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ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases—a Preliminary Study

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Abstract

Purpose

Apparent diffusion coefficient (ADC) histogram analysis has been used to some extent in cervical cancer (CC) to distinguish between low-grade and high-grade tumors. Although this differentiation is undoubtedly helpful, it would be even more crucial in the presurgical setting to determine whether a tumor already gained the potential to metastasize via the lymphatic system. So far, no studies investigated the potential of 3T ADC histogram analysis in CC to differentiate between nodal-positive and nodal-negative entities. Therefore, the principal aim of our study was to investigate the potential of 3T ADC histogram analysis to differentiate between CC with and without lymph node metastasis. The second aim was to elucidate possible differences in ADC histogram parameters between CC with limited vs. advanced tumor stages and well-differentiated vs. undifferentiated lesions. Finally, correlations of p53 expression and Ki-67 index with ADC parameters were analyzed.

Procedures

Eighteen female patients (mean age 55.4 years, range 32–79 years) with histopathologically confirmed cervical squamous cell carcinoma of the uterine cervix were prospectively enrolled. Tumor stages, tumor grading, status of metastatic dissemination, Ki67-index, and p53 expression were assessed in these patients. Diffusion weighted imaging (DWI) was obtained in a 3T scanner using the following b values: b0 and b1000 s/mm2.

Results

Group comparisons using Mann-Whitney U test revealed the following findings: nodal-positive CC had statistically significant lower ADC parameters (ADCmin, ADCmean, median ADC, Mode, p10, p25, p75, and p90) in comparison to nodal-negative CC (all p < 0.05). ADCentropy was significantly elevated (p = 0.046) in tumors with advanced T stages (T3/4) compared to tumors with limited T stage (T2). ADCmin values were different in a statistically significant manner comparing G1/G2 and G3 tumors (40.45 ± 18.63 vs. 65.0 ± 23.63 × 10–5 mm2 s−1, p = 0.035). Furthermore, Spearman Rho calculation identified an inverse correlation between ADCentropy and p53 expression (r = −0.472, p = 0.048).

Conclusion

The main finding of our study is the discriminability of nodal-positive from nodal-negative CC using ADC histogram analysis in 3T DWI. This information is crucial for the gynecological surgeon to identify the optimal treatment strategy for patients suffering from CC. Furthermore, ADCentropy was identified as a potential imaging biomarker for tumor heterogeneity and might be able to indicate further molecular changes like loss of p53 expression, which is associated with EMT and consequentially indicates a poor prognosis in CC. Finally, our study confirmed the findings of previous works, which indicated that histogram analysis of ADC maps can distinguish between low-grade and high-grade CC. In conclusion, it can be stated that ADC histogram analysis provides additional, prognostically important information on tumor biology in CC.

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Authors and Affiliations

  1. Department of Neuroradiology, University Hospital Leipzig, Liebigstraße 20, 04103, Leipzig, Germany

    Stefan Schob

  2. Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany

    Hans Jonas Meyer, Kristina Bremicker, Marc Exner, Nikita Garnov & Alexey Surov

  3. Department of Pathology, Martin Luther University, Halle-Wittenberg, Germany

    Nikolaos Pazaitis

  4. Department of Radiology, Martin Luther University, Halle-Wittenberg, Germany

    Dominik Schramm

  5. Department of Pathology, University of Leipzig, Leipzig, Germany

    Anne Kathrin Höhn

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  1. Stefan Schob
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  2. Hans Jonas Meyer
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  4. Dominik Schramm
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  9. Alexey Surov
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Correspondence to Stefan Schob.

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The authors declare that they have no conflict of interest.

Additional information

Stefan Schob and Hans Jonas Meyer contributed equally to the paper.

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Schob, S., Meyer, H.J., Pazaitis, N. et al. ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases—a Preliminary Study. Mol Imaging Biol 19, 953–962 (2017). https://doi.org/10.1007/s11307-017-1073-y

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  • DOI: https://doi.org/10.1007/s11307-017-1073-y

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