18F-FDG-PET-based tumor delineation in cervical cancer: threshold contouring and lesion volumes

Concordance of FDG PET/CT metabolic tumour volume versus DW-MRI functional tumour volume with T2-weighted anatomical tumour volume in cervical cancer

Background

¹⁸F–fluoro-deoxyglucose positron emission tomography with computed tomography (FDG PET/CT) has been employed to define radiotherapy targets using a threshold based on the standardised uptake value (SUV), and has been described for use in cervical cancer. The aim of this study was to evaluate the concordance between the metabolic tumour volume (MTV) measured on FDG PET/CT and the anatomical tumour volume (ATV) measured on T2-weighted magnetic resonance imaging (T2W-MRI); and compared with the functional tumour volume (FTV) measured on diffusion-weighted MRI (DW-MRI) in cervical cancer, taking the T2W-ATV as gold standard.

Methods

Consecutive newly diagnosed cervical cancer patients who underwent FDG PET/CT and DW-MRI were retrospectively reviewed from June 2013 to July 2017.

Volumes of interest was inserted to the focal hypermetabolic activity corresponding to the cervical tumour on FDG PET/CT with automated tumour contouring and manual adjustment, based on SUV 20%–80% thresholds of the maximum SUV (SUVmax) to define the MTV_20–80, with intervals of 5%.

Tumour areas were manually delineated on T2W-MRI and multiplied by slice thickness to calculate the ATV.

FTV were derived by manually delineating tumour area on ADC map, multiplied by the slice thickness to determine the FTV_(manual). Diffusion restricted areas was extracted from b0 and ADC map using K-means clustering to determine the FTV_{(semi-automated)}.

The ATVs, FTVs and the MTVs at different thresholds were compared using the mean and correlated using Pearson’s product-moment correlation.

Results

Twenty-nine patients were evaluated (median age 52 years). Paired difference of mean between ATV and MTV was the closest and not statistically significant at MTV₃₀ (−2.9cm³, −5.2%, p = 0.301). This was less than the differences between ATV and FTV_{(semi-automated)} (25.0cm³, 45.1%, p < 0.001) and FTV_(manual) (11.2cm³, 20.1%, p = 0.001). The correlation of MTV₃₀ with ATV was excellent (r = 0.968, p < 0.001) and better than that of the FTVs.

Conclusions

Our study demonstrated that MTV₃₀ was the only parameter investigated with no statistically significant difference with ATV, had the least absolute difference from ATV, and showed excellent positive correlation with ATV, suggesting its superiority as a functional imaging modality when compared with DW-MRI and supporting its use as a surrogate for ATV for radiotherapy tumour contouring.

Adaptive threshold segmentation of pituitary adenomas from FDG PET images for radiosurgery

In this study we have attempted to optimize a PET based adaptive threshold seg- mentation method for delineating small tumors, particularly in a background of high tracer activity. The metabolic nature of pituitary adenomas and the constraints of MRI imaging in the postoperative setting to delineate these tumors during radio- surgical procedures motivated us to develop this method. Phantom experiments were done to establish a relationship between the threshold required for segmenting the PET images and the target size and the activity concentration within the target in relation to its background. The threshold was developed from multiple linear regression of the experimental data optimized for tumor sizes less than 4 cm3. We validated our method against the phantom target volumes with measured target to background ratios ranging from 1.6 to 14.58. The method was tested on ten retro- spective patients with residual growth hormone-secreting pituitary adenomas that underwent radiosurgery and compared against the volumes delineated by manual method. The predicted volumes against the true volume of the phantom inserts gave a correlation coefficient of 99% (p &lt; 0.01). In the ten retrospective patients, the automatically segmented tumor volumes against volumes manually delineated by the clinicians had a correlation of 94% (p &lt; 0.01). This adaptive threshold segmentation showed promising results in delineating tumor volumes in pituitary adenomas planned for stereotactic radiosurgery, particularly in the postoperative setting where MR and CT images may be associated with artifacts, provided opti- mization experiment is carried out.