Comparison of tumor delineation using dual energy computed tomography versus magnetic resonance imaging in head and neck cancer re-irradiation cases.
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ABSTRACT:
SUBMITTER: Ng SP
PROVIDER: S-EPMC7807720 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeThe aim of this article is to establish a comprehensive contouring guideline for treatment planning using only magnetic resonance images through an up-to-date set of organs at risk (OARs), recommended organ boundaries, and relevant suggestions for the magnetic resonance imaging (MRI)-based delineation of OARs in the head and neck (H&N) region.Methods and materialsAfter a detailed review of the literature, MRI data were collected from the H&N region of healthy volunteers. OARs were delineated in the axial, coronal, and sagittal planes on T2-weighted sequences. Every contour defined was revised by 4 radiation oncologists and subsequently by 2 independent senior experts (H&N radiation oncologist and radiologist). After revision, the final structures were presented to the consortium partners.ResultsA definitive consensus was reached after multi-institutional review. On that basis, we provided a detailed anatomic and functional description and specific MRI characteristics of the OARs.ConclusionsIn the era of precision radiation therapy, the need for well-built, straightforward contouring guidelines is on the rise. Precise, uniform, delineation-based, automated OAR segmentation on MRI may lead to increased accuracy in terms of organ boundaries and analysis of dose-dependent sequelae for an adequate definition of normal tissue complication probability.
| S-EPMC9830100 | biostudies-literature
Project description:Background and purposeFew studies on magnetic resonance imaging (MRI) only head and neck radiation treatment planning exist, and none using a generally available software. The aim of this study was to evaluate the accuracy of absorbed dose for head and neck synthetic computed tomography data (sCT) generated by a commercial convolutional neural network-based algorithm.Materials and methodsFor 44 head and neck cancer patients, sCT were generated and the geometry was validated against computed tomography data (CT). The clinical CT based treatment plan was transferred to the sCT and recalculated without re-optimization, and differences in relative absorbed dose were determined for dose-volume-histogram (DVH) parameters and the 3D volume.ResultsFor overall body, the results of the geometric validation were (Mean ± 1sd): Mean error -5 ± 10 HU, mean absolute error 67 ± 14 HU, Dice similarity coefficient 0.98 ± 0.05, and Hausdorff distance difference 4.2 ± 1.7 mm. Water equivalent depth difference for region Th1-C7, mid mandible and mid nose were -0.3 ± 3.4, 1.1 ± 2.0 and 0.7 ± 3.8 mm respectively. The maximum mean deviation in absorbed dose for all DVH parameters was 0.30% (0.12 Gy). The absorbed doses were considered equivalent (p-value < 0.001) and the mean 3D gamma passing rate was 99.4 (range: 95.7-99.9%).ConclusionsThe convolutional neural network-based algorithm generates sCT which allows for accurate absorbed dose calculations for MRI-only head and neck radiation treatment planning. The sCT allows for statistically equivalent absorbed dose calculations compared to CT based radiotherapy.
| S-EPMC8058030 | biostudies-literature
Project description:BACKGROUND AND PURPOSE:Loco-regionally recurrent head and neck cancer (HNC) in the setting of prior radiotherapy carries significant morbidity and mortality. The role of re-irradiation (re-RT) remains unclear due to toxicity. We determined prognostic factors for loco-regional control (LRC) and formulated a nomogram to help clinicians select re-RT candidates. MATERIAL AND METHODS:From July 1996 to April 2011, 257 patients with recurrent HNC underwent fractionated re-RT. Median prior dose was 65 Gy and median time between RT was 32.4 months. One hundred fifteen patients (44%) had salvage surgery and 172 (67%) received concurrent chemotherapy. Median re-RT dose was 59.4 Gy and 201 (78%) patients received IMRT. Multivariate Cox proportional hazards were used to identify independent predictors of LRC and a nomogram for 2-year LRC was constructed. RESULTS:Median follow-up was 32.6 months. Two-year LRC and overall survival (OS) were 47% and 43%, respectively. Recurrent stage (P=0.005), non-oral cavity subsite (P<0.001), absent organ dysfunction (P<0.001), salvage surgery (P<0.001), and dose >50 Gy (P=0.006) were independently associated with improved LRC. We generated a nomogram with concordance index of 0.68. CONCLUSION:Re-RT can be curative, and our nomogram can help determine a priori which patients may benefit.
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Project description:PURPOSE:To describe in detail a dataset consisting of longitudinal fan-beam computed tomography (CT) imaging to visualize anatomical changes in head-and-neck squamous cell carcinoma (HNSCC) patients throughout radiotherapy (RT) treatment course. ACQUISITION AND VALIDATION METHODS:This dataset consists of CT images from 31 HNSCC patients who underwent volumetric modulated arc therapy (VMAT). Patients had three CT scans acquired throughout the duration of the radiation treatment course. Pretreatment planning CT scans with a median of 13 days before treatment (range: 2-27), mid-treatment CT at 22 days after start of treatment (range: 13-38), and post-treatment CT 65 days after start of treatment (range: 35-192). Patients received RT treatment to a total dose of 58-70 Gy, using daily 2.0-2.20 Gy, fractions for 30-35 fractions. The fan-beam CT images were acquired using a Siemens 16-slice CT scanner head protocol with 120 kV and current of 400 mAs. A helical scan with 1 rotation per second was used with a slice thickness of 2 mm and table increment of 1.2 mm. In addition to the imaging data, contours of anatomical structures for RT, demographic, and outcome measurements are provided. DATA FORMAT AND USAGE NOTES:The dataset with DICOM files including images, RTSTRUCT files, and RTDOSE files can be found and publicly accessed in the Cancer Imaging Archive (TCIA, http://www.cancerimagingarchive.net/) as collection Head-and-neck squamous cell carcinoma patients with CT taken during pretreatment, mid-treatment, and post-treatment (HNSCC-3DCT-RT). DISCUSSION:This is the first dataset to date in TCIA which provides a collection of multiple CT imaging studies (pretreatment, mid-treatment, and post-treatment) throughout the treatment course. The dataset can serve a wide array of research projects including (but not limited to): quantitative imaging assessment, investigation on anatomical changes with treatment progress, dosimetry of target volumes and/or normal structures due to anatomical changes occurring during treatment, investigation of RT toxicity, and concurrent chemotherapy and RT effects on head-and-neck patients.
| S-EPMC6510641 | biostudies-literature
Project description:PurposeRadiotherapy planning based only on positron emission tomography/magnetic resonance imaging (PET/MRI) lacks computed tomography (CT) information required for dose calculations. In this study, a previously developed deep learning model for creating synthetic CT (sCT) from MRI in patients with head and neck cancer was evaluated in 2 scenarios: (1) using an independent external dataset, and (2) using a local dataset after an update of the model related to scanner software-induced changes to the input MRI.Methods and materialsSix patients from an external site and 17 patients from a local cohort were analyzed separately. Each patient underwent a CT and a PET/MRI with a Dixon MRI sequence over either one (external) or 2 (local) bed positions. For the external cohort, a previously developed deep learning model for deriving sCT from Dixon MRI was directly applied. For the local cohort, we adapted the model for an upgraded MRI acquisition using transfer learning and evaluated it in a leave-one-out process. The sCT mean absolute error for each patient was assessed. Radiotherapy dose plans based on sCT and CT were compared by assessing relevant absorbed dose differences in target volumes and organs at risk.ResultsThe MAEs were 78 ± 13 HU and 76 ± 12 HU for the external and local cohort, respectively. For the external cohort, absorbed dose differences in target volumes were within ± 2.3% and within ± 1% in 95% of the cases. Differences in organs at risk were <2%. Similar results were obtained for the local cohort.ConclusionsWe have demonstrated a robust performance of a deep learning model for deriving sCT from MRI when applied to an independent external dataset. We updated the model to accommodate a larger axial field of view and software-induced changes to the input MRI. In both scenarios dose calculations based on sCT were similar to those of CT suggesting a robust and reliable method.
| S-EPMC8452789 | biostudies-literature
Project description:Computed tomography (CT) and magnetic resonance imaging (MRI) are common imaging methods to detect cervical lymph node metastasis of head and neck cancer. We aimed to assess the diagnostic efficacy of CT and MRI in detecting cervical lymph node metastasis, and to establish unified diagnostic criteria via systematic review and meta-analysis. A systematic literature search in five databases until January 2014 was carried out. All retrieved studies were reviewed and eligible studies were qualitatively summarized. Besides pooling the sensitivity (SEN) and specificity (SPE) data of CT and MRI, summary receiver operating characteristic curves were generated. A total of 63 studies including 3,029 participants were involved. The pooled results of meta-analysis showed that CT had a higher SEN (0.77 [95% confidence interval {CI} 0.73-0.87]) than MRI (0.72 [95% CI 0.70-0.74]) when node was considered as unit of analysis (P<0.05); MRI had a higher SPE (0.81 [95% CI 0.80-0.82]) than CT (0.72 [95% CI 0.69-0.74]) when neck level was considered as unit of analysis (P<0.05) and MRI had a higher area under concentration-time curve than CT when the patient was considered as unit of analysis (P<0.05). With regards to diagnostic criteria, for MRI, the results showed that the minimal axial diameter of 10 mm could be considered as the best size criterion, compared to 12 mm for CT. Overall, MRI conferred significantly higher SPE while CT demonstrated higher SEN. The diagnostic criteria for MRI and CT on size of metastatic lymph nodes were suggested as 10 and 12 mm, respectively.
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Project description:PurposeThe goal of this multicenter retrospective study of patients with head and neck malignancies was to evaluate the efficacy and safety of carbon-ion (C-ion) radiotherapy (RT) after photon RT.MethodsWe enrolled 56 patients with head and neck malignancies who underwent re-irradiation (re-RT) using C-ions between November 2003 and March 2019, treated previously with photon RT. The tumors at re-RT were located in the sinonasal cavities (n = 20, 35.7%), skull base (n = 12, 21.4%), and orbit (n = 7, 12.5%). The tumors at the initial RT were located in the sinonasal cavities (n = 13, 23.2%), skull base (n = 9, 16.1%), and orbit (n = 9, 16.1%). The median period between the initial RT and re-RT was 41 (4-568) months. The most common histology of re-RT was squamous cell carcinoma (n = 11, 19.6%). The most commonly used protocol was 57.6 Gy (relative biological effectiveness) in 16 fractions (n = 23, 41.1%). Surgery preceded re-RT in three patients (5.4%). One patient with malignant melanoma received concurrent chemotherapy.ResultsThe 2-year local control, progression-free survival, and overall survival rates were 66.5%, 36.9%, and 67.9%, respectively. The median follow-up time was 28 months. Two patients (3.6%) developed grade ≥ 3 acute toxicities, and 14 (25.0%) developed grade ≥ 3 late toxicities. A single patient had confirmed grade 5 dermatitis with infection.ConclusionRe-RT using C-ions for head and neck malignancies after photon RT is an effective treatment with tolerable toxicity.
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Project description:PurposeTo develop an imaging method to characterize and map marrow composition in the entire skeletal system, and to simulate differential targeted marrow irradiation based on marrow composition.Methods and materialsWhole-body dual energy computed tomography (DECT) images of cadavers and leukemia patients were acquired, segmented to separate bone marrow components, namely, bone, red marrow (RM), and yellow marrow (YM). DECT-derived marrow fat fraction was validated using histology of lumbar vertebrae obtained from cadavers. The fractions of RM (RMF = RM/total marrow) and YMF were calculated in each skeletal region to assess the correlation of marrow composition with sites and ages. Treatment planning was simulated to target irradiation differentially at a higher dose (18 Gy) to either RM or YM and a lower dose (12 Gy) to the rest of the skeleton.ResultsA significant correlation between fat fractions obtained from DECT and cadaver histology samples was observed (r=0.861, P<.0001, Pearson). The RMF decreased in the head, neck, and chest was significantly inversely correlated with age but did not show any significant age-related changes in the abdomen and pelvis regions. Conformity of radiation to targets (RM, YM) was significantly dependent on skeletal sites. The radiation exposure was significantly reduced (P<.05, t test) to organs at risk (OARs) in RM and YM irradiation compared with standard total marrow irradiation (TMI).ConclusionsWhole-body DECT offers a new imaging technique to visualize and measure skeletal-wide marrow composition. The DECT-based treatment planning offers volumetric and site-specific precise radiation dosimetry of RM and YM, which varies with aging. Our proposed method could be used as a functional compartment of TMI for further targeted radiation to specific bone marrow environment, dose escalation, reduction of doses to OARs, or a combination of these factors.
| S-EPMC5081224 | biostudies-literature
Project description:PurposeSpinal cord delineation is critical to the delivery of stereotactic body radiation therapy (SBRT). Although underestimating the spinal cord can lead to irreversible myelopathy, overestimating the spinal cord may compromise the planning target volume coverage. We compare spinal cord contours based on computed tomography (CT) simulation with a myelogram to spinal cord contours based on fused axial T2 magnetic resonance imaging (MRI).Methods and materialsEight patients with 9 spinal metastases treated with spinal SBRT were contoured by 8 radiation oncologists, neurosurgeons, and physicists, with spinal cord definition based on (1) fused axial T2 MRI and (2) CT-myelogram simulation images, yielding 72 sets of spinal cord contours. The spinal cord volume was contoured at the target vertebral body volume based on both images. The mixed-effect model assessed comparisons of T2 MRI- to myelogram-defined spinal cord in centroid deviations (deviations in the center point of the cord) through the vertebral body target volume, spinal cord volumes, and maximum doses (0.035 cc point) to the spinal cord applying the patient's SBRT treatment plan, in addition to in-between and within-subject variabilities.ResultsThe estimate for the fixed effect from the mixed model showed that the mean difference between 72 CT volumes and 72 MRI volumes was 0.06 cc and was not statistically significant (95% confidence interval, -0.034, 0.153; P = .1832). The mixed model showed that the mean dose at 0.035 cc for CT-defined spinal cord contours was 1.24 Gy lower than that of MRI-defined spinal cord contours and was statistically significant (95% confidence interval, -2.292, -0.180; P = .0271). Also, the mixed model indicated no statistical significance for deviations in any of the axes between MRI-defined spinal cord contours and CT-defined spinal cord contours.ConclusionsCT myelogram may not be required when MRI imaging is feasible, although uncertainty at the cord-to-treatment volume interface may result in overcontouring and hence higher estimated cord dose-maximums with axial T2 MRI-based cord definition.
| S-EPMC9991542 | biostudies-literature
Project description:Background and purposeHypoxia Positron-Emission-Tomography (PET) as well as Computed Tomography (CT) radiomics have been shown to be prognostic for radiotherapy outcome. Here, we investigate the stratification potential of CT-radiomics in head and neck cancer (HNC) patients and test if CT-radiomics is a surrogate predictor for hypoxia as identified by PET.Materials and methodsTwo independent cohorts of HNC patients were used for model development and validation, HN1 (n = 149) and HN2 (n = 47). The training set HN1 consisted of native planning CT data whereas for the validation cohort HN2 also hypoxia PET/CT data was acquired using [18F]-Fluoromisonidazole (FMISO). Machine learning algorithms including feature engineering and classifier selection were trained for two-year loco-regional control (LRC) to create optimal CT-radiomics signatures.Secondly, a pre-defined [18F]FMISO-PET tumour-to-muscle-ratio (TMRpeak ≥ 1.6) was used for LRC prediction. Comparison between risk groups identified by CT-radiomics or [18F]FMISO-PET was performed using area-under-the-curve (AUC) and Kaplan-Meier analysis including log-rank test.ResultsThe best performing CT-radiomics signature included two features with nearest-neighbour classification (AUC = 0.76 ± 0.09), whereas AUC was 0.59 for external validation. In contrast, [18F]FMISO TMRpeak reached an AUC of 0.66 in HN2. Kaplan-Meier analysis of the independent validation cohort HN2 did not confirm the prognostic value of CT-radiomics (p = 0.18), whereas for [18F]FMISO-PET significant differences were observed (p = 0.02).ConclusionsNo direct correlation of patient stratification using [18F]FMISO-PET or CT-radiomics was found in this study. Risk groups identified by CT-radiomics or hypoxia PET showed only poor overlap. Direct assessment of tumour hypoxia using PET seems to be more powerful to stratify HNC patients.
| S-EPMC7536307 | biostudies-literature