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Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters

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Abstract

Purpose

To assess preoperative short-course radiotherapy (SCR) tumor response in locally advanced rectal cancer (LARC) by means of Standardized Index of Shape (SIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters derived from diffusion-weighted MRI (DW-MRI).

Materials and methods

Thirty-four patients with LARC who underwent MRI scans before and after SCR followed by delayed surgery, retrospectively, were enrolled. SIS, ADC, IVIM parameters [tissue diffusion (Dt), pseudo-diffusion (Dp), perfusion fraction (fp)] and DKI parameters [mean diffusivity (MD), mean of diffusional kurtosis (MK)] were calculated for each patient. IVIM parameters were estimated using two methods, namely conventional biexponential fitting (CBFM) and variable projection (VARPRO). After surgery, the pathological TNM and tumor regression grade (TRG) were estimated. For each parameter, percentage changes between before and after SCR were evaluated. Furthermore, an artificial neural network was trained for outcome prediction. Nonparametric sample tests and receiver operating characteristic curve (ROC) analysis were performed.

Results

Fifteen patients were classified as responders (TRG ≤ 2) and 19 as not responders (TRG > 3). Seven patients had TRG 1 (pathological complete response, pCR). Mean and standard deviation values of pre-treatment CBFM Dp and mean value of VARPRO Dp pre-treatment showed statistically significant differences to predict pCR. (p value at Mann–Whitney test was 0.05, 0.03 and 0.008, respectively.) Exclusively SIS percentage change showed significant differences between responder and non-responder patients after SCR (p value << 0.001) and to assess pCR after SCR (p value << 0.001). The best results to predict pCR were obtained by VARPRO Fp mean value pre-treatment with area under ROC of 0.84, a sensitivity of 96.4%, a specificity of 71.4%, a positive predictive value (PPV) of 92.9%, a negative predictive value (NPV) of 83.3% and an accuracy of 91.2%. The best results to assess after treatment complete pathological response were obtained by SIS with an area under ROC of 0.89, a sensitivity of 85.7%, a specificity of 92.6%, a PPV of 75.0%, a NPV of 96.1% and an accuracy of 91.2%. Moreover, the best results to differentiate after treatment responders vs. non-responders were obtained by SIS with an area under ROC of 0.94, a sensitivity of 93.3%, a specificity of 84.2%, a PPV of 82.4%, a NPV of 94.1% and an accuracy of 88.2%. Promising initial results were obtained using a decision tree tested with all ADC, IVIM and DKI extracted parameter: we reached high accuracy to assess pathological complete response after SCR in LARC (an accuracy of 85.3% to assess pathological complete response after SCR using VARPRO Dp mean value post-treatment, ADC standard deviation value pre-treatment, MD standard deviation value post-treatment).

Conclusion

SIS is a hopeful DCE-MRI angiogenic biomarker to assess preoperative treatment response after SCR with delayed surgery. Furthermore, an important prognostic role was obtained by VARPRO Fp mean value pre-treatment and by a decision tree composed by diffusion parameters derived by DWI and DKI to assess pathological complete response.

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Data availability

All data were present in the text of manuscript.

Abbreviations

AUC:

Area under ROC curve

CTV:

Clinical target volume

CT:

Computed tomography

CBFM:

Conventional biexponential fitting

DCE-MRI:

Dynamic contrast-enhanced magnetic resonance imaging

DWI:

Diffusion-weighted imaging

DKI:

Diffusion kurtosis imaging

D t :

Tissue diffusion

D p :

Pseudo-diffusion

f p :

Perfusion fraction

IMRT:

Intensity-modulated radiation therapy

IVIM:

Intravoxel incoherent motion

LARC:

Locally advanced rectal cancer

MD:

Mean diffusivity

MK:

Mean of diffusional kurtosis

MLC:

Multileaf collimators

MSD:

Maximum signal difference

NPV:

Negative predictive value

pCR:

pathological complete response

pCRT:

Preoperative chemo-radiation therapy

PPV:

Positive predictive value

ROC:

RECEIVER operating characteristic

ROI:

Regions of interest

SCR:

Short-course radiotherapy

SCRDS:

Short-course radiotherapy with delayed surgery

SIS:

Standardized Index of Shape

TRG:

Tumor regression grade

WOS:

Washout slope

VARPRO:

Variable projection

VOI:

Volume of interest

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Acknowledgements

Writing/editorial support in the preparation of this manuscript was provided by Di Giovanni Manuela, University of Technology, Sydney, Australia.

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Authors and Affiliations

  1. Division of Radiology, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Via Mariano Semmola, 80131, Naples, Italy

    Roberta Fusco, Vincenza Granata & Antonella Petrillo

  2. Department of Electrical Engineering and Information Technologies (DIETI), Via Claudio 21, 80125, Naples, Italy

    Mario Sansone

  3. Siemens Healthcare GmbH, Erlangen, Germany

    Robert Grimm

  4. Division of Gastrointestinal Surgical Oncology, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Via Mariano Semmola, 80131, Naples, Italy

    Ugo Pace & Paolo Delrio

  5. Division of Diagnostic Pathology, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Via Mariano Semmola, 80131, Naples, Italy

    Fabiana Tatangelo & Gerardo Botti

  6. Division of Gastrointestinal Medical Oncology, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Via Mariano Semmola, 80131, Naples, Italy

    Antonio Avallone

  7. Division of Radiotherapy, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Via Mariano Semmola, 80131, Naples, Italy

    Biagio Pecori

Authors
  1. Roberta Fusco
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  2. Mario Sansone
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  3. Vincenza Granata
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  4. Robert Grimm
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  11. Antonella Petrillo
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Contributions

All authors contributed to this work for patient’s enrollment, diagnostic and therapeutic procedures. RF performed image post-processing, statistical analysis and manuscript editing.

Corresponding author

Correspondence to Roberta Fusco.

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No funding.

Conflict of interest

Each author declares that has no conflict of interest. Exclusively Robert Grimm (Robert.grimm@siemens.com) is an employee of Siemens Healthcare for development of the MR Body Diffusion Toolbox, a post-processing software to calculate IVIM and Kurtosis maps.

Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent was obtained from all individual participants included in the study.

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Consent was obtained from all individual participants included in the study.

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Fusco, R., Sansone, M., Granata, V. et al. Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters. Abdom Radiol 44, 3683–3700 (2019). https://doi.org/10.1007/s00261-018-1801-z

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