Quantitative T2 mapping of junctional zone alterations in endometrial fibrosis: comparison with diffusion-weighted imaging
Original Article

Quantitative T2 mapping of junctional zone alterations in endometrial fibrosis: comparison with diffusion-weighted imaging

Huanhuan Liang1#, Kaibo Sun1#, Hui Zhu2#, Yucan Chen1, Peipei Jiang2, Huanhuan Wang1, Nan Zhou1, Yali Hu2, Zhengyang Zhou1, Kefeng Zhou1

1Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; 2Department of Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China

Contributions: (I) Conception and design: H Liang, K Sun, H Zhu; (II) Administrative support: Y Hu, Z Zhou; (III) Provision of study materials or patients: N Zhou, Y Hu, K Zhou, Z Zhou; (IV) Collection and assembly of data: Y Chen, P Jiang, H Wang, N Zhou; (V) Data analysis and interpretation: H Liang, K Sun, H Zhu; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Kefeng Zhou, MD, PhD; Zhengyang Zhou, MD, PhD; Nan Zhou, MD, PhD. Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321 Zhongshan Road, Nanjing 210008, China. Email: zhoukefeng1977@163.com; zyzhou@nju.edu.cn; snscorpion@163.com; Yali Hu, MD, PhD. Department of Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321 Zhongshan Road, Nanjing 210008, China. Email: yalihu@nju.edu.cn.

Background: Endometrial fibrosis can disrupt the uterine junctional zone and lead to infertility. Accurate and noninvasive evaluation of junctional zone alterations is important to clinical treatment. Although conventional T2-weighted imaging provides only qualitative information, quantitative techniques such as diffusion-weighted imaging (DWI) and T2 mapping may better capture fibrosis-related microstructural changes. This study aimed to use T2 mapping to quantitatively assess junctional zone alterations in endometrial fibrosis using, compare its performance with the apparent diffusion coefficient (ADC), and evaluate its diagnostic value and reproducibility.

Methods: This prospective study included 86 patients with severe endometrial fibrosis (SEF), 40 patients with mild-to-moderate endometrial fibrosis (MMEF), and 55 healthy women. Junctional zone thickness (JZT), outer myometrial thickness (OMT), T2 relaxation times of the junctional zone (T2JZ) and outer myometrium (T2OM), and ADC values of the junctional zone (ADCJZ) and outer myometrium (ADCOM) were measured and analyzed. Statistical analyses included Kruskal-Wallis one-way analysis of variance, Spearman correlation analysis, binary logistic regression, receiver operating characteristic curves, and intraclass correlation coefficients.

Results: JZT, T2JZ, and ADCJZ values were significantly higher in patients with SEF (6.0 mm, 81.3 ms, 1.04×10−3 mm2/s, respectively) and patients with MMEF (5.1 mm, 71.2 ms, and 0.98×10−3 mm2/s, respectively) than in healthy women (3.8 mm, 65.2 ms, and 0.81×10−3 mm2/s, respectively) (all P values <0.05). T2JZ was substantially elevated in patients with SEF compared with those with MMEF (P<0.001). OMT, T2OM, and ADCOM were significantly higher in patients with SEF compared to healthy women (all P values <0.05). T2JZ was strongly correlated with the degree of endometrial fibrosis (ρ=0.728), whereas JZT, ADCJZ, OMT, T2OM, and ADCOM showed weak-to -moderate correlations (ρ=0.254–0.550; all P values <0.05). Junctional zone and outer myometrial magnetic resonance imaging parameters and the multivariable model accurately distinguished patients with MMEF or those with SEF from healthy women (areas under the curve >0.600). The intra- and interobserver agreement for T2 values was excellent and higher than that for ADC values.

Conclusions: T2 mapping is more effective than ADC in accurately assessing the junctional zone alterations associated with endometrial fibrosis.

Keywords: T2 mapping; diffusion-weighted imaging (DWI); apparent diffusion coefficient (ADC); junctional zone; endometrial fibrosis


Submitted Nov 20, 2025. Accepted for publication May 19, 2026. Published online Jun 04, 2026.

doi: 10.21037/qims-2025-1-2502


Introduction

The uterine junctional zone, also known as the inner myometrium, is the transitional region that is located between the endometrium and the outer myometrium (1). The junctional zone plays a crucial role in regulating endometrial growth, differentiation, and uterine contraction (2). Notably, thickening or disruption of the junctional zone is commonly observed in pathological conditions such as adenomyosis and uterine fibroids, which may contribute to reproductive disorders and adverse pregnancy outcomes. Therefore, the accurate and noninvasive assessment of junctional zone alterations is essential for understanding reproductive dysfunction and guiding clinical management in affected individuals.

Endometrial fibrosis, a leading cause of uterine infertility, is characterized by the presence of intrauterine adhesions (IUAs) (3). Studies have shown that the incidence of endometrial fibrosis among women of childbearing age is as high as 31.6% (4). Mechanical damage or infection triggers an inflammatory cascade that promotes endometrial scarring and fibrosis and further infiltrates the adjacent junctional zone (5,6). Consequently, disruption of the junctional zone could impair uterine peristalsis and endometrial perfusion, ultimately leading to implantation failure (7,8). This may represent one potential mechanism contributing to adverse pregnancy outcomes in patients with endometrial fibrosis.

Among the imaging techniques currently in use for evaluating the junctional zone, transvaginal ultrasound can visualize it as a hypoechoic band at the interface between the endometrium and the myometrium (9). However, its diagnostic accuracy is limited by relatively low spatial resolution and high operator dependency, restricting the precise anatomical and microstructural assessment of the junctional zone (10). In contrast, magnetic resonance imaging (MRI) is considered the standard modality for imaging the junctional zone (11). On T2-weighted imaging (T2WI), the junctional zone appears as a hypointense band located between the hyperintense endometrium and the intermediate-signal outer myometrium (12). Previous studies have reported increased signal intensity of the junctional zone on T2WI in patients with endometrial fibrosis, indicating underlying microstructural alterations in this region. However, T2WI provides only qualitative or semiquantitative information based on relative signal intensity, limiting its capability to objectively and quantitatively assess either diffuse or even subtle changes in the junctional zone.

Functional MRI techniques, such as diffusion-weighted imaging (DWI) and T2 mapping, have been applied to detect fibrosis-related microstructural changes in organs, including the myocardium, liver, and intestines (13-15). DWI quantifies water molecule diffusion within tissues by calculating the apparent diffusion coefficient (ADC), which reflects changes in tissue cellularity within the junctional zone (16,17). However, since DWI relies on echo-planar imaging (EPI) pulse sequences, it has relatively low spatial resolution and is susceptible to image artifacts (18). As another quantitative measurement, T2 mapping calculates the intrinsic T2 relaxation time of tissues by fitting exponential decay curves to the signal intensities acquired at multiple echo times, which reflects the water accumulation and blood volume within tissues. Owing to its fast spin echo-based (FSE) acquisition, T2 mapping offers higher spatial resolution and reduced sensitivity to motion and susceptibility artifacts (19). It has been used to assess junctional zone-related pathologies, such as adenomyosis and endometrial carcinoma (20,21). Infiltration of the junctional zone by inflammatory cells and fibrotic tissue disrupts normal cellular architecture, which may theoretically alter tissue water content (5,6). Thus, T2 mapping has the potential to quantitatively assessing junctional zone alterations in patients with endometrial fibrosis.

Therefore, we conducted a prospective study to quantitatively assess junctional zone alterations in patients with varying degrees of endometrial fibrosis by determining T2 values, comparing them with corresponding ADC values, and evaluating their diagnostic performance and reproducibility. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2502/rc).


Methods

Study population

This prospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Ethics Committee of Nanjing Drum Tower Hospital (approval No. 2019-051-02). Informed consent was obtained from all participants. The patients were recruited during routine clinic visits at the Department of Obstetrics and Gynecology at Nanjing Drum Tower Hospital. According to the American Fertility Society (AFS) classification system, severe IUA is characterized by more extensive endometrial fibrotic scarring compared to mild-to-moderate IUA, indicating a positive relationship between the extent of adhesion and the severity of endometrial fibrosis (22). Accordingly, patients with severe IUAs were categorized as patients with severe endometrial fibrosis (SEF), while those with mild-to-moderate IUAs were classified as patients with mild-to-moderate endometrial fibrosis (MMEF) (19). The inclusion criteria for patients were as follows: (I) endometrial fibrosis confirmed by hysteroscopy; (II) age ranging from 20 to 42 years; (III) history of dilation and curettage (D&C); (IV) clinical infertility, defined as the inability to achieve a clinical pregnancy after at least 12 months of regular unprotected intercourse (23); and (V) preserved normal ovarian function. Meanwhile, the exclusion criteria for patients were as follows: (I) concomitant severe uterine pathology according to the European Society of Human Reproduction and Embryology/European Society for Gynaecological Endoscopy (ESHRE/ESGE) consensus definition (24), such as uterine fibroids and adenomyosis; and (II) contraindications to MRI examination. Healthy women aged 20–42 years with regular menstrual cycles and normal menstrual blood volume were included. Individuals with any history of uterine disease or uterine injury (e.g., D&C procedures) or with MRI contraindications were excluded.

Sample size was calculated with G*Power software version 3.1.9.6 (http://www.gpower.hhu.de/) based on an a priori power analysis for one-way analysis of variance (ANOVA). The analysis assumed a medium effect size of 0.25, a significance level (α) of 0.05, and a power (1−β) of 0.80 (β=0.2) (25). The results indicated that 159 participants were needed to compare the MRI parameters across healthy women, patients with MMEF, and patients with SEF.

Endometrial fibrosis was diagnosed based on hysteroscopic findings and endometrial biopsy. The degree of endometrial fibrosis was graded according to the AFS classification criteria in a blinded manner by a gynecologist with 10 years of experience in hysteroscopy (22). Any disagreement on AFS scores was reviewed by a senior gynecologist and resolved via consultation with a senior gynecologist.

MRI protocols

All participants underwent MRI scanning within 2 days prior to the hysteroscopic procedure. Given that the junctional zone undergoes morphological and microstructural variations during the menstrual cycle (26), MRI examination was also performed during the late proliferative phase. MRI scans were performed on a 3.0-T system (Ingenia, Philips Medical Systems, Best, The Netherlands) with a 16-channel phased-array body coil. To reduce motion artifacts arising from intestinal peristalsis and bladder movement, all participants fasted for a minimum of 2 hours and emptied their bladders before imaging. The MRI sequences include sagittal T2WI, T2 mapping, and DWI of the uterus. The detailed parameters of these sequences are provided in Table 1.

Table 1

MRI scanning protocol

Parameter T2WI T2 mapping DWI
Sequence TSE Multi-echo TSE EPI
TR (ms) 1,700–5,000 1,773 6,000
TE (ms) 100 17–85 (Δ=17 ms) 90
Matrix 200×167 124×108 133×160
Flip angle (º) 90 90 90
Slice thickness (mm) 3 3 3
Number of slices 18 18 18
FOV (mm) 120×120 200×200 240×240
Voxel size (mm) 0.6×0.7×3 1.6×1.75×3 1.8×1.5×3
b value (s/mm2) 0, 1,000
NSA 1.1 1 2
Acquisition time (min:s) 3:56 0:57 2:06

DWI, diffusion-weighted imaging; EPI, echo-planar imaging; FOV, field of view; MRI, magnetic resonance imaging; NSA, number of signals averaged; T2WI, T2-weighted imaging; TE, echo time; TR, repetition time; TSE, turbo spin echo.

Image analysis

Two radiologists (with 5 years and 10 years of experience in pelvic MRI, respectively) independently analyzed the MRI sequences of all participants on ImageJ software version 1.53c (ImageJ, US National Institutes of Health, Bethesda, MD, USA) and were blinded to the clinical data of all participants during the analysis. Qualitative assessment of image quality was jointly performed by the two radiologists. Images with motion or other artifacts that substantially impaired the delineation of the junctional zone and outer myometrium were considered to have inadequate quality. In contrast, relatively high-quality images were considered to be those with minimal or no artifacts that could ensure clear visualization of both regions and were thus included in the subsequent analysis. The junctional zone thickness (JZT) and outer myometrial thickness (OMT) were respectively measured at the anterior wall, posterior wall, and fundus of the uterine corpus on the midsagittal T2WI. The final values of JZT and OMT were calculated as the average of the measurements on the three uterine walls. T2 values of the junctional zone (T2JZ) and outer myometrium (T2OM) were respectively measured on the midsagittal T2 maps of the uterus. Correspondingly, ADC values of the junctional zone (ADCJZ) and outer myometrium (ADCOM) were respectively measured on the midsagittal ADC maps of the uterus from DWI data. Regions of interest (ROIs) were manually delineated to include as much of the junctional zone and outer myometrium of the uterine corpus as possible, with care taken to avoid their boundaries and areas affected by susceptibility artifacts from intestinal air (Figure 1). For each participant, the ROIs were visually inspected to ensure accurate alignment and consistency between the T2 and ADC maps, with reference to the corresponding T2WI images. The mean values of the measurements obtained by the two radiologists for all parameters (JZT, OMT, T2JZ, T2OM, ADCJZ, and ADCOM) were used for the subsequent analysis. To assess intraobserver reproducibility, T2JZ, T2OM, ADCJZ, and ADCOM were repeatedly measured by the first observer with an interval of 8 weeks.

Figure 1 Measurements of the thickness, T2, and ADC values of the junctional zone and outer myometrium in the uterine corpus on a midsagittal T2-weighted image (A), T2 map (B), and ADC map (C). Thickness was measured at the AJZ and AOM, PJZ and POM, and FJZ and FOM. For T2 and ADC quantification, regions of interest were manually delineated to encompass as much of the junctional zone (dotted line) and outer myometrium (solid line) of the uterine corpus as possible. ADC, apparent diffusion coefficient; AJZ, anterior junctional zone; AOM, anterior outer myometrium; FJZ, fundal junctional zone; FOM, fundal outer myometrium; PJZ, posterior junctional zone; POM, posterior outer myometrium.

Statistical analysis

Statistical analyses were conducted via SPSS version 22.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism 7.0 (Dotmatics, Boston, MA, USA). Continuous variables with a normal distribution are expressed as the mean ± standard deviation, whereas nonnormally distributed variables are expressed as the median and interquartile range (IQR). Differences in JZT, OMT, T2JZ, T2OM, ADCJZ, and ADCOM were analyzed via Kruskal-Wallis one-way ANOVA. Bonferroni adjustment was applied for post hoc multiple comparisons. Correlations between uterine MRI parameters and the degree of endometrial fibrosis were evaluated according to the Spearman rank correlation coefficient (ρ). Correlation was categorized as weak (r>0.3), moderate (r>0.5), or strong (r>0.7) (27). Binary logistic regression analysis was used to build a multivariable model with the statistically significant MRI parameters. Receiver operating characteristic (ROC) analysis was performed to determine the cutoff values, sensitivity, and specificity of the MRI parameters. Confidence intervals for the area under the curve (AUC) and pairwise AUC comparisons were estimated via the DeLong method. Statistical significance of the AUC was calculated and adjusted for multiple comparisons through Bonferroni correction. The interobserver reproducibility of continuous quantitative variables was evaluated according to the intraclass correlation coefficient (ICC), with values >0.75 indicating good agreement (28). Bland-Altman analysis was performed to graphically display the mean differences and 95% limits of agreement (LOA). P<0.05 was considered statistically significant.


Results

Study population

Between November 2022 and March 2024, 60 healthy women, 45 patients with MMEF, and 95 patients with SEF were prospectively enrolled. After 5 healthy women, 5 patients with MMEF, and 9 patients with SEF were excluded due to insufficient image quality, 55 healthy women (median age 29 years; IQR, 28–32 years), 40 patients with MMEF (median age 32 years; IQR, 28–35 years), and 86 patients with SEF (median age 33 years; IQR, 30–36 years) were included in the final analysis. All patients had a history of at least one D&C, and patients with a severe condition had experienced recurrent IUAs requiring multiple hysteroscopic adhesiolysis procedures. The flowchart of participant inclusion is presented in Figure 2.

Figure 2 Flowchart of participant inclusion. MRI, magnetic resonance imaging.

Differences in MRI parameters of the junctional zone and outer myometrium

As shown in Table 2, JZT, T2JZ, and ADCJZ were significantly higher in the MMEF and SEF groups than in the healthy group. Moreover, T2JZ was significantly higher in the SEF group than in the MMEF group, whereas no significant differences in JZT or ADCJZ were observed between these two groups. OMT, T2OM, and ADCOM were significantly higher in the SEF group than in the healthy group, whereas no significant differences were found between the healthy group and MMEF group or between the two patient groups. Representative uterine midsagittal T2WI, T2 maps, and ADC maps of the participants are shown in Figure 3.

Table 2

Differences in thickness, T2 value, and ADC value in the junctional zone and outer myometrium among healthy women, patients with MMEF, and patients with SEF

Parameter Healthy women Patients with MMEF Patients with SEF P Pairwise comparison
P1 P2 P3
Junctional zone
   JZT (mm) 4.0 (3.4, 5.1) 5.1 (4.3, 6.8) 6.0 (5.1, 6.8) <0.001* <0.001* <0.001* 0.089
   T2JZ (ms) 62.2 (57.3, 67.1) 71.2 (68.5, 75.0) 81.3 (76.9, 81.4) <0.001* 0.001* <0.001* <0.001*
   ADCJZ (×10−3 mm2/s) 0.78 (0.69, 0.91) 0.98 (0.85, 1.14) 1.04 (0.93, 1.19) <0.001* <0.001* <0.001* 0.234
Outer myometrium
   OMT (mm) 8.2 (7.4, 10.1) 9.4 (7.7, 11.5) 10.3 (9.0, 11.7) <0.001* 0.102 <0.001* 0.115
   T2OM (ms) 110.2 (100.4, 118.7) 116.5 (108.0, 129.9) 119.8 (110.1, 133.5) 0.002* 0.138 0.001* 0.965
   ADCOM (×10−3 mm2/s) 1.42 (1.22, 1.61) 1.46 (1.36, 1.59) 1.60 (1.43, 1.75) <0.001* 0.139 <0.001* 0.112

Data are presented as median (interquartile range). Kruskal-Wallis one-way analysis of variance test with Bonferroni adjustment for pairwise comparisons. P1, MMEF patients vs. healthy women; P2, patients with SEF vs. healthy women; P3, patients with SEF vs. MMEF patients. *, P<0.05. ADC, apparent diffusion coefficient; JZ, junctional zone; JZT, junctional zone thickness; MMEF, mild-to-moderate endometrial fibrosis; OM, outer myometrium; OMT, outer myometrial thickness; SEF, severe endometrial fibrosis.

Figure 3 Midsagittal T2-weighted images (A,E,I), T2 maps (B,F,J), the corresponding pseudo-color T2 maps (C,G,K), and ADC maps (D,H,L) in a heathy woman (A-D), a patient with MMEF (E-H), and a patient with SEF (I-L). Dotted lines show the junctional zone areas in corpus uteri. The JZT, T2JZ, and ADCJZ were, respectively, 4.1 mm, 65 ms, and 0.99×10−3 mm2/s in the healthy woman; 5.8 mm, 71 ms, and 0.90×10−3 mm2/s in the patient with MMEF; and 7.9 mm, 79 ms, and 1.25×10−3 mm2/s in the patient with SEF. The OMT, T2 value of the T2OM, and ADCOM were, respectively, 7.9 mm, 106 ms, and 1.50×10−3 mm2/s in the healthy woman; 9.6 mm, 124 ms, and 1.56×10−3 mm2/s in the patient with MMEF; and 9.9 mm, 120 ms, and 1.63×10−3 mm2/s in the patient with SEF. ADC, apparent diffusion coefficient; ADCJZ, ADC value of the junctional zone; ADCOM, ADC value of the outer myometrium; JZT, junctional zone thickness; MMEF, mild-to-moderate endometrial fibrosis; OMT, outer myometrium thickness; SEF, severe endometrial fibrosis; T2JZ, T2 value of the junctional zone; T2OM, T2 value of the outer myometrium.

Correlations of the thickness, T2 value, and ADC value of the junctional zone and outer myometrium with the degree of endometrial fibrosis

As shown in Figure 4, there were strong positive correlations between T2JZ and the degree of endometrial fibrosis. There was weak-to-moderate positive correlation of OMT, T2OM, ADCOM, JZT, and ADCJZ with the degree of endometrial fibrosis.

Figure 4 Charts for the significant correlations between the degree of endometrial fibrosis and the uterine anatomical parameters, T2, and ADC of the junctional zone and outer myometrium. JZT (A), T2JZ (B), ADCJZ (C), OMT (D), T2OM (E), and ADCOM (F). ADC, apparent diffusion coefficient; ADCJZ, ADC value of the junctional zone; ADCOM, ADC value of the outer myometrium; JZT, junctional zone thickness; OMT, outer myometrial thickness; T2JZ, T2 value of the junctional zone; T2OM, T2 value of the outer myometrium.

Thickness, T2 value, and ADC value of the junctional zone and outer myometrium in diagnosing MMEF and SEF according to ROC analysis

As shown in Table 3 and Figure 5, the AUC of the multivariable model for distinguishing patients with MMEF from healthy women was significantly higher than that of JZT, T2JZ, and ADCJZ alone (P=0.001, P=0.015, and P=0.012, respectively). For distinguishing patients with SEF from healthy women, the multivariable model achieved the highest AUC and was significantly superior to JZT, ADCJZ, OMT, T2OM, ADCOM (all P values <0.001), and T2JZ (P=0.015). T2JZ showed good performance in distinguishing MMEF patients from patients with SEF.

Table 3

ROC analysis for the diagnosis of patients with MMEF and patients with SEF

Parameter AUC (95% CI) Cutoff value Sensitivity Specificity P
MMEF patients vs. healthy women
   JZT (mm) 0.759 (0.664–0.855) 3.8 0.975 0.455 <0.001*
   T2JZ (ms) 0.836 (0.756–0.916) 67.1 0.850 0.745 <0.001*
   ADCJZ (×10−3 mm2/s) 0.781 (0.688–0.874) 0.95 0.625 0.855 <0.001*
   Multivariable model 0.920 (0.869–0.972) 0.283 0.950 0.800 <0.001*
Patients with SEF vs. healthy women
   JZT (mm) 0.840 (0.770–0.909) 4.4 0.930 0.655 <0.001*
   T2JZ (ms) 0.968 (0.945–0.992) 71.6 0.919 0.891 <0.001*
   ADCJZ (×10−3 mm2/s) 0.855 (0.789–0.921) 0.95 0.721 0.855 <0.001*
   OMT (mm) 0.742 (0.659–0.825) 8.5 0.849 0.545 <0.001*
   T2OM (ms) 0.672 (0.582–0.763) 118.8 0.523 0.764 <0.001*
   ADCOM (×10−3mm2/s) 0.648 (0.554–0.741) 1.42 0.779 0.491 0.002*
   Multivariable model 0.995 (0.989–1.000) 0.619 0.965 0.964 <0.001*
Patients with MMEF vs. patients with SEF
   T2JZ (ms) 0.867 (0.800–0.934) 75.9 0.802 0.825 <0.001*

*, P value for significance set at 0.017 with Bonferroni correction used to adjust for multiple comparisons. ADC, apparent diffusion coefficient; AUC, area under the curve; CI, confidence interval; JZ, junctional zone; JZT, junctional zone thickness; MMEF, mild-to-moderate endometrial fibrosis; OM, outer myometrium; OMT, outer myometrial thickness; ROC, receiver operating characteristic; SEF, severe endometrial fibrosis.

Figure 5 ROC curves of the junctional zone and outer myometrial parameters—including thickness (JZT and OMT), T2 value (T2JZ and T2OM), and ADC value (ADCJZ and ADCOM)—for differentiating (A) patients with MMEF from healthy women, (B) patients with SEF from healthy women, and (C) patients with SEF from those with MMEF. ADC, apparent diffusion coefficient; ADCJZ, ADC value of the junctional zone; ADCOM, ADC value of the outer myometrium; JZT, junctional zone thickness; MMEF, mild-to-moderate endometrial fibrosis; OMT, outer myometrial thickness; ROC, receiver operating characteristic; SEF, severe endometrial fibrosis; T2JZ, T2 value of the junctional zone; T2OM, T2 value of the outer myometrium.

Reproducibility of the T2 value and ADC value of the junctional zone and outer myometrium

As shown in Table 4, both the intra- and interobserver ICCs of T2JZ, ADCJZ, T2OM, and ADCOM measurements were excellent across healthy women, patients with MMEF, and patients with SEF. For both intra- and interobserver agreement, T2 values demonstrated higher ICCs compared with ADC values. Bland-Altman plots (Figure 6) indicated that T2 measurements had narrower LOA and fewer outliers beyond ±1.96 SD than did ADC measurements.

Table 4

Reproducibility of T2 values and ADC values of the junctional zone and outer myometrium

Parameter Healthy women Patients with MMEF Patients with SEF
Intraobserver Interobserver Intraobserver Interobserver Intraobserver Interobserver
Junctional zone
   T2JZ (ms) 0.955 (0.917, 0.975) 0.941 (0.901, 0.965) 0.912 (0.841, 0.953) 0.911 (0.838, 0.952) 0.952 (0.922, 0.970) 0.916 (0.873, 0.944)
   ADCJZ (×10−3 mm2/s) 0.912 (0.853, 0.948) 0.878 (0.799, 0.927) 0.881 (0.787, 0.936) 0.873 (0.774, 0.931) 0.901 (0.850, 0.935) 0.880 (0.822, 0.920)
Outer myometrium
   T2OM (ms) 0.945 (0.905, 0.968) 0.933 (0.889, 0.961) 0.921 (0.856, 0.958) 0.901 (0.817, 0.947) 0.908 (0.862, 0.939) 0.900 (0.821, 0.941)
   ADCOM (×10−3 mm2/s) 0.910 (0.850, 0.946) 0.885 (0.810, 0.932) 0.911 (0.838, 0.952) 0.829 (0.323, 0.938) 0.897 (0.838, 0.933) 0.832 (0.683, 0.904)

Data are presented as ICC (95% CI). ADC, apparent diffusion coefficient; CI, confidence interval; ICC, intraclass correlation coefficient; JZ, junctional zone; MMEF, mild-to-moderate endometrial fibrosis; OM, outer myometrium; SEF, severe endometrial fibrosis.

Figure 6 Bland-Altman plots (% difference vs. average) of T2 and ADC values for the junctional zone and outer myometrium (n=181). (A,B) Comparison of T2JZ and ADCJZ measured on sides by the same observer and (C,D) by two different observers. (E,F) Comparison of T2OM and ADCOM measured on sides by the same observer and (G,H) by two different observers. Red solid and blue dashed lines in Bland-Altman plots show the bias and 95% limits of agreement, respectively. The Bland-Altman comparison results are expressed as a percentage of the relative difference [100 × (reader 1 –reader 2)/average] vs. average or [100 × (1st – 2nd)/average] vs. the average. ADC, apparent diffusion coefficient; ADCJZ, ADC value of the junctional zone; ADCOM, ADC value of the outer myometrium; SD, standard deviation; T2JZ, T2 value of the junctional zone; T2OM, T2 value of the outer myometrium.

Discussion

This prospective study demonstrated that patients with endometrial fibrosis exhibited increased JZT, T2JZ, and ADCJZ compared with healthy women. In patients with SEF, OMT, T2OM, and ADCOM were also significantly elevated. T2JZ showed stronger correlations with the degree of endometrial fibrosis compared with other parameters. T2 values, ADC values, and multivariable models based on junctional zone and outer myometrial anatomical parameters showed high diagnostic performance in diagnosing endometrial fibrosis. Moreover, T2 values demonstrated superior reproducibility compared to ADC values.

In the normal junctional zone, relatively low water content and a high cytoplasm-–nucleus ratio result in a dense cellular architecture, producing a short T2 relaxation time and restricted water diffusion (12,16). In the context of endometrial fibrosis, infiltration of inflammatory cells and fibrous tissue deposition within the junctional zone can disrupt its dense cellular architecture (29), increasing free water content and extracellular space. These microstructural alterations of the junctional zone can lead to prolonged T2 relaxation times and enhanced water mobility, resulting in elevated T2JZ and ADCJZ values in patients with endometrial fibrosis as compared with healthy women. Furthermore, anatomical disruption of the subendometrial myometrium can manifest as junctional zone thickening (30), which is consistent with a higher JZT being observed in patients with endometrial fibrosis. In our study, T2JZ was significantly higher in the SEF group than in the MMEF group, whereas ADCJZ and JZT were not significantly different between these groups. This likely suggests that T2 mapping is more sensitive to progressive microstructural disruption of the junctional zone, as it primarily reflects tissue water content. By contrast, ADC values are influenced by multiple factors, including cellular density, extracellular matrix composition, and perfusion effects, which may obscure intergroup differences (31). In addition, the majority of patients with MMEF were considered to have moderate IUAs, which might have weakened the observed differences in junctional zone morphology and microstructural alterations between the MMEF and SEF groups.

Furthermore, we observed that both T2JZ and ADCJZ were positively correlated with the degree of endometrial fibrosis. This indicates that a higher degree of endometrial fibrosis is associated with more severe damage of junctional zone. Lei et al. reported that patients with SEF exhibited a higher percentage of an inhomogeneous endometrial-myometrial junction compared to patients with MMEF (32). Kang et al. discovered that as the degree of endometrial fibrosis increased, the signal intensity of junctional zone on T2WI images increased and became vague and even invisible (33). These findings are consistent with our results. Notably, T2JZ showed a stronger correlation with the degree of endometrial fibrosis than did the other MRI parameters and demonstrated high diagnostic efficacy in distinguishing patients with SEF, patients with MMEF, and healthy women. In addition, the multivariable model incorporating junctional zone T2 values, ADC values, and anatomical parameters demonstrated excellent performance in distinguishing both patients MMEF and those with SEF from healthy women. These findings support the potential advantage of T2 mapping for the quantitative assessment of the junctional zone microstructural alterations associated with endometrial fibrosis. However, adverse reproductive outcomes are multifactorial in nature, and the association between the microstructure changes of the junctional zone and adverse reproductive outcomes should be further investigated in studies with larger sample sizes and long-term follow-up data.

In our study, OMT, T2OM, and ADCOM were significantly higher in patients with SEF than in healthy women, whereas no significant differences were observed for patients with MMEF. This might indicate that patients with SEF exhibit more detectable microstructural and morphological changes of the outer myometrium as compared to those with MMEF.

In contrast to ADC mapping, T2 mapping offers several advantages. First, T2 mapping, acquired with an FSE sequence, provides higher in-plane spatial resolution and a reduction in susceptibility artifacts as compared with EPI-based DWI, enabling clearer delineation of the junctional zone boundary and more accurate ROI placement (18). For the DWI, the ROIs are drawn by comparing the T2WI images of the same section. Second, the T2 mapping protocol we used in our study is readily applicable in clinical settings, as it requires no complex mathematical modeling and can be acquired in a shorter scan time than DWI (34). With the widespread availability of MRI equipment, pelvic MRI has become a routine clinical imaging modality, with its generally acceptable cost facilitating good clinical applicability. Although ultrasound is more affordable, it is limited in its ability to quantitatively assess microstructural changes as compared to MRI. As a quantitative imaging technique, T2 mapping offers a short scan duration and simple image postprocessing. It can be easily integrated into standard MRI protocols without requiring additional hardware. Therefore, T2 mapping can be viably used in clinical practice with relative cost-effectiveness.

This study demonstrated the feasibility of T2 mapping for quantitatively assessing junctional zone alterations in patients with varying degrees of endometrial fibrosis. Our results showed that T2 values were more sensitive than were ADC values in detecting junctional zone abnormalities, highlighting the unique advantage of T2 mapping in reflecting microstructural changes of the junctional zone. Evidence from both animal and human studies indicates that the microstructural disruption of the endometrium-subendometrium myometrial unit (manifesting as thickening and infiltration or disruption of the junctional zone) is associated with impaired fertility (30,35). Therefore, the noninvasive and quantitative assessment of junctional zone microstructure with T2 mapping may serve as a imaging biomarker for evaluating disease severity, guiding follow-up, and monitoring postoperative recovery in patients with endometrial fibrosis.

This study involved several limitations that should be addressed. First, although the feasibility of T2 mapping and DWI for quantitatively assessing junctional zone alterations was demonstrated, the sample size was relatively small. Second, ADC is substantially affected by T2 shine-through, which may partly reflect intrinsic T2 tissue characteristics rather than solely alterations in diffusion (36,37). Future investigations of advanced diffusion models, such as intravoxel incoherent motion, may provide deeper insights into the distinct effects of diffusion and T2-related effects on ADC. Third, as the endometrial fibrosis examined in this study was specifically induced by D&C, the utility of T2 mapping and DWI for evaluating junctional zone changes in patients with endometrial fibrosis resulting from other etiologies remains to be further investigated. Fourth, all MRI scans were performed exclusively during the late proliferative phase of the menstrual cycle, which provides optimal soft tissue contrast and is considered ideal for investigating junctional zone disorders (38). Clinically, this phase also facilitates therapeutic intervention in patients with endometrial fibrosis (39). However, the efficacy of T2 mapping and DWI for assessing junctional zone alterations during other menstrual phases has not been clarified. Finally, interobserver agreement for the AFS scores was not assessed in this study and should be confirmed in future research.


Conclusions

In this prospective study, T2 mapping was found to be a feasible noninvasive technique for quantitatively assessing junctional zone alterations in patients with endometrial fibrosis. Compared with anatomical measurements and ADC values, T2 values of the junctional zone showed stronger correlations with the degree of endometrial fibrosis and better reproducibility. Therefore, T2 mapping has the potential to serve as an incremental imaging biomarker for assessing junctional zone alterations and may support personalized clinical management and dynamic monitoring in patients with endometrial fibrosis.


Acknowledgments

None.


Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2502/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2502/dss

Funding: This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (ID: XDA16040302).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2502/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This prospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Nanjing Drum Tower Hospital (approval No. 2019-051-02) and informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


References

  1. Tanos V, Lingwood L, Balami S. Junctional Zone Endometrium Morphological Characteristics and Functionality: Review of the Literature. Gynecol Obstet Invest 2020;85:107-17. [Crossref] [PubMed]
  2. Tanos V, Lingwood L, Balami S. The importance of the junctional zone of the endometrium in human reproduction. Hum Fertil (Camb) 2022;25:4-12. [Crossref] [PubMed]
  3. Ang CJ, Skokan TD, McKinley KL. Mechanisms of Regeneration and Fibrosis in the Endometrium. Annu Rev Cell Dev Biol 2023;39:197-221. [Crossref] [PubMed]
  4. Wu L, Zhan Y, Wang Y. Semaglutide May Ameliorate Fibrosis and Inhibit Epithelial-Mesenchymal Transition in Intrauterine Adhesion Models. Int J Mol Sci 2024;25:6196. [Crossref] [PubMed]
  5. Jiang P, Tang X, Wang H, Dai C, Su J, Zhu H, Song M, Liu J, Nan Z, Ru T, Li Y, Wang J, Yang J, Chen B, Dai J, Hu Y. Collagen-binding basic fibroblast growth factor improves functional remodeling of scarred endometrium in uterine infertile women: a pilot study. Sci China Life Sci 2019;62:1617-29. [Crossref] [PubMed]
  6. Li W, Gu P, Gao B, Zou L, Zhang A, Huang H, Zhao X, Xu D, Cheng C. Characteristics and transcriptomic analysis of scar tissues on the inner uterine cavity wall in patients with intrauterine adhesions. Front Physiol 2022;13:990009. [Crossref] [PubMed]
  7. Jiao Y, Xue N, Shui X, Yu C, Hu C. Application of ultrasound multimodal score in the assessment of endometrial receptivity in patients with artificial abortion. Insights Imaging 2020;11:29. [Crossref] [PubMed]
  8. Liang H, Zhou N, Chen Y, Sun K, Zhu H, Jiang P, Wang H, Hu Q, Zhou K, Hu Y, Zhou Z. Cine magnetic resonance imaging of uterine peristalsis in patients with endometrial fibrosis. Fertil Steril 2026;125:496-505. [Crossref] [PubMed]
  9. Exacoustos C, Luciano D, Corbett B, De Felice G, Di Feliciantonio M, Luciano A, Zupi E. The uterine junctional zone: a 3-dimensional ultrasound study of patients with endometriosis. Am J Obstet Gynecol 2013;209:248.e1-7. [Crossref] [PubMed]
  10. Bazot M, Cortez A, Darai E, Rouger J, Chopier J, Antoine JM, Uzan S. Ultrasonography compared with magnetic resonance imaging for the diagnosis of adenomyosis: correlation with histopathology. Hum Reprod 2001;16:2427-33. [Crossref] [PubMed]
  11. Harmsen MJ, Trommelen LM, de Leeuw RA, Tellum T, Juffermans LJM, Griffioen AW, Thomassin-Naggara I, van den Bosch T, Huirne JAF. Uterine junctional zone and adenomyosis: comparison of MRI, transvaginal ultrasound and histology. Ultrasound Obstet Gynecol 2023;62:42-60. [Crossref] [PubMed]
  12. McCarthy S, Scott G, Majumdar S, Shapiro B, Thompson S, Lange R, Gore J. Uterine junctional zone: MR study of water content and relaxation properties. Radiology 1989;171:241-3. [Crossref] [PubMed]
  13. Kim PK, Hong YJ. Im DJ, Suh YJ, Park CH, Kim JY, Chang S, Lee HJ, Hur J, Kim YJ, Choi BW. Myocardial T1 and T2 Mapping: Techniques and Clinical Applications. Korean J Radiol 2017;18:113-31. [Crossref] [PubMed]
  14. Duarte-Rojo A, Taouli B, Leung DH, Levine D, Nayfeh T, Hasan B, Alsawaf Y, Saadi S, Majzoub AM, Manolopoulos A, Haffar S, Dundar A, Murad MH, Rockey DC, Alsawas M, Sterling RK. Imaging-based noninvasive liver disease assessment for staging liver fibrosis in chronic liver disease: A systematic review supporting the AASLD Practice Guideline. Hepatology 2025;81:725-48. [Crossref] [PubMed]
  15. Lu Y, Wang Q, Zhang T, Li J, Liu H, Yao D, Hou L, Tu B, Wang D. Staging Liver Fibrosis: Comparison of Native T1 Mapping, T2 Mapping, and T1ρ: An Experimental Study in Rats With Bile Duct Ligation and Carbon Tetrachloride at 11.7 T MRI. J Magn Reson Imaging 2022;55:507-17. [Crossref] [PubMed]
  16. Kilickesmez O, Bayramoglu S, Inci E, Cimilli T, Kayhan A. Quantitative diffusion-weighted magnetic resonance imaging of normal and diseased uterine zones. Acta Radiol 2009;50:340-7. [Crossref] [PubMed]
  17. Jha RC, Zanello PA, Ascher SM, Rajan S. Diffusion-weighted imaging (DWI) of adenomyosis and fibroids of the uterus. Abdom Imaging 2014;39:562-9. [Crossref] [PubMed]
  18. Zhang J, Ge Y, Zhang H, Wang Z, Dou W, Hu S. Quantitative T2 Mapping to Discriminate Mucinous from Nonmucinous Adenocarcinoma in Rectal Cancer: Comparison with Diffusion-weighted Imaging. Magn Reson Med Sci 2022;21:593-8. [Crossref] [PubMed]
  19. Zhou N, Zhu H, Jiang P, Hu Q, Feng Y, Chen W, Zhou K, Hu Y, Zhou Z. Quantification of Endometrial Fibrosis Using Noninvasive MRI T2 Mapping: Initial Findings. J Magn Reson Imaging 2023;58:1703-13. [Crossref] [PubMed]
  20. Ghosh A, Singh T, Bagga R, Srinivasan R, Singla V, Khandelwal N. T2 relaxometry mapping in demonstrating layered uterine architecture: parameter optimization and utility in endometrial carcinoma and adenomyosis: a feasibility study. Br J Radiol 2018;91:20170377. [Crossref] [PubMed]
  21. Zhang Z, Liu J, Wang W, Zhang Y, Qu F, Hilbert T, Kober T, Cheng J, Li S, Zhu J. Feasibility of accelerated T2 mapping for the preoperative assessment of endometrial carcinoma. Front Oncol 2023;13:1117148. [Crossref] [PubMed]
  22. The American Fertility Society classifications of adnexal adhesions, distal tubal occlusion, tubal occlusion secondary to tubal ligation, tubal pregnancies, müllerian anomalies and intrauterine adhesions. Fertil Steril 1988;49:944-55.
  23. Vander Borght M, Wyns C. Fertility and infertility: Definition and epidemiology. Clin Biochem 2018;62:2-10. [Crossref] [PubMed]
  24. Grimbizis GF, Gordts S, Di Spiezio Sardo A, Brucker S, De Angelis C, Gergolet M, Li TC, Tanos V, Brölmann H, Gianaroli L, Campo R. The ESHRE-ESGE consensus on the classification of female genital tract congenital anomalies. Gynecol Surg 2013;10:199-212. [Crossref] [PubMed]
  25. Faul F, Erdfelder E, Lang AG, Buchner A G. *Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007;39:175-91. [Crossref] [PubMed]
  26. He YL, Ding N, Li Y, Li Z, Xiang Y, Jin ZY, Xue HD. Cyclic changes of the junctional zone on 3 T MRI images in young and middle-aged females during the menstrual cycle. Clin Radiol 2016;71:341-8. [Crossref] [PubMed]
  27. Chan YH. Biostatistics 104: correlational analysis. Singapore Med J 2003;44:614-9.
  28. Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1979;86:420-8. [Crossref] [PubMed]
  29. Foix A, Bruno RO, Davison T, Lema B. The pathology of postcurettage intrauterine adhesions. Am J Obstet Gynecol 1966;96:1027-33. [Crossref] [PubMed]
  30. Tocci A, Greco E, Ubaldi FM. Adenomyosis and 'endometrial-subendometrial myometrium unit disruption disease' are two different entities. Reprod Biomed Online 2008;17:281-90.
  31. Ge YX, Hu SD, Wang Z, Guan RP, Zhou XY, Gao QZ, Yan G. Feasibility and reproducibility of T2 mapping and DWI for identifying malignant lymph nodes in rectal cancer. Eur Radiol 2021;31:3347-54. [Crossref] [PubMed]
  32. Lei L, Zou L, Yu Y, Li W, Zhang A, Xu D. A Novel Nomogram Based on 3-dimensional Transvaginal Ultrasound for Differential Diagnosis Between Severe and Mild-to-Moderate Intrauterine Adhesions. J Minim Invasive Gynecol 2022;29:862-70. [Crossref] [PubMed]
  33. Kang K, Wang A, Wu H. MRI for Diagnosing Intrauterine Adhesions. J Obstet Gynaecol Can 2023;45:102168. [Crossref] [PubMed]
  34. Adams LC, Bressem KK, Jurmeister P, Fahlenkamp UL, Ralla B, Engel G, Hamm B, Busch J, Makowski MR. Use of quantitative T2 mapping for the assessment of renal cell carcinomas: first results. Cancer Imaging 2019;19:35. [Crossref] [PubMed]
  35. Meylaerts LJ, Wijnen L, Ombelet W, Bazot M, Vandersteen M. Uterine junctional zone thickness in infertile women evaluated by MRI. J Magn Reson Imaging 2017;45:926-36. [Crossref] [PubMed]
  36. Wáng YXJ, Ma FZ. A tri-phasic relationship between T2 relaxation time and MRI-derived apparent diffusion coefficient (ADC). Quant Imaging Med Surg 2023;13:8873-80. [Crossref] [PubMed]
  37. Wáng YXJ. An explanation for the triphasic dependency of apparent diffusion coefficient (ADC) on T2 relaxation time: the multiple T2 compartments model. Quant Imaging Med Surg 2025;15:3779-91. [Crossref] [PubMed]
  38. He YL, Ding N, Qi YF, Li Y, Xiang Y, Qian TY, Liu H, Lin CY, Yuan L, Zhou HL, Jin ZY, Xue HD. Visualising the boundary sharpness of uterine zonal structures using high-resolution T2-weighted images during the menstrual cycle. Clin Radiol 2019;74:81.e19-24.
  39. Gao Y, Wu G, Xu Y, Zhao D, Zheng L. Stem Cell-Based Therapy for Asherman Syndrome: Promises and Challenges. Cell Transplant 2021;30:9636897211020734. [Crossref] [PubMed]
Cite this article as: Liang H, Sun K, Zhu H, Chen Y, Jiang P, Wang H, Zhou N, Hu Y, Zhou Z, Zhou K. Quantitative T2 mapping of junctional zone alterations in endometrial fibrosis: comparison with diffusion-weighted imaging. Quant Imaging Med Surg 2026;16(7):578. doi: 10.21037/qims-2025-1-2502

Download Citation