Biological Image-Guided Radiotherapy in Rectal Cancer: Challenges and Pitfalls

Roels, Sarah; Slagmolen, Pieter; Nuyts, Johan; Lee, John A.; Loeckx, Dirk; Maes, Frederik; Vandecaveye, Vincent; Stroobants, Sigrid; Ectors, Nadine; Penninckx, Freddy; Haustermans, Karin

doi:10.1016/j.ijrobp.2008.11.031

Cited by 47 publications

(29 citation statements)

References 30 publications

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“…These studies have common steps that are discussed below by tumor location: specimen fixation (for all except one), registration of the specimen with the images, and deformation corrections for some of them (Table 2). Such are the PSPVs generated by Daisne et al [25], Caldas-Magalhaes et al [26], Stroom et al [27], Van Loon et al [28], Yu et al [29], Meng et al [30], Schaefer et al [31], Dahele et al [32], Wanet et al [33], Zhang et al [34], and Roels et al [35]. After this, we provide an overview of the volumetric studies.…”

Section: Available Data Setsmentioning

confidence: 94%

“…Threshold [27-29, 33, 43] Adaptive threshold [12,31,33,52] Gradient [47] Fuzzy C-means [48] Active contours [49] FLAB [54] Neural network [55] Multimodality using level sets [51] Cervical cancer Threshold [34] Colon, rectal and sigmoid cancer Threshold [39,45] Adaptive threshold [35,44] Gradient [35,39] multimodality segmentation tool using level sets and Jensen-Renyi divergence (JRD). They compared the results to those from Zaidi et al [50], and found that the JRD approach was second to the FCM-SW method.…”

Section: Evaluation Of Pet Segmentation Methodsmentioning

confidence: 99%

“…Pathology processing Roels et al [35] put each rectum specimen in a box immediately after extraction; wooden rods were placed inside and around the specimen for orientation and reconstruction purposes. The box was filled with a gelatin solution and stored at -20°C for 2-3 days to freeze it.…”

Section: Rectal Cancermentioning

confidence: 99%

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Pathology-validated PET image data sets and their role in PET segmentation

Kirov

Fanchon

2014

Clin Transl Imaging

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Positron emission tomography (PET)/computed tomography has recently been finding broader application for the diagnosis, treatment and therapy assessment of malignant disease. Accurate definition of the tumor border is extremely important for the success of localized tumor therapies. PET promises to provide the metabolically active tumor volume and, at present, it is used for target definition in a variety of tumors. This process is, however, subject to uncertainties of different origin. Resolving these uncertainties is challenging, since validating PET images and segmentation contours against tumor pathology is experimentally difficult. In addition to accurate lesion contouring, this challenges validation of PET tracers and investigations of tumor functional heterogeneity. In this paper, we briefly review the present studies providing PET image data sets with pathology validation. We focus on the specimen handling techniques aimed at achieving higher geometrical accuracy of the pathology-derived ''ground truth''. We also summarize the main findings obtained for the PET segmentation techniques which have been tested with the help of these data sets. Finally, we provide a critical summary of the current state of the art in pathological validation of PET images and briefly discuss future possibilities in this direction.

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Section: Available Data Setsmentioning

confidence: 94%

Section: Evaluation Of Pet Segmentation Methodsmentioning

confidence: 99%

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Pathology-validated PET image data sets and their role in PET segmentation

Kirov

Fanchon

2014

Clin Transl Imaging

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“…Cannon 20 showed that "Demons"-based deformable registration improved the accuracy, compared with rigid registration, in assessment of tumour response with SUV peak and VOI 50% in head and neck cancer. Roels et al 21 investigated the use of MRI and 18 F-FDG-PET/CT for rectal tumour response to CRT. Images acquired before, during and after CRT from 15 patients were registered using B-spline registration with mutual information as similarity metric.…”

Section: Deformable Registrationmentioning

confidence: 99%

Computerized PET/CT image analysis in the evaluation of tumour response to therapy

Wang²,

Zhang³

2015

BJR

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Current cancer therapy strategy is mostly population based, however, there are large differences in tumour response among patients. It is therefore important for treating physicians to know individual tumour response. In recent years, many studies proposed the use of computerized positron emission tomography/CT image analysis in the evaluation of tumour response. Results showed that computerized analysis overcame some major limitations of current qualitative and semiquantitative analysis and led to improved accuracy. In this review, we summarize these studies in four steps of the analysis: image registration, tumour segmentation, image feature extraction and response evaluation. Future works are proposed and challenges described.

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“…Apart from the various applications of FDG PET/CT listed above, there are many other utilities of FDG PET/CT. For example, it can be used for radiation oncology purposes [9][10][11][12], e.g. by identifying areas with high metabolic activity that may require a boost of radiation to improve treatment outcome.…”

mentioning

confidence: 99%