4.7 Article

Pre-treatment amide proton transfer imaging predicts treatment outcome in nasopharyngeal carcinoma

Journal

EUROPEAN RADIOLOGY
Volume 30, Issue 11, Pages 6339-6347

Publisher

SPRINGER
DOI: 10.1007/s00330-020-06985-5

Keywords

Amide proton transfer; Head and neck cancer; Nasopharyngeal carcinoma; Disease-free survival; Treatment outcome

Funding

  1. Research Grants council of the Hong Kong Special Administrative Region, China [CUHK141070/14, SEG_CUHK02]

Ask authors/readers for more resources

Objective To investigate the value of pre-treatment amide proton transfer-weighted (APTw) imaging for predicting survival of patients with nasopharyngeal carcinoma (NPC). Materials and methods Pre-treatment APTw imaging was performed in 77 NPC patients and the mean, 90th percentile, skewness, and kurtosis of APT asymmetry (APT(mean), APT(90), APT(skewness), and APT(kurtosis), respectively) were obtained from the primary tumor. Associations of APTw parameters with locoregional relapse-free survival (LRRFS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) after 2 years were assessed by univariable Cox regression analysis and significant APTw parameters, together with age, sex, treatment, and stage as confounding variables, were added to the multivariable model. Kaplan-Meier analysis was used to determine the prognostic significance of patients with high or low APT values based on a threshold value from receiver operating characteristic curve analysis. Results Locoregional relapse, distant metastases, and disease relapse occurred in 14/77 (18%), 10/77 (13%), and 20/77 (26%) patients, respectively, at a median follow-up of 48.3 (10.6-67.4) months. Univariable analysis showed significant associations of LRRFS with APT(skewness)(HR = 1.98;p =0.034), DMFS with APT(mean)(HR = 2.44;p =0.033), and APT(90)(HR = 1.93;p =0.009), and DFS with APT(mean)(HR = 2.01;p =0.016), APT(90)(HR = 1.68;p =0.009), and APT(skewness)(HR = 1.85;p= 0.029). In multivariable analysis, the significant predictors for DMFS were APT(90)(HR = 3.51;p= 0.004) and nodal stage (HR = 5.95;p= 0.034) and for DFS were APT(90)(HR = 1.97;p= 0.010) and age (HR = 0.92;p= 0.014). An APT(90)>= 4.38% was associated with a significantly poorer DFS at 2 years than APT(90)< 4.38% (66% vs. 91%; HR = 4.01;p =0.005). Conclusion APTw imaging may potentially predict survival in patients with NPC. Key Points APTw imaging may provide new markers to predict survival in nasopharyngeal carcinoma. APT(90) is an independent predictor of distant metastases-free survival and disease-free survival. The APT(high) group is at higher risk of disease relapse than the APT(low) group.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Editorial Material Radiology, Nuclear Medicine & Medical Imaging

Editorial for Multi-site concordance of diffusion weighted imaging quantification for assessing prostate cancer aggressiveness

Jing Yuan, Darren M. C. Poon, Gladys Lo

JOURNAL OF MAGNETIC RESONANCE IMAGING (2022)

Article Oncology

Analysis of online plan adaptation for 1.5T magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) of prostate cancer

Darren M. C. Poon, Bin Yang, Hui Geng, Oi Lei Wong, Sin Ting Chiu, Kin Yin Cheung, Siu Ki Yu, George Chiu, Jing Yuan

Summary: This study retrospectively analyzed and characterized the online plan adaptation of 1.5T magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) in prostate cancer patients. The study found significant differences in the adoption frequency of ATS fractions between different treatment fractions, and investigated the rationale and criteria for ATS implementation.

JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY (2023)

Article Radiology, Nuclear Medicine & Medical Imaging

Detecting Early-Stage Liver Fibrosis Using Macromolecular Proton Fraction Mapping Based on Spin-Lock MRI: Preliminary Observations

Jian Hou, Vincent W-S Wong, Yurui Qian, Baiyan Jiang, Anthony W-H Chan, Howard H-W Leung, Grace L-H Wong, Simon C-H Yu, Winnie C-W Chu, Weitian Chen

Summary: This study used MPF-SL technology to measure macromolecule levels in the liver and found that it can detect early-stage liver fibrosis, and is not confounded by liver iron concentration or fat fraction.

JOURNAL OF MAGNETIC RESONANCE IMAGING (2023)

Article Radiology, Nuclear Medicine & Medical Imaging

Discriminating between benign and malignant salivary gland tumors using diffusion-weighted imaging and intravoxel incoherent motion at 3 Tesla

Rongli Zhang, Ann D. King, Lun M. Wong, Kunwar S. Bhatia, Sahrish Qamar, Frankie K. F. Mo, Alexander C. Vlantis, Qi Yong H. Ai

Summary: This study retrospectively evaluated the diagnostic performances of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for distinguishing between benign and malignant salivary gland tumors (SGTs). Significant differences in ADC(mean), D-mean, and D*(mean) were found between SGTs. IVIM showed higher accuracy than DWI in discriminating between benign and malignant SGTs due to its advantage in detecting Warthin's tumors (WTs).

DIAGNOSTIC AND INTERVENTIONAL IMAGING (2023)

Review Medicine, General & Internal

Current Applications of Deep Learning and Radiomics on CT and CBCT for Maxillofacial Diseases

Kuo Feng Hung, Qi Yong H. Ai, Lun M. Wong, Andy Wai Kan Yeung, Dion Tik Shun Li, Yiu Yan Leung

Summary: The increasing use of CT and CBCT in oral and maxillofacial imaging has led to the development of deep learning and radiomics applications for maxillofacial disease diagnosis and management. Deep learning models have been developed for automatic diagnosis, segmentation, and classification of various maxillofacial diseases, while radiomics applications mainly focus on diagnosing occult metastasis and osteoarthritis. These models show high performance and have the potential for clinical use, but challenges in generalizability and reproducibility need to be addressed.

DIAGNOSTICS (2023)

Editorial Material Radiology, Nuclear Medicine & Medical Imaging

Editorial for Repeatability of Quantitative Knee Cartilage T1, T2, and T1ρ Mapping with 3D-MRI Fingerprinting

Weitian Chen

JOURNAL OF MAGNETIC RESONANCE IMAGING (2023)

Article Radiology, Nuclear Medicine & Medical Imaging

Repeatability of quantitative T1rho magnetic resonance imaging in normal brain tissues at 3.0T

Lei Wang, Weitian Chen, Yurui Qian, Tiffany Y. So

Summary: This study aimed to assess the repeatability of T1rho imaging in normal brain grey and white matter. The results showed high test-retest repeatability of T1rho imaging for whole brain imaging, indicating its reliability for quantitative brain imaging.

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2023)

Article Engineering, Biomedical

An uncertainty aided framework for learning based liver T 1ρ mapping and analysis

Chaoxing Huang, Vincent Wai-Sun Wong, Queenie Chan, Winnie Chiu-Wing Chu, Weitian Chen

Summary: This study proposes a parametric map refinement approach for learning-based T-1 rho mapping. By training the model probabilistically to model uncertainty and utilizing uncertainty maps for weighted training of an improved mapping network, the mapping performance is enhanced and unreliable values are effectively removed. The results demonstrate the potential of this method to provide a trustworthy learning-based quantitative MRI system for T-1 rho mapping of the liver.

PHYSICS IN MEDICINE AND BIOLOGY (2023)

Review Oncology

Radiomics Analysis in Characterization of Salivary Gland Tumors on MRI: A Systematic Review

Kaijing Mao, Lun M. Wong, Rongli Zhang, Tiffany Y. So, Zhiyi Shan, Kuo Feng Hung, Qi Yong H. Ai

Summary: This study systematically evaluated the procedures of radiomics analysis for characterizing salivary gland tumors (SGTs) on MRI. Radiomics analysis showed potential in characterizing SGTs on MRI, but its clinical application is limited due to complex procedures and a lack of standardized methods. This review summarized the procedures of radiomics analysis, focusing on reported methodologies and performances, and proposed potential standards for further development, which may benefit the application of radiomics analysis in characterizing SGTs on MRI.

CANCERS (2023)

Article Radiology, Nuclear Medicine & Medical Imaging

Unsupervised domain adaptation for automated knee osteoarthritis phenotype classification

Junru Zhong, Yongcheng Yao, Donal G. Cahill, Fan Xiao, Siyue Li, Jack Lee, Kevin Ki-Wai Ho, Michael Tim-Yun Ong, James F. Griffith, Weitian Chen

Summary: This study demonstrates the utility of unsupervised domain adaptation (UDA) for automated osteoarthritis (OA) phenotype classification. By using a large, high-quality source dataset for training, the proposed UDA approach improves the performance of automated OA phenotype classification on small target datasets. This technique is important for improving downstream analysis of locally collected datasets with a small sample size.

QUANTITATIVE IMAGING IN MEDICINE AND SURGERY (2023)

Article Oncology

Role of chemotherapy in patients with nasopharynx carcinoma treated with radiotherapy (MAC-NPC): an updated individual patient data network meta-analysis

Claire Petit, Anne Lee, Jun Ma, Benjamin Lacas, Wai Tong Ng, Anthony T. C. Chan, Ruey-Long Hong, Ming-Yuan Chen, Lei Chen, Wen-Fei Li, Pei-Yu Huang, Terence Tan, Roger K. C. Ngan, Guopei Zhu, Hai-Qiang Mai, Edwin P. Hui, George Fountzilas, Li Zhang, Alexandra Carmel, Dora L. W. Kwong, James Moon, Jean Bourhis, Anne Auperin, Jean-Pierre Pignon, Pierre Blanchard

Summary: This study updated the evaluation of chemotherapy for nasopharynx carcinoma through a network meta-analysis. The results showed that the addition of induction chemotherapy or adjuvant chemotherapy to chemoradiotherapy improved overall survival for patients with non-metastatic nasopharyngeal carcinoma compared to chemoradiotherapy alone.

LANCET ONCOLOGY (2023)

Article Medicine, General & Internal

Evaluation of contemporary olanzapine- and netupitant/palonosetron-containing antiemetic regimens for chemotherapy-induced nausea and vomiting

Christopher C. H. Yip, L. Li, Thomas K. H. Lau, Vicky T. C. Chan, Carol C. H. Kwok, Joyce J. S. Suen, Frankie K. F. Mo, Winnie Yeo

Summary: This retrospective analysis compared the efficacy of olanzapine-based and NEPA-based regimens in controlling chemotherapy-induced nausea and vomiting (CINV) in breast cancer patients receiving AC. The olanzapine group showed higher rates of no rescue therapy and no significant nausea during cycle 1 of AC. However, there were no differences in quality of life between the two groups. Multiple cycle assessment revealed higher rates of total control in the NEPA group in later cycles. These results do not support the superiority of either regimen for breast cancer patients receiving AC.

HONG KONG MEDICAL JOURNAL (2023)

No Data Available