Jane Shortall

• PhD Cancer Science
• Research Fellow at The University of Manchester

Background and purpose Growing evidence suggests that spatial dose variations across the rectal surface influence toxicity risk after radiotherapy. Existing methodologies employ a fixed, arbitrary physical extent for rectal dose mapping, limiting their analysis. We developed a method to standardise rectum contours, unfold them into 2D cylindrical s...

The value of post Radiotherapy PSA dynamics for prostate cancer risk stratification models

Background: One in three high-risk prostate cancer patients treated with radiotherapy recur. Detection of lymph node metastasis and microscopic disease spread using conventional imaging is poor, and many patients are under-treated due to suboptimal seminal vesicle or lymph node irradiation. We use Image Based Data Mining (IBDM) to investigate asso...

Purpose: To develop a machine learning (ML) model based on radiomic features (RF) extracted from whole prostate gland magnetic resonance imaging (MRI) for prediction of tumour hypoxia pre-radiotherapy. Material and methods: Consecutive patients with high-grade prostate cancer and pre-treatment MRI treated with radiotherapy between 01/12/2007 and...

Purpose/Objective(s) The ability to detect changes during radiotherapy to the prostate with radiomics techniques may allow prediction of clinical outcomes and influence subsequent treatment choices. In this feasibility study, we aimed to assess changes in features (delta-radiomics) across a course of treatment in men undergoing MRI-guided radiother...

Deep learning models are increasingly used to generate synthetic images. Synthetic CTs (sCTs) generated from on-treatment cone-beam CTs (CBCTs) hold potential for adaptive radiotherapy, promising a high-quality representation of daily anatomy without requiring additional imaging or dose to the patient. However, validating sCT is very challenging as...

Contours are used in radiotherapy treatment planning to identify regions to be irradiated with high dose and regions to be spared. Therefore, any contouring uncertainty influences the whole treatment. Even though this is the biggest remaining source of uncertainty when daily IGRT or adaptation is used, it has not been accounted for quantitatively i...

Purpose Due to the electron return effect (ERE) during magnetic resonance imaging guided radiotherapy (MRIgRT), rectal gas during pelvic treatments can result in hot spots of over‐dosage in the rectal wall. Determining the clinical impact of this effect on rectal toxicity requires estimation of the amount and mobility (and stability) of rectal gas...

Purpose Due to differences in attenuation and the electron return effect (ERE), the presence of gas can increase the risk of toxicity in organs at risk (OAR) during magnetic resonance‐guided radiotherapy (MRgRT). Current adaptive MRgRT workflows using density overrides negate gas from the dose calculation, meaning that the effects of ERE around gas...

Purpose Dose deposition around unplanned air cavities during magnetic resonance‐guided radiotherapy (MRgRT) is influenced by the electron return effect (ERE). This is clinically relevant for gas forming close to or inside organs at risk (OARs) that lie in the path of a single beam, for example, intestinal track during pelvic treatment. This work ai...

Purpose It has been proposed that beam modulation and opposing beam configurations can cancel effects of the Electron Return Effect (ERE) during MR‐guided radiotherapy (MRgRT). However, this may not always be the case for unplanned gas cavities outside of the target in the pelvic region. We evaluate dosimetric effects, including effects in the rect...