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Evaluating microstructures in endometrial cancer using diffusion‐relaxation correlated spectroscopic imaging: Histopathological correlations.

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Title: Evaluating microstructures in endometrial cancer using diffusion‐relaxation correlated spectroscopic imaging: Histopathological correlations.
Authors: Dai, Yongming1 (AUTHOR), Shi, Gaofeng2 (AUTHOR), Hu, Wentao3 (AUTHOR), Yang, Tianshu3 (AUTHOR), Wu, Dongmei4 (AUTHOR), Zhuang, Zhiguo3 (AUTHOR), Song, Mengyu2 (AUTHOR), Wang, Yaning2 (AUTHOR), Cai, Xiaojia2 (AUTHOR), Li, Muzi5 (AUTHOR), Zhai, Yingmin2 (AUTHOR) zhaiyingminct@163.com, Hu, Peng1 (AUTHOR) hupeng_bme@163.com
Source: Medical Physics. Jun2025, Vol. 52 Issue 6, p4443-4453. 11p.
Subjects: Endometrial cancer, Spectroscopic imaging, Tumors, Microstructure, Cell anatomy, Evaluation research, Magnetic resonance imaging, Lymphatic metastasis
Abstract: Background: Endometrial cancer (EC) is a prevalent gynecologic malignancy where accurate grading and assessment are crucial for determining prognosis and treatment strategies. Conventional MRI techniques, including apparent diffusion coefficient (ADC) and T2‐weighted imaging, often fail to capture the detailed microstructural complexities of EC. Purpose: To evaluate the efficacy of diffusion relaxation correlated spectroscopic imaging (DR‐CSI) in assessing EC and to compare its diagnostic performance with conventional ADC and T2‐weighted imaging. Materials and Methods: Sixty‐two patients with histopathologically confirmed EC were included in this prospective study. All patients underwent preoperative MRI, including DR‐CSI using a multi‐TE (50–90 ms) and multi‐b‐value (0–1600 s/mm2) echo‐planar imaging sequence. The DR‐CSI data were analyzed to generate a four‐compartment D‐T2 spectra, yielding corresponding volume fraction metrics (VF, I–IV). Voxel‐wise ADC and T2 values were also obtained. The relationships between these imaging parameters and histopathologic results were evaluated using one‐way ANOVA or Kruskal–Wallis tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Results: VFII and VFIII demonstrated significant differences across histological grades (p < 0.01 and p = 0.04, respectively). The combination of VFII and VFIII provided optimal differentiation between low‐ and high‐grade EC (Area under curve, AUC 0.801 [95% confidence interval: 0.623–0.937]). VFIV exhibited superior performance in distinguishing lymph node metastasis (LNM) status (AUC 0.734 [0.556–0.892]). The combination of VFIV and VFII improved performance in predicting LNM status (AUC 0.826 [0.66–0.961]). However, no parameter alone effectively distinguished myometrial invasion (MI) statuses, but the combination of VFI and ADC improved performance (AUC 0.706 [0.560–0.844]). Conclusion: DR‐CSI offers a novel and effective method for quantifying microstructural compartments in EC, providing superior diagnostic accuracy compared to conventional ADC and T2 values. The ability to capture detailed microstructural information from DR‐CSI metrics holds promise for improving EC diagnosis and grading, offering deeper insights into tumor heterogeneity. [ABSTRACT FROM AUTHOR]
Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Evaluating microstructures in endometrial cancer using diffusion‐relaxation correlated spectroscopic imaging: Histopathological correlations.
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  Data: &lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Dai%2C+Yongming%22&quot;&gt;Dai, Yongming&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Shi%2C+Gaofeng%22&quot;&gt;Shi, Gaofeng&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Hu%2C+Wentao%22&quot;&gt;Hu, Wentao&lt;/searchLink&gt;&lt;relatesTo&gt;3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Yang%2C+Tianshu%22&quot;&gt;Yang, Tianshu&lt;/searchLink&gt;&lt;relatesTo&gt;3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Wu%2C+Dongmei%22&quot;&gt;Wu, Dongmei&lt;/searchLink&gt;&lt;relatesTo&gt;4&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Zhuang%2C+Zhiguo%22&quot;&gt;Zhuang, Zhiguo&lt;/searchLink&gt;&lt;relatesTo&gt;3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Song%2C+Mengyu%22&quot;&gt;Song, Mengyu&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Wang%2C+Yaning%22&quot;&gt;Wang, Yaning&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Cai%2C+Xiaojia%22&quot;&gt;Cai, Xiaojia&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Li%2C+Muzi%22&quot;&gt;Li, Muzi&lt;/searchLink&gt;&lt;relatesTo&gt;5&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Zhai%2C+Yingmin%22&quot;&gt;Zhai, Yingmin&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;i&gt; zhaiyingminct@163.com&lt;/i&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Hu%2C+Peng%22&quot;&gt;Hu, Peng&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;i&gt; hupeng_bme@163.com&lt;/i&gt;
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22Medical+Physics%22&quot;&gt;Medical Physics&lt;/searchLink&gt;. Jun2025, Vol. 52 Issue 6, p4443-4453. 11p.
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– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Endometrial cancer (EC) is a prevalent gynecologic malignancy where accurate grading and assessment are crucial for determining prognosis and treatment strategies. Conventional MRI techniques, including apparent diffusion coefficient (ADC) and T2‐weighted imaging, often fail to capture the detailed microstructural complexities of EC. Purpose: To evaluate the efficacy of diffusion relaxation correlated spectroscopic imaging (DR‐CSI) in assessing EC and to compare its diagnostic performance with conventional ADC and T2‐weighted imaging. Materials and Methods: Sixty‐two patients with histopathologically confirmed EC were included in this prospective study. All patients underwent preoperative MRI, including DR‐CSI using a multi‐TE (50–90 ms) and multi‐b‐value (0–1600 s/mm2) echo‐planar imaging sequence. The DR‐CSI data were analyzed to generate a four‐compartment D‐T2 spectra, yielding corresponding volume fraction metrics (VF, I–IV). Voxel‐wise ADC and T2 values were also obtained. The relationships between these imaging parameters and histopathologic results were evaluated using one‐way ANOVA or Kruskal–Wallis tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Results: VFII and VFIII demonstrated significant differences across histological grades (p &lt; 0.01 and p = 0.04, respectively). The combination of VFII and VFIII provided optimal differentiation between low‐ and high‐grade EC (Area under curve, AUC 0.801 [95% confidence interval: 0.623–0.937]). VFIV exhibited superior performance in distinguishing lymph node metastasis (LNM) status (AUC 0.734 [0.556–0.892]). The combination of VFIV and VFII improved performance in predicting LNM status (AUC 0.826 [0.66–0.961]). However, no parameter alone effectively distinguished myometrial invasion (MI) statuses, but the combination of VFI and ADC improved performance (AUC 0.706 [0.560–0.844]). Conclusion: DR‐CSI offers a novel and effective method for quantifying microstructural compartments in EC, providing superior diagnostic accuracy compared to conventional ADC and T2 values. The ability to capture detailed microstructural information from DR‐CSI metrics holds promise for improving EC diagnosis and grading, offering deeper insights into tumor heterogeneity. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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        Value: 10.1002/mp.17768
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        Text: English
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        PageCount: 11
        StartPage: 4443
    Subjects:
      – SubjectFull: Endometrial cancer
        Type: general
      – SubjectFull: Spectroscopic imaging
        Type: general
      – SubjectFull: Tumors
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      – SubjectFull: Microstructure
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      – SubjectFull: Magnetic resonance imaging
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      – SubjectFull: Lymphatic metastasis
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      – TitleFull: Evaluating microstructures in endometrial cancer using diffusion‐relaxation correlated spectroscopic imaging: Histopathological correlations.
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              M: 06
              Text: Jun2025
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              Y: 2025
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