Laura M. O'COnnor

Accurately defining gross tumour volume (GTV) and organs at risk (OAR) is key to successful radiation therapy (RT) treatment outcomes for patients with gynaecological cancers. With improved access to magnetic resonance imaging (MRI) for RT simulation and planning, the optimisation and tailoring of proven diagnostic MRI techniques towards RT specific planning goals is fast evolving. Modifying MRI techniques for radiation oncology (RO) with the priority of anatomy visualisation and spatial location over diagnosis and disease characterisation relies heavily on successful collaboration between radiology and radiation oncology staff. This 'How I Do It' paper describes a qualitative analysis of the adaptation of a diagnostic MRI vaginal opacification technique into an RT specific MRI simulation procedure using aqueous ultrasound gel for improving natural anatomical visualisation of the vaginal canal. This technique is explained and could be introduced in other RO departments for dedicated RT planning scans in MR-Sim sessions with minimal difficulty. We found 10-15 cc of aqueous gel delivered vaginally produced optimal MRI planning images for most patients. With this small amount of gel and careful application technique, the full extent of the vaginal vault and cervix can be well visualised on T2 Weighted (T2W) imaging, while tending not to unfold the natural fornices of the collapsed vagina, representing a significant improvement in image quality from the outdated tampon procedure. This 'How I Do It' paper describes the adaptation of a proven diagnostic magnetic resonance imaging (MRI) technique into a radiation therapy (RT) specific MRI simulation procedure. This well-tolerated technique could be easily introduced in other radiation oncology departments for dedicated RT planning scans with minimal difficulty and is an example of the successful collaborations between radiographers and radiation therapists showcasing effective knowledge sharing and skill pooling.image

Introduction: Magnetic resonance imaging (MRI) is being increasingly used to improve radiation therapy planning by allowing visualisation of organs at risk that cannot be well‐defined on computed tomography (CT). Diagnostic sequences are increasingly being adapted for radiation therapy planning, such as the use of heavily T2‐weighted 3D SPACE (Sampling Perfection with Application optimised Contrasts using different flip angle Evolution) sequence for cranial nerve identification in head and neck tumour treatment planning.Methods: A 3D isotropic T2 SPACE sequence used for cranial nerve identification was adapted for radiation therapy purposes. Distortion was minimised using a spin‐echo‐based sequence, 3D distortion correction, isocentre scanning and an increased readout bandwidth. Radiation therapy positioning was accounted for by utilising two small flex, 4‐channel coils. The protocol was validated for cranial nerve identification in clinical applications and distortion minimisation using an MRI QA phantom.Results: Normal anatomy of the cranial nerves CI‐CIX, were presented, along with a selection of clinical applications and abnormal anatomy. The usefulness of cranial nerve identification is discussed for several case studies, particularly in proximity to tumours extending into the base of skull region. In‐house testing validated that higher bandwidths of 600 Hz resulted in minimal displacement well below 1 mm.Conclusion: The use of MRI for radiation therapy planning allows for greater individualisation and prediction of patient outcomes. Dose reduction to cranial nerves can decrease late side effects such as cranial neuropathy. In addition to current applications, future directions include further applications of this technology for radiation therapy treatments.

Purpose: Previous work on Magnetic Resonance Imaging (MRI) only planning has been applied to limited treatment regions with a focus on male anatomy. This research aimed to validate the use of a hybrid multi-atlas synthetic computed tomography (sCT) generation technique from a MRI, using a female and male atlas, for MRI only radiation therapy treatment planning of rectum, anal canal, cervix and endometrial malignancies. Patients and methods: Forty patients receiving radiation treatment for a range of pelvic malignancies, were separated into male (n = 20) and female (n = 20) cohorts for the creation of gender specific atlases. A multi-atlas local weighted voting method was used to generate a sCT from a T1-weighted VIBE DIXON MRI sequence. The original treatment plans were copied from the CT scan to the corresponding sCT for dosimetric validation. Results: The median percentage dose difference between the treatment plan on the CT and sCT at the ICRU reference point for the male cohort was − 0.4% (IQR of 0 to − 0.6), and − 0.3% (IQR of 0 to − 0.6) for the female cohort. The mean gamma agreement for both cohorts was > 99% for criteria of 3%/2 mm and 2%/2 mm. With dose criteria of 1%/1 mm, the pass rate was higher for the male cohort at 96.3% than the female cohort at 93.4%. MRI to sCT anatomical agreement for bone and body delineated contours was assessed, with a resulting Dice score of 0.91 ± 0.2 (mean ± 1 SD) and 0.97 ± 0.0 for the male cohort respectively; and 0.96 ± 0.0 and 0.98 ± 0.0 for the female cohort respectively. The mean absolute error in Hounsfield units (HUs) within the entire body for the male and female cohorts was 59.1 HU ± 7.2 HU and 53.3 HU ± 8.9 HU respectively. Conclusions: A multi-atlas based method for sCT generation can be applied to a standard T1-weighted MRI sequence for male and female pelvic patients. The implications of this study support MRI only planning being applied more broadly for both male and female pelvic sites. Trial registration This trial was registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) (www.anzctr.org.au) on 04/10/2017. Trial identifier ACTRN12617001406392.

Purpose: There are several means of synthetic computed tomography (sCT) generation for magnetic resonance imaging (MRI)-only planning; however, much of the research omits large pelvic treatment regions and female anatomical specific methods. This research aimed to apply four of the most popular methods of sCT creation to facilitate MRI-only radiotherapy treatment planning for male and female anorectal and gynecological neoplasms. sCT methods were validated against conventional computed tomography (CT), with regard to Hounsfield unit (HU) estimation and plan dosimetry.Methods and Materials: Paired MRI and CT scans of 40 patients were used for sCT generation and validation. Bulk density assignment, tissue class density assignment, hybrid atlas, and deep learning sCT generation methods were applied to all 40 patients. Dosimetric accuracy was assessed by dose difference at reference point, dose volume histogram (DVH) parameters, and 3D gamma dose comparison. HU estimation was assessed by mean error and mean absolute error in HU value between each sCT and CT.Results: The median percentage dose difference between the CT and sCT was <1.0% for all sCT methods. The deep learning method resulted in the lowest median percentage dose difference to CT at −0.03% (IQR 0.13, −0.31) and bulk density assignment resulted in the greatest difference at −0.73% (IQR −0.10, −1.01). The mean 3D gamma dose agreement at 3%/2 mm among all sCT methods was 99.8%. The highest agreement at 1%/1 mm was 97.3% for the deep learning method and the lowest was 93.6% for the bulk density method. Deep learning and hybrid atlas techniques gave the lowest difference to CT in mean error and mean absolute error in HU estimation.Conclusions: All methods of sCT generation used in this study resulted in similarly high dosimetric agreement for MRI-only planning of male and female cancer pelvic regions. The choice of the sCT generation technique can be guided by department resources available and image guidance considerations, with minimal impact on dosimetric accuracy.

Deformable image registration is an increasingly important method to account for soft tissue deformation between image acquisitions. This editorial discusses the clinical need and current status of deformable image registration.