Shuhsin Liu

Dr. Shuhsin Liu


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 December 2020 in Diagnostics
Verified
Journal Article
Open access
PDF file
KLKun-Han Lue
Kun-Han Lue
YWYi-Feng Wu
Yi-Feng Wu
HLHsin-Hon Lin
Hsin-Hon Lin
THTsung-Cheng Hsieh
Tsung-Cheng Hsieh
SLShuhsin Liu
Shuhsin Liu
YCYu-Hung Chen
Yu-Hung Chen
This study investigates whether baseline 18F-FDG PET radiomic features can predict survival outcomes in patients with diffuse large B-cell lymphoma (DLBCL). We retrospectively enrolled 83 patients diagnosed with DLBCL who underwent 18F-FDG PET scans before treatment. The patients were divided into the training cohort (n = 58) and the validation cohort (n = 25). Eighty radiomic features were extracted from the PET images for each patient. Least absolute shrinkage and selection operator regression were used to reduce the dimensionality within radiomic features. Cox proportional hazards model was used to determine the prognostic factors for progression-free survival (PFS) and overall survival (OS). A prognostic stratification model was built in the training cohort and validated in the validation cohort using Kaplan–Meier survival analysis. In the training cohort, run length non-uniformity (RLN), extracted from a gray level run length matrix (GLRLM), was independently associated with PFS (hazard ratio (HR) = 15.7, p = 0.007) and OS (HR = 8.64, p = 0.040). The International Prognostic Index was an independent prognostic factor for OS (HR = 2.63, p = 0.049). A prognostic stratification model was devised based on both risk factors, which allowed identification of three risk groups for PFS and OS in the training (p < 0.001 and p < 0.001) and validation (p < 0.001 and p = 0.020) cohorts. Our results indicate that the baseline 18F-FDG PET radiomic feature, RLNGLRLM, is an independent prognostic factor for survival outcomes. Furthermore, we propose a prognostic stratification model that may enable tailored therapeutic strategies for patients with DLBCL.

9 June 2021 in Diagnostics
Verified
Journal Article
Open access
PDF file
YCYu-Hung Chen
Yu-Hung Chen
SCSung-Chao Chu
Sung-Chao Chu
LWLing-Yi Wang
Ling-Yi Wang
TWTso-Fu Wang
Tso-Fu Wang
KLKun-Han Lue
Kun-Han Lue
SCSheng-Chieh Chan
Sheng-Chieh Chan
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.

22 May 2020 in Clinical Nuclear Medicine
Verified
Journal Article
Closed access
YCYu-Hung Chen
Yu-Hung Chen
YHYung-Hsiang Hsu
Yung-Hsiang Hsu
HCHwa-Tsung Chen
Hwa-Tsung Chen
BCBee-Song Chang
Bee-Song Chang
SLShuhsin Liu
Shuhsin Liu
99mTc-MIBI has long been used to localize hyperfunctioning parathyroid tissue in patients with hyperparathyroidism. This tracer can also concentrate in various neoplastic tissues including prostate adenocarcinoma. We herein report a case with parathyroid hormone-secreting metastatic prostate cancer mimicking an ectopic parathyroid adenoma on the 99mTc-MIBI scan. We conclude that metastatic prostate cancer should be included as one of the differential diagnoses when interpreting 99mTc-MIBI scan.

1 April 2003 in The Kaohsiung Journal of Medical Sciences
Verified
Journal Article
Open access
SLShuhsin Liu
Shuhsin Liu
SCSheng‐Chieh Chan
Sheng‐Chieh Chan
TYTzu‐Chen Yen
Tzu‐Chen Yen
SJShih‐Ming Jung
Shih‐Ming Jung
Gallium-67 scanning is a useful tool to search for infectious foci and malignant tumors. Multiple myeloma is one clinical indication for gallium-67 tumor survey. Here, we report a rare case of diffuse multiple cutaneous plasmacytomas from recurrent multiple myeloma, demonstrated by whole-body gallium-67 scan.

17 February 2026 in Diagnostics
Verified
Journal Article
Open access
PDF file
CTChang-Shen Tseng
Chang-Shen Tseng
YCYu-Hung Chen
Yu-Hung Chen
CHChing-Chun Ho
Ching-Chun Ho
KSKuei-Ying Su
Kuei-Ying Su
SCSung-Chao Chu
Sung-Chao Chu
SLShuhsin Liu
Shuhsin Liu
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.

26 March 2026 in Diagnostics
Verified
Journal Article
Open access
PDF file
STSze Ian Tan
Sze Ian Tan
KLKun-Han Lue
Kun-Han Lue
YCYu-Hung Chen
Yu-Hung Chen
SCSung-Chao Chu
Sung-Chao Chu
CLChih-Bin Lin
Chih-Bin Lin
SLShuhsin Liu
Shuhsin Liu
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.