HEL) cells to identify genes involved in LT-induced megakaryocytic suppression. Through cDNA microarray analysis, we identified Dachshund homolog 1 (DACH1) as a gene that was upregulated upon TPA treatment but downregulated in the presence of TPA and LT, purified from the culture supernatants of B. anthracis. To investigate the function of DACH1 in megakaryocytic differentiation, we employed short hairpin RNA technology to knock down DACH1 expression in HEL cells and assessed its effect on differentiation. Our data revealed that the knockdown of DACH1 expression suppressed megakaryocytic differentiation, particularly in polyploidization. We demonstrated that one mechanism by which B. anthracis LT induces suppression of polyploidization in HEL cells is through the cleavage of MEK1/2. This cleavage results in the downregulation of the ERK signaling pathway, thereby suppressing DACH1 gene expression and inhibiting polyploidization. Additionally, we found that known megakaryopoiesis-related genes, such as FOSB, ZFP36L1, RUNX1, FLI1, AHR, and GFI1B genes may be positively regulated by DACH1. Furthermore, we observed an upregulation of DACH1 during in vitro differentiation of CD34–megakaryocytes and downregulation of DACH1 in patients with thrombocytopenia. In summary, our findings shed light on one of the molecular mechanisms behind LT-induced thrombocytopenia and unveil a previously unknown role for DACH1 in megakaryopoiesis.

BACKGROUND In recent years, advancements in cancer treatment have enabled cancer cell inhibition, leading to improved patient outcomes. However, the side effects of chemotherapy, especially leukopenia, impact patients’ ability to tolerate their treatments and affect their quality of life. Traditional Chinese medicine is thought to provide complementary cancer treatment to improve the quality of life and prolong survival time among patients with cancer. OBJECTIVE This study aims to evaluate the effectiveness of Chinese herbal medicine (CHM) as a complementary treatment for neutropenia prevention and immunity modulation during chemotherapy in patients with breast cancer. METHODS We will conduct a real-world pragmatic clinical trial to evaluate the effectiveness of CHM as a supplementary therapy to prevent neutropenia in patients with breast cancer undergoing chemotherapy. Patients will be classified into CHM or non-CHM groups based on whether they received CHM during chemotherapy. Using generalized estimating equations or repeated measures ANOVA, we will assess differences in white blood cell counts, absolute neutrophil counts, immune cells, and programmed cell death protein 1 (PD-1) expression levels between the 2 groups. RESULTS This study was approved by the research ethics committee of Hualien Tzu Chi Hospital (IRB 110-168-A). The enrollment process began in September 2021 and will stop in December 2024. A total of 140 patients will be recruited. Data cleaning and analysis are expected to finish in the middle of 2025. CONCLUSIONS Traditional Chinese medicine is the most commonly used complementary medicine, and it has been reported to significantly alleviate chemotherapy-related side effects. This study’s findings may contribute to developing effective interventions targeting chemotherapy-related neutropenia among patients with breast cancer in clinical practice. CLINICALTRIAL International Traditional Medicine Clinical Trial Registry ITMCTR2023000054; https://tinyurl.com/yc353hes INTERNATIONAL REGISTERED REPORT DERR1-10.2196/55662

Radiogenomic heterogeneity features in ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) have become popular in non-small cell lung cancer (NSCLC) research. However, the reliabilities of genomic heterogeneity features and of PET-based glycolytic features in different image matrix sizes have yet to be thoroughly tested. We conducted a prospective study with 46 NSCLC patients to assess the intra-class correlation coefficient (ICC) of different genomic heterogeneity features. We also tested the ICC of PET-based heterogeneity features from different image matrix sizes. The association of radiogenomic features with clinical data was also examined. The entropy-based genomic heterogeneity feature (ICC = 0.736) is more reliable than the median-based feature (ICC = −0.416). The PET-based glycolytic entropy was insensitive to image matrix size change (ICC = 0.958) and remained reliable in tumors with a metabolic volume of p = 0.011). We conclude that the entropy-based radiogenomic features are reliable and may serve as ideal biomarkers for research and further clinical use for NSCLC.

Objective We investigated whether glycolytic heterogeneity correlated with histopathology, and further stratified the survival outcomes pertaining to resectable lung adenocarcinoma. Methods We retrospectively analyzed the ¹⁸F-fluorodeoxyglucose positron emission tomography-derived entropy and histopathology from 128 patients who had undergone curative surgery for lung adenocarcinoma. Disease-free survival (DFS) and overall survival (OS) were analyzed using univariate and multivariate Cox regression models. Independent predictors were used to construct survival prediction models. Results Entropy significantly correlated with histopathology, including tumor grades, lympho-vascular invasion, and visceral pleural invasion. Furthermore, entropy was an independent predictor of unfavorable DFS (p = 0.031) and OS (p = 0.004), while pathological nodal metastasis independently predicted DFS (p = 0.009). Our entropy-based models outperformed the traditional staging system (c-index = 0.694 versus 0.636, p = 0.010 for DFS; c-index = 0.704 versus 0.630, p = 0.233 for OS). The models provided further survival stratification in subgroups comprising different tumor grades (DFS: HR = 2.065, 1.315, and 1.408 for grade 1–3, p = 0.004, 0.001, and 0.039, respectively; OS: HR = 25.557, 6.484, and 2.570, for grade 1–3, p = 0.006, < 0.001, and = 0.224, respectively). Conclusion The glycolytic heterogeneity portrayed by entropy is associated with aggressive histopathological characteristics. The proposed entropy-based models may provide more sophisticated survival stratification in addition to histopathology and may enable personalized treatment strategies for resectable lung cancer.

We investigated whether the combination of primary tumor and nodal ¹⁸F-FDG PET parameters predict survival outcomes in patients with nodal metastatic non-small cell lung cancer (NSCLC) without distant metastasis. We retrospectively extracted pre-treatment ¹⁸F-FDG PET parameters from 89 nodal-positive NSCLC patients (stage IIB–IIIC). The Cox proportional hazard model was used to identify independent prognosticators of overall survival (OS) and progression-free survival (PFS). We devised survival stratification models based on the independent prognosticators and compared the model to the American Joint Committee on Cancer (AJCC) staging system using Harrell’s concordance index (c-index). Our results demonstrated that total TLG (the combination of primary tumor and nodal total lesion glycolysis) and age were independent risk factors for unfavorable OS (p < 0.001 and p = 0.001) and PFS (both p < 0.001), while the Eastern Cooperative Oncology Group scale independently predicted poor OS (p = 0.022). Our models based on the independent prognosticators outperformed the AJCC staging system (c-index = 0.732 versus 0.544 for OS and c-index = 0.672 versus 0.521 for PFS, both p < 0.001). Our results indicate that incorporating total TLG with clinical factors may refine risk stratification in nodal metastatic NSCLC patients and may facilitate tailored therapeutic strategies in this patient group.