磁共振耦合谱成像识别头颈部肿瘤异质性及隐匿性淋巴结转移

doi:10.3969/j.issn.1674-8115.2025.09.012

上海交通大学学报（医学版） ›› 2025, Vol. 45 ›› Issue (9): 1202-1213.doi: 10.3969/j.issn.1674-8115.2025.09.012

磁共振耦合谱成像识别头颈部肿瘤异质性及隐匿性淋巴结转移

李偲羽¹, 陈娅¹, 胡文韬², 戴勇鸣³, 吴颖为¹()

^1.上海交通大学医学院附属第九人民医院放射科，上海 200011
^2.上海交通大学医学院附属仁济医院放射科，上海 200127
^3.上海科技大学生物医学工程学院，上海 201210

收稿日期:2025-03-06 接受日期:2025-03-25 出版日期:2025-09-28 发布日期:2025-09-30
通讯作者: 吴颖为，主任医师，博士；电子信箱: wuyw0103@hotmail.com。
基金资助:
国家自然科学基金(82373114);上海交通大学医学院附属第九人民医院“交叉”研究基金(JYJC202107);上海交通大学医学院“双百人”项目(20191815)

Using diffusion-relaxation correlation spectroscopic imaging to assess the heterogeneity of head and neck tumors and identify occult lymph node metastasis

LI Siyu¹, CHEN Ya¹, HU Wentao², DAI Yongming³, WU Yingwei¹()

^1.Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
^2.Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
^3.School of Biomedical Engineering, ShanghaiTech University, Shanghai 201210, China

Received:2025-03-06 Accepted:2025-03-25 Online:2025-09-28 Published:2025-09-30
Contact: WU Yingwei, E-mail: wuyw0103@hotmail.com.
Supported by:
National Natural Science Foundation of China(82373114);Cross Disciplinary Research Fund of Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine(JYJC202107);“Two-Hundred Talents”Program of Shanghai Jiao Tong University School of Medicine(20191815)

摘要/Abstract

摘要：

目的·评估磁共振弥散-弛豫耦合谱成像（diffusion-relaxation correlation spectroscopic imaging，DR-CSI）识别头颈部良恶性肿瘤异质性及隐匿性淋巴结转移（occult lymph node metastasis，OLNM）的可行性并检验其诊断效能。方法·前瞻性纳入2024年1月—12月上海交通大学医学院附属第九人民医院收治的疑似头颈部肿瘤、拟行手术且有明确病理诊断的患者。所有患者术前行常规头颈部平扫加增强磁共振成像（magnetic resonance imaging，MRI），含DR-CSI序列。常规图像上获得肿瘤最大径（maximal diameter，MD）、浸润深度（depth of invasion，DOI）及淋巴结长短径等数据，DR-CSI经后处理得到表观扩散系数（apparent diffusion coefficient，ADC）、T2值及所有病灶的D-T2耦合谱。基于不同疾病的谱峰分布特征进行亚区优化分割，分割后获得各亚区的体积分数V _i。使用独立样本t检验、Mann-Whitney U检验、χ²检验或Fisher精确检验比较患者临床资料和影像学参数的组间差异。使用主成分分析（principle component analysis，PCA）及Adonis分析评估影像学参数区分头颈部良性肿瘤不同亚型的效能。通过受试者操作特征（receiver operating characteristic，ROC）曲线评价单变量或多变量区分头颈鳞状细胞癌（head and neck squamous cell carcinoma，HNSCC）恶性程度并识别OLNM的能力。结果·共收集头颈部肿瘤97例，其中良性28例，HNSCC 69例。另有15枚经病理证实的OLNM及20枚良性淋巴结（benign lymph node，BLN）。28例良性肿瘤中，多形性腺瘤-基质丰富型（pleomorphic adenoma stroma-rich，PA stroma-rich）6例，基质缺乏型（pleomorphic adenoma stroma-rich，PA stroma-poor）9例，腺淋巴瘤（Warthin’s tumor，WT）9例，基底细胞腺瘤（basal cell adenoma，BCA）4例。良性肿瘤各亚型部分影像学参数（ADC、T2及DR-CSI V _i ）的组间差异均具有统计学意义（均P＜0.05）。PCA结果表明，含DR-CSI的影像学参数在头颈部良性肿瘤不同病理亚型间具有良好的区分度（R²=0.64，P<0.001）。69例HNSCC中，Grade 1组（高/高—中分化）47例，Grade 2组（中/中—低/低分化）22例。相较于恶性程度较低的Grade 1组，Grade 2组ADC更低，T2值更大，但差异均未达统计学意义。随着HNSCC的恶性程度增加，V_A4明显减少，而V_B4明显增大，组间差异具有统计学意义。相较于BLN，OLNM的短径（short diameter，SD）和V_A4显著增加，联合SD和V_A4对术前识别OLNM的诊断效能达0.843。结论·DR-CSI可通过解耦合获得单个体素独立的弥散和弛豫特征并解析肿瘤微观成分，在表征头颈部良性肿瘤不同亚型、HNSCC恶性程度和识别OLNM中具有良好的诊断价值。相较于传统单维参数ADC或T2等，DR-CSI能在亚体素水平更好地解析组织微观结构。

关键词: 磁共振弥散-弛豫耦合谱成像, 多形性腺瘤, 腺淋巴瘤, 基底细胞腺瘤, 头颈鳞癌, 隐匿性淋巴结转移

Abstract:

Objective ·To evaluate the feasibility and diagnostic performance of diffusion-relaxation correlation spectroscopic imaging (DR-CSI) in assessing the heterogeneity of benign and malignant head and neck tumors, as well as in identifying occult lymph node metastasis (OLNM). Methods ·A prospective study was conducted from January to December 2024 at Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, enrolling patients with suspected head and neck tumors who were scheduled for surgery and had a confirmed pathological diagnosis. All patients underwent preoperative routine head and neck plain and contrast-enhanced magnetic resonance imaging (MRI) examinations, including DR-CSI sequence. Conventional imaging parameters, including maximal diameter (MD), depth of invasion (DOI) for tumors, and MD and short diameter (SD) for lymph nodes, were obtained. Post-processing was performed to obtain apparent diffusion coefficient (ADC), T2 value, and D-T2 spectra for all lesions. The compartment segmentation strategy was optimized based on the spectral peak distribution characteristics of different diseases, and the volume fraction (V _i ) of each compartment was obtained. Independent sample t-tests, Mann-Whitney U tests, chi-square tests, or Fisher's exact tests were used to compare intergroup differences in clinical data and imaging metrics. Principal component analysis (PCA) and Adonis analysis were employed to evaluate the discriminative ability of imaging metrics among different subtypes of benign tumors. Receiver operating characteristic (ROC) analysis was used to evaluate the ability of univariate and multivariable models to characterize the malignancy of head and neck squamous cell carcinoma (HNSCC) and identify OLNM. Results ·A total of 97 cases were collected, including 28 benign tumors and 69 HNSCCs. Fifteen pathologically confirmed OLNMs and 20 benign lymph nodes (BLNs) were also enrolled. Among the 28 benign tumors, there were 6 cases of pleomorphic adenoma stroma-rich (PA stroma-rich), 9 cases of pleomorphic adenoma stroma-poor (PA stroma-poor), 9 cases of Warthin's tumor (WT), and 4 cases of basal cell adenoma (BCA). Statistically significant differences were observed in certain imaging parameters (ADC, T2, and DR-CSI V _i ) among benign tumor subtypes. PCA analysis demonstrated a strong discriminative ability of imaging parameters in distinguishing pathological subtypes of benign tumors (R²=0.64, P<0.001). Among the 69 HNSCCs, 47 were classified as Grade 1 (well/moderately well-differentiated) and 22 as Grade 2 (moderately/poorly differentiated). Compared to Grade 1, Grade 2 showed lower ADC and higher T2 values, though differences were not statistically significant. As HNSCC malignancy increased, V_A4 decreased and V_B4^{increased significantly. OLNM showed a significant increase in SD and V_A4 compared to BLNs. The combination of SD and V_A4 for preoperative OLNM identification achieved a diagnostic efficiency of 0.843. Conclusion ·DR-CSI can analyze diffusion and relaxation characteristics at the sub-voxel level, offering valuable insights for characterizing benign head and neck tumor subtypes, assessing HNSCC malignancy, and identifying OLNMs. Compared to traditional parameters like ADC or T2, DR-CSI provides enhanced tissue microstructure analysis.

Key words:
diffusion-relaxation correlation spectroscopic imaging,
pleomorphic adenoma,
Warthin's tumor,
basal cell adenoma,
head and neck squamous cell carcinoma,
occult lymph node metastasis

中图分类号:

R455.2

引用本文

李偲羽, 陈娅, 胡文韬, 戴勇鸣, 吴颖为. 磁共振耦合谱成像识别头颈部肿瘤异质性及隐匿性淋巴结转移[J]. 上海交通大学学报（医学版）, 2025, 45(9): 1202-1213.
LI Siyu, CHEN Ya, HU Wentao, DAI Yongming, WU Yingwei. Using diffusion-relaxation correlation spectroscopic imaging to assess the heterogeneity of head and neck tumors and identify occult lymph node metastasis[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025, 45(9): 1202-1213.

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https://xuebao.shsmu.edu.cn/CN/10.3969/j.issn.1674-8115.2025.09.012



https://xuebao.shsmu.edu.cn/CN/Y2025/V45/I9/1202}

图/表 12

图1 研究流程设计

Fig 1 Diagram of this study

表1 头颈部良性肿瘤患者的临床和影像数据

Tab 1 Clinical and imaging data of patients with benign head and neck tumors

Item	PA stroma-poor (n=9)	PA stroma-rich (n=6)	WT (n=9)	BCA (n=4)	P value
Age/year	45.4±13.9	40.8±11.0	51.7±10.1	41.8±9.0	0.101
Sex/n (%)					0.423
Male	5 (55.6)	2 (33.3)	7 (77.8)	2(50.0)
Female	4 (44.4)	4 (66.7)	2 (22.2)	2 (50.0)
MD/cm	2.56±1.04	2.00±0.88	3.33±0.97	1.98±0.64	0.040
ADC/(μm²·ms^-1)	1.35±0.13	2.04±0.10	0.87±0.21	1.72±0.18	<0.001
T2/ms	80.32±19.89	155.85±23.84	67.12±5.56	124.29±19.16	<0.001

表2 不同组织学等级的HNSCC患者的临床和影像数据

Tab 2 Clinical and imaging data of patients with HNSCC of different histological grades

Item	Grade 1 (n=47)	Grade 2 (n=22)	P value
Age/year	51.8±14.6	59.6±10.1	0.043
Sex/n (%)			0.715
Male	32 (68.1)	14 (63.6)
Female	14 (31.9)	8 (36.4)
Subsite/n (%)			0.599
Oral tongue	39 (83.0)	18 (81.8)
Oral floor	1 (2.1)	1 (4.5)
Gingiva	5 (10.6)	1 (4.5)
Oropharynx	2 (4.3)	2 (9.1)
MD/cm	2.85 (1.98, 3.75)	3.00 (2.05, 3.73)	0.605
DOI/cm	1.30 (0.90, 1.68)	1.30 (1.00, 2.00)	0.506
cT stage/n (%)			0.973
T1‒2	13 (27.7)	6 (27.3)
T3‒4	34 (72.3)	16 (72.7)
LNM/n (%)			0.044
Negative	25 (53.2)	6 (27.3)
Positive	22 (46.8)	16 (72.1)
ADC/(μm²·ms^-1)	0.98 (0.92, 1.12)	0.92 (0.87, 1.04)	0.053
T2/ms	65.46 (52.28, 70.40)	62.75 (56.91, 69.13)	0.827
DR-CSI V_A4/%	40.2 (25.7, 54.1)	22.9 (17.9, 33.5)	0.002
DR-CSI V_B4/%	41.3 (28.6, 58.4)	59.3 (52.8, 67.8)	0.002
DR-CSI V_C4/%	14.9 (12.1, 20.6)	14.2 (12.7, 19.4)	0.718

图2 不同病理类型的头颈部良性肿瘤的典型示例Note： A‒D. DR-CSI, T2WI, DWI images, and D-T2 spectra of PA stroma-poor from a 61-year-old male (A), PA stroma-rich from a 54-year-old female (B), WT from a 62-year-old male (C), and BCA from a 38-year-old male (D). The ROIs are labeled in red dashed circle. Original D-T2 spectra of benign tumors were firstly segmented into seven compartments (A1-3, B1-3, and C). E‒H. The final segmentation strategies for comparison of D-T2 spectra among different benign tumors are as follows: PA stroma-poor (E) vs PA stroma-rich (A1+2+3, B1+2+3, and C); PA stroma-poor (F) vs WT (A1B1, A2+3B2+3, and C); WT (G) vs BCA (A1+2, A3, B1+2+3, and C); PA stroma-rich (H) vs BCA (A1+2B1+2, A3B3, and C).

Fig 2 Representative cases of different pathological types of benign head and neck tumors

图3 不同病理类型的良性肿瘤DR-CSI各亚区体积分数、ADC和T2伪彩图的典型示例

Fig 3 Representative DR-CSI volume fraction, ADC, and T2 maps of different pathological types of benign head and neck tumors

表3 影像学参数在头颈部良性肿瘤不同亚型中的两两比较

Tab 3 Pairwise comparison of imaging parameters among different subtypes of benign head and neck tumors

Item	PA stroma-poor (n=9)	PA stroma-rich (n=6)	P value
ADC/(μm²·ms^-1)	1.35±0.13	2.04±0.10	<0.001
T2/ms	80.32±19.89	155.85±23.84	<0.001
DR-CSI V_A1+2+3/%	87.0±6.1	46.4±19.8	0.003
DR-CSI V_B1+2+3/%	3.9±3.6	39.9±17.6	0.004
DR-CSI V_C/%	9.1±4.4	13.7±3.8	0.060
Item	PA stroma-poor (n=9)	WT (n=9)	P value
ADC/(μm²·ms^-1)	1.35±0.13	0.87±0.21	<0.001
T2/ms	80.32±19.89	67.12±5.56	0.086
DR-CSI V_A1B1/%	25.3±4.5	53.9±9.5	<0.001
DR-CSI V_A2+3B2+3/%	67.3 (60.3, 70.5)	16.9 (2.0, 19.2)	<0.001
DR-CSI V_C/%	9.1±4.4	34.5±12.5	<0.001
Item	WT (n=9)	BCA (n=4)	P value
ADC/(μm²·ms^-1)	0.87±0.21	1.72±0.18	<0.001
T2/ms	67.12±5.56	124.29±19.16	0.008
DR-CSI V_A1+2/%	53.1±9.3	15.4±7.0	<0.001
DR-CSI V_A3/%	15.7 (2.0, 19.1)	38.5 (33.0, 40.9)	0.005
DR-CSI V_B1+2+3/%	1.1±0.9	29.0±11.7	0.017
DR-CSI V_C/%	34.5±12.5	18.1±2.7	0.004
Item	PA stroma-rich (n=6)	BCA (n=4)	P value
ADC/(μm²·ms^-1)	2.04±0.10	1.72±0.18	0.006
T2/ms	155.85±23.84	124.29±19.16	0.059
DR-CSI V_A1+2B1+2/%	40.7±3.7	63.0±7.0	0.004
DR-CSI V_A3B3/%	45.6±3.9	18.9±7.6	0.003
DR-CSI V_C/%	13.7±3.8	18.1±2.7	0.080

图4 DR-CSI参数在头颈部良性肿瘤不同病理亚型之间的差异（A）及影像学参数在头颈部良性肿瘤不同病理亚型中的区分度（B）

图5 不同组织学级别HNSCC的典型示例Note： Original DR-CSI images (b=800 s/mm2, TE=77 ms), D-T2 spectra, and DR-CSI volume fraction mappings, ADC, and T2 mappings. A. Well-to moderately differentiated oral tongue squamous cell carcinoma from a 71-year-old man. B. Moderately differentiated oropharynx squamous cell carcinoma from a 66-year-old man. The ROIs are labeled in red dashed circle. The spectra are divided by dash lines into three compartments (A4, B4, and C).

Fig 5 Representative cases of HNSCC with different pathological grades

图6 BLN与OLNM的典型示例Note： Original DR-CSI (b=800 s/mm2, TE=77 ms), T2WI, CE-T1WI images, D-T2 spectra, and DR-CSI volume fraction mappings, ADC, and T2 mappings. A. An 8.9 mm BLN at left level Ⅱ from a 30-year-old male with PA. B. A 7.2 mm OLNM at left level II from a 71-year-old male with oral tongue squamous cell carcinoma. The ROIs are labeled in red dashed circle. The D-T2 spectra are divided into three compartments by dash lines (A4, B4, and C).

Fig 6 Representative cases of BLN and OLNM

表4 BLN和OLNM组影像学参数的比较

Tab 4 Comparison of imaging parameters between BLN and OLNM groups

Item	BLN (n=20)	OLNM (n=15)	P value
SD/cm	0.67 (0.57, 0.80)	0.92 (0.72, 1.00)	0.011
L/S ratio	1.46 (1.28, 1.84)	1.51 (1.33, 1.73)	0.805
ADC/(μm²·ms^-1)	0.88±0.17	0.96±0.16	0.119
T2/ms	71.03±11.09	67.46±13.73	0.401
DR-CSI V_A4/%	16.7±9.9	27.3±13.0	0.010
DR-CSI V_B4/%	63.1±12.3	54.5±14.4	0.066
DR-CSI V_C/%	20.2±8.7	18.2±9.6	0.531

表5 影像学参数评估HNSCC恶性程度及识别OLNM的诊断效能

Tab 5 Diagnostic performance of imaging parameters for assessing malignancy of HNSCC and detecting OLNM

Item	AUC	Sensitivity	Specificity	Cut-off
HNSCC malignancy assessment
DR-CSI V_A4/%	0.733	0.809	0.591	25.0
DR-CSI V_B4/%	0.730	0.818	0.660	49.3
OLNM identification
SD/cm	0.753	0.867	0.700	0.70
DR-CSI V_A4/%	0.722	0.733	0.650	19.6
Combined parameters	0.843	0.667	0.900	‒

图7 影像学参数评估HNSCC恶性程度及识别OLNM的诊断效能Note： Pie charts illustrate the differences in DR-CSI parameters, while ROC curves depict the diagnostic performance for Grade 1 versus Grade 2 HNSCC (A) and for BLN versus OLNM (B).

Fig 7 Diagnostic performance for imaging parameters in characterizing the malignancy of HNSCC and identifying OLNM

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磁共振耦合谱成像识别头颈部肿瘤异质性及隐匿性淋巴结转移

Using diffusion-relaxation correlation spectroscopic imaging to assess the heterogeneity of head and neck tumors and identify occult lymph node metastasis

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