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Mohamed ASR, Abusaif A, He R, Wahid KA, Salama V, Youssef S, McDonald BA, Naser M, Ding Y, Salzillo TC, AboBakr MA, Wang J, Lai SY, Fuller CD. Prospective validation of diffusion-weighted MRI as a biomarker of tumor response and oncologic outcomes in head and neck cancer: Results from an observational biomarker pre-qualification study. Radiother Oncol 2023; 183:109641. [PMID: 36990394 PMCID: PMC10848569 DOI: 10.1016/j.radonc.2023.109641] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 03/17/2023] [Accepted: 03/21/2023] [Indexed: 03/29/2023]
Abstract
PURPOSE To determine DWI parameters associated with tumor response and oncologic outcomes in head and neck (HNC) patients treated with radiotherapy (RT). METHODS HNC patients in a prospective study were included. Patients had MRIs pre-, mid-, and post-RT completion. We used T2-weighted sequences for tumor segmentation which were co-registered to respective DWIs for extraction of apparent diffusion coefficient (ADC) measurements. Treatment response was assessed at mid- and post-RT and was defined as: complete response (CR) vs. non-complete response (non-CR). The Mann-Whitney U test was used to compare ADC between CR and non-CR. Recursive partitioning analysis (RPA) was performed to identify ADC threshold associated with relapse. Cox proportional hazards models were done for clinical vs. clinical and imaging parameters and internal validation was done using bootstrapping technique. RESULTS Eighty-one patients were included. Median follow-up was 31 months. For patients with post-RT CR, there was a significant increase in mean ADC at mid-RT compared to baseline ((1.8 ± 0.29) × 10-3 mm2/s vs. (1.37 ± 0.22) × 10-3 mm2/s, p < 0.0001), while patients with non-CR had no significant increase (p > 0.05). RPA identified GTV-P delta (Δ)ADCmean < 7% at mid-RT as the most significant parameter associated with worse LC and RFS (p = 0.01). Uni- and multi-variable analysis showed that GTV-P ΔADCmean at mid-RT ≥ 7% was significantly associated with better LC and RFS. The addition of ΔADCmean significantly improved the c-indices of LC and RFS models compared with standard clinical variables (0.85 vs. 0.77 and 0.74 vs. 0.68 for LC and RFS, respectively, p < 0.0001 for both). CONCLUSION ΔADCmean at mid-RT is a strong predictor of oncologic outcomes in HNC. Patients with no significant increase of primary tumor ADC at mid-RT are at high risk of disease relapse.
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Affiliation(s)
- Abdallah S R Mohamed
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
| | - Abdelrahman Abusaif
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Renjie He
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Kareem A Wahid
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA
| | - Vivian Salama
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA
| | - Sara Youssef
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Brigid A McDonald
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA
| | - Mohamed Naser
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Yao Ding
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Travis C Salzillo
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Moamen A AboBakr
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Jihong Wang
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Stephen Y Lai
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA; Department of Head and Neck Surgery, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
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