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Predicting locally advanced rectal cancer response to neoadjuvant therapy with 18F-FDG PET and MRI radiomics features

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Abstract

Purpose

Pathological complete response (pCR) following neoadjuvant chemoradiotherapy or radiotherapy in locally advanced rectal cancer (LARC) is reached in approximately 15–30% of cases, therefore it would be useful to assess if pretreatment of 18F-FDG PET/CT and/or MRI texture features can reliably predict response to neoadjuvant therapy in LARC.

Methods

Fifty-two patients were dichotomized as responder (pR+) or non-responder (pR-) according to their pathological tumor regression grade (TRG) as follows: 22 as pR+ (nine with TRG = 1, 13 with TRG = 2) and 30 as pR- (16 with TRG = 3, 13 with TRG = 4 and 1 with TRG = 5). First-order parameters and 21 second-order texture parameters derived from the Gray-Level Co-Occurrence matrix were extracted from semi-automatically segmented tumors on T2w MRI, ADC maps, and PET/CT acquisitions. The role of each texture feature in predicting pR+ was assessed with monoparametric and multiparametric models.

Results

In the mono-parametric approach, PET homogeneity reached the maximum AUC (0.77; sensitivity = 72.7% and specificity = 76.7%), while PET glycolytic volume and ADC dissimilarity reached the highest sensitivity (both 90.9%). In the multiparametric analysis, a logistic regression model containing six second-order texture features (five from PET and one from T2w MRI) yields the highest predictivity in distinguish between pR+ and pR- patients (AUC = 0.86; sensitivity = 86%, and specificity = 83% at the Youden index).

Conclusions

If preliminary results of this study are confirmed, pretreatment PET and MRI could be useful to personalize patient treatment, e.g., avoiding toxicity of neoadjuvant therapy in patients predicted pR-.

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Funding

This work was funded by “AIRC 5xmille Special Program Molecular Clinical Oncology - Ref. 9970” and “FPRC 5xmille 2013 Ministero Salute”.

Author information

Authors and Affiliations

  1. Imaging Unit, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142 km 3.95, 10060, Candiolo, TO, Italy

    V. Giannini, S. Mazzetti, I. Bertotto, C. Chiarenza & D. Regge

  2. Department of Surgical Sciences, University of Turin, 10124, Turin, Italy

    V. Giannini, S. Mazzetti & D. Regge

  3. Nuclear Medicine Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy

    S. Cauda

  4. Radiation Therapy Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy

    E. Delmastro

  5. Medical Physics Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy

    C. Bracco, A. Di Dia & M. Stasi

  6. Medical Oncology Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy

    F. Leone

  7. Laboratory of Oncogenomics, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy

    E. Medico

  8. Pathology Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy

    A. Pisacane

  9. Hepatobilio-Pancreatic and Colorectal Surgery Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy

    D. Ribero

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  1. V. Giannini
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Correspondence to V. Giannini.

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Giannini, V., Mazzetti, S., Bertotto, I. et al. Predicting locally advanced rectal cancer response to neoadjuvant therapy with 18F-FDG PET and MRI radiomics features. Eur J Nucl Med Mol Imaging 46, 878–888 (2019). https://doi.org/10.1007/s00259-018-4250-6

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  • DOI: https://doi.org/10.1007/s00259-018-4250-6

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