A robust semi-automatic delineation workflow using denoised diffusion weighted magnetic resonance imaging for response assessment of patients with esophageal cancer treated with neoadjuvant chemoradiotherapy

Background and Purpose

Diffusion weighted magnetic resonance imaging (DW-MRI) can be prognostic for response to neoadjuvant chemotherapy (nCRT) in patients with esophageal cancer. However, manual tumor delineation is labor intensive and subjective. Furthermore, noise in DW-MRI images will propagate into the corresponding apparent diffusion coefficient (ADC) signal. In this study a workflow is investigated that combines a denoising algorithm with semi-automatic segmentation for quantifying ADC changes.

Materials and Methods

Twenty patients with esophageal cancer who underwent nCRT before esophagectomy were included. One baseline and five weekly DW-MRI scans were acquired for every patient during nCRT. A self-supervised learning denoising algorithm, Patch2Self, was used to denoise the DWI-MRI images. A semi-automatic delineation workflow (SADW) was next developed and compared with a manually adjusted workflow (MAW). The agreement between workflows was determined using the Dice coefficients and Brand Altman plots. The prognostic value of ADCmean increases (%/week) for pathologic complete response (pCR) was assessed using c-statistics.

Results

The median Dice coefficient between the SADW and MAW was 0.64 (interquartile range 0.20). For the MAW, the c-statistic for predicting pCR was 0.80 (95% confidence interval (CI):0.56-1.00). The SADW showed a c-statistic of 0.84 (95%CI:0.63-1.00) after denoising. No statistically significant differences in c-statistics were observed between the workflows or after applying denoising.

Conclusions

The SADW resulted in non-inferior prognostic value for pCR compared to the more laborious MAW, allowing broad scale applications. The effect of denoising on the prognostic value for pCR needs to be investigated in larger cohorts.

Online Magnetic Resonance-Guided Radiotherapy (oMRgRT) for Gynecological Cancers

Radiation therapy (RT) is increasingly being used in gynecological cancer management. RT delivered with curative or palliative intent can be administered alone or combined with chemotherapy or surgery. Advanced treatment planning and delivery techniques such as intensity-modulated radiation therapy, including volumetric modulated arc therapy, and image-guided adaptive brachytherapy allow for highly conformal radiation dose delivery leading to improved tumor control rates and less treatment toxicity. Quality on-board imaging that provides accurate visualization of target and surrounding organs at risk is a critical feature of these advanced techniques. As soft tissue contrast resolution is superior with magnetic resonance imaging (MRI) compared to other imaging modalities, MRI has been used increasingly to delineate tumor from adjacent soft tissues and organs at risk from initial diagnosis to tumor response evaluation. Gynecological cancers often have poor contrast resolution compared to the surrounding tissues on computed tomography scan, and consequently the benefit of MRI is high. One example is in management of locally advanced cervix cancer where adaptive MRI guidance has been broadly implemented for adaptive brachytherapy. The role of MRI for external beam RT is also steadily increasing. MRI information is being used for treatment planning, predicting, and monitoring position shifts and accounting for tissue deformation and target regression during treatment. The recent clinical introduction of online MRI-guided radiation therapy (oMRgRT) could be the next step in high-precision RT. This technology provides a tool to take full advantage of MRI not only at the time of initial treatment planning but as well as for daily position verification and online plan adaptation. Cervical, endometrial, vaginal, and oligometastatic ovarian cancers are being treated on MRI linear accelerator systems throughout the world. This review summarizes the current state, early experience, ongoing trials, and future directions of oMRgRT in the management of gynecological cancers.

An in-silico assessment of the dosimetric benefits of MR-guided radiotherapy for esophageal cancer patients

PURPOSE

To assess the dosimetric benefits of online MR-guided radiotherapy (MRgRT) for esophageal cancer patients and to assess how these benefits could be translated into a local boosting strategy to improve future outcomes.

METHODS

Twenty-nine patients were in-silico treated with both a MRgRT regimen and a conventional image guided radiotherapy (IGRT) regimen using dose warping techniques. Here, the inter and intrafractional changes that occur over the course of treatment (as derived from 5 MRI scans that were acquired weekly during treatment) were incorporated to assess the total accumulated dose for each regimen.

RESULTS

A significant reduction in dose to the organs-at-risk (OARs) was observed for all dose-volume-histogram (DVH) parameters for the MRgRT regimen without concessions to target coverage compared to the IGRT regimen. The mean lung dose was reduced by 28%, from 7.9 to 5.7 Gy respectively and V20Gy of the lungs was reduced by 55% (6.3-2.8%). A reduction of 24% was seen in mean heart dose (14.8-11.2 Gy), while the V25Gy of the heart was decreased by 53% (14.3-6.7%) and the V40Gy of the heart was decreased by 69% (3.9-1.2%). In addition, MRgRT dose escalation regimens with a boost up to 66% of the prescription dose to the primary tumor yielded approximately the same dose levels to the OARs as from the conventional IGRT regimen.

CONCLUSION

This study revealed that MRgRT for esophageal cancer has the potential to significantly reduce the dose to heart and lungs. In addition, online high precision targeting of the primary tumor opens new perspectives for local boosting strategies to improve outcome of the local management of this disease.