Fundamentals of Radiation Oncology for Neurologic Imaging

Mendel, Jameson T.; Jaster, Adam W.; Yu, Fang; Morris, Lee C.; Lynch, P.; Shah, Bhavya; Agarwal, Amit Kumar; Timmerman, Robert; Nedzi, Lucien A.; Raj, Karuna M.

doi:10.1148/rg.2020190138

Cited by 11 publications

(7 citation statements)

References 118 publications

(136 reference statements)

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“…Another consideration is the identification of best MR modality for fusion that yields highest accuracy. While T1 weighted images and CT are considered the best for visualizing interstitial seeds [ 34 ], greater research is warranted in this direction. Also, in the present study, the number of I-125 particles was not analyzed and serves as a limitation.…”

Section: Discussionmentioning

confidence: 99%

CT-MR Image Fusion for Post-Implant Dosimetry Analysis in Brain Tumor Seed Implantation- a Preliminary Study

et al. 2022

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Purpose. To calculate and evaluate postimplant dosimetry (PID) with CT-MR fusion technique after brain tumor brachytherapy and compare the result with CT-based PID. Methods and Materials. 16 brain tumor patients received MR-guided intervention with Iodine-125 (125I) seed implantation entered this preliminary study for PID evaluation. Registration and fusion of CT and MR images of the same patients were performed one day after operation. Seeds identification and targets delineation were carried out on CT, MR, and CT-MR fusion images, each. The number and location of seeds on MR or CT- MR fusion images were compared with those of actually implanted seeds. Clinical target volume (CTV) and dosimetric parameters such as %D90, %V100 and external V100 were measured and calculated. In addition, the correlation of the fusion to CT CTV ratio and other factors were analyzed. Results. The numbers of fusion seeds were not significantly different compared with reference seeds (t =1.76, p >0.05). The difference between reference seeds numbers and truly extracted MR seeds numbers was statistically significant (t =3.91, p <0.05). All dosimetric parameters showed significant differences between the two techniques (p <0.05). The mean CTV delineated on fusion images was 34.3 ± 33.6, smaller than that on CT images. The mean values of external V100, %V100 and %D90 on fusion images were larger than those on CT images. Correlation analysis showed that the fusion-CT V100 ratio was positively and significantly correlated with the fusion-CT volume ratio. Conclusions. This preliminary study indicated that CT-MR fusion-based PID exhibited good accuracy for 125I brain tumor brachytherapy dosimetry when compared to CT-based PID and merits further research to establish best-outcome protocols.

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Section: Discussionmentioning

confidence: 99%

CT-MR Image Fusion for Post-Implant Dosimetry Analysis in Brain Tumor Seed Implantation- a Preliminary Study

et al. 2022

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“…While imperfect, advanced imaging techniques such as MR perfusion and positron emission tomography (PET) MRI have emerged as modalities that may be helpful and differentiate posttreatment effect from tumor progression; MR spectroscopy is used less frequently. 21 In MR perfusion, an elevated relative cerebral blood volume in the measured region of contrast enhancement is a result of neovascularization and concerning for active tumor where decreased relative cerebral blood volumes can be indicative of posttreatment changes. On PET MRI, lesions with increased tracer uptake, as opposed to those without, are considered active.…”

Section: Commentmentioning

confidence: 99%

“…The associated radiographic changes may mimic tumor progression including increased size of the treated lesion and increased surrounding fluid-attenuated inversion recovery (FLAIR) signal changes because of increased edema. While imperfect, advanced imaging techniques such as MR perfusion and positron emission tomography (PET) MRI have emerged as modalities that may be helpful and differentiate posttreatment effect from tumor progression; MR spectroscopy is used less frequently 21 . In MR perfusion, an elevated relative cerebral blood volume in the measured region of contrast enhancement is a result of neovascularization and concerning for active tumor where decreased relative cerebral blood volumes can be indicative of posttreatment changes.…”

Section: Radiationmentioning

confidence: 99%

Neurologic Complications of Cancer Treatment

Porter¹

2023

CONTINUUM: Lifelong Learning in Neurology

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Objective Advances in cancer treatment have led to extended survival and increased risk of neurologic complications in an aging population. This review summarizes potential neurologic complications in patients who have undergone treatment for neurologic and systemic malignancies. Latest Developments Radiation and cytotoxic chemotherapy along with other targeted therapies continue to be the mainstay of cancer treatment. These advances in cancer care have led to improved outcomes and increased the need to understand the spectrum of neurologic complications that may arise from treatment. While radiation and older therapies including cytotoxic chemotherapies have side effect profiles that are widely known and well understood, this article serves as a review of the more commonly associated neurologic complications of both traditional and newer treatments being offered to this patient population. Essential Points Neurotoxicity is a common complication of cancer-directed treatment. In general, neurologic complications of radiation therapy are more common in central nervous system malignancies, and neurologic complications of chemotherapy are more common in non-neurologic malignancies. Attempts at prevention, early detection, and intervention remain paramount in the reduction of neurologic morbidity.

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“…Segmenting these two tumor components are clinically important for radiation therapy, neurosurgery, and treatment response monitoring. [5][6][7] The tumors in this dataset were manually segmented within the picture archiving and communication system (PACS) of Yale New Haven Hospital. Five medical students, who were trained to manually segment the tumor components, manually segmented the images for 1,001 patients.…”

Section: Introductionmentioning

confidence: 99%

“…Segmenting these two tumor components are clinically important for radiation therapy, neurosurgery, and treatment response monitoring. 5–7…”

Section: Introductionmentioning

confidence: 99%

Self-Configuring Capsule Networks for Brain Image Segmentation

Avesta

Hossain

Aboian

et al. 2023

Preprint

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When an auto-segmentation model needs to be applied to a new segmentation task, multiple decisions should be made about the pre-processing steps and training hyperparameters. These decisions are cumbersome and require a high level of expertise. To remedy this problem, I developed self-configuring CapsNets (scCapsNets) that can scan the training data as well as the computational resources that are available, and then self-configure most of their design options. In this study, we developed a self-configuring capsule network that can configure its design options with minimal user input. We showed that our self-configuring capsule netwrok can segment brain tumor components, namely edema and enhancing core of brain tumors, with high accuracy. Out model outperforms UNet-based models in the absence of data augmentation, is faster to train, and is computationally more efficient compared to UNet-based models.

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Fundamentals of Radiation Oncology for Neurologic Imaging

Cited by 11 publications

References 118 publications

CT-MR Image Fusion for Post-Implant Dosimetry Analysis in Brain Tumor Seed Implantation- a Preliminary Study

CT-MR Image Fusion for Post-Implant Dosimetry Analysis in Brain Tumor Seed Implantation- a Preliminary Study

Neurologic Complications of Cancer Treatment

Self-Configuring Capsule Networks for Brain Image Segmentation

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