Image-guided interstitial high-dose-rate brachytherapy in the treatment of inoperable recurrent head and neck malignancies: An effective option of reirradiation
“…There are few previous reports on the use of HDR brachytherapy as palliative treatment for head and neck cancer [ 6 , 7 , 8 ]. Skowronek et al .…”
Section: Discussionmentioning
confidence: 99%
“…There are few previous reports on the use of HDR brachytherapy as palliative treatment for head and neck cancer [6,7,8]. Skowronek et al reported the results of palliative HDR and pulsed-dose-rate (PDR) brachytherapy in 47 cases, with a relapse of head and neck cancer [8].…”
Section: Discussionmentioning
confidence: 99%
“…Interstitial brachytherapy has historically been preferred for treatment of head and neck cancer [ 1 , 2 ]. High-dose-rate (HDR) brachytherapy is frequently performed as a part of treatment of these cancers [ 3 , 4 , 5 ], but there have been few reports using HDR brachytherapy as a palliative treatment [ 6 , 7 , 8 ]. HDR brachytherapy has several advantages.…”
Purpose
To present a small series of cases, in which single-fraction image-guided high-dose-rate (HDR) brachytherapy was provided as palliative treatment for inoperable head and neck cancer cases.
Material and methods
We used this technique to treat 3 patients with symptomatic head and neck cancer (tongue cancer, gingival metastasis of osteosarcoma, and external auditory canal cancer), who were not eligible for a definitive treatment. The purpose of palliative brachytherapy in all 3 patients was the relief of symptoms such as difficulty in eating, talking, and hearing. All patients were treated with computed tomography (CT) image-guided interstitial HDR brachytherapy under local anesthesia in an outpatient setting, with a single dose of 10 Gy.
Results
Satisfactory palliative effects were achieved in all cases without serious side effects. The palliative effects were sustained in 2 patients until death, and 1 patient lived for 39 weeks before a relapse.
Conclusions
Our palliative treatment technique appears to be safe, effective, and less invasive, and could be a treatment option for symptomatic patients with head and neck cancer.
“…There are few previous reports on the use of HDR brachytherapy as palliative treatment for head and neck cancer [ 6 , 7 , 8 ]. Skowronek et al .…”
Section: Discussionmentioning
confidence: 99%
“…There are few previous reports on the use of HDR brachytherapy as palliative treatment for head and neck cancer [6,7,8]. Skowronek et al reported the results of palliative HDR and pulsed-dose-rate (PDR) brachytherapy in 47 cases, with a relapse of head and neck cancer [8].…”
Section: Discussionmentioning
confidence: 99%
“…Interstitial brachytherapy has historically been preferred for treatment of head and neck cancer [ 1 , 2 ]. High-dose-rate (HDR) brachytherapy is frequently performed as a part of treatment of these cancers [ 3 , 4 , 5 ], but there have been few reports using HDR brachytherapy as a palliative treatment [ 6 , 7 , 8 ]. HDR brachytherapy has several advantages.…”
Purpose
To present a small series of cases, in which single-fraction image-guided high-dose-rate (HDR) brachytherapy was provided as palliative treatment for inoperable head and neck cancer cases.
Material and methods
We used this technique to treat 3 patients with symptomatic head and neck cancer (tongue cancer, gingival metastasis of osteosarcoma, and external auditory canal cancer), who were not eligible for a definitive treatment. The purpose of palliative brachytherapy in all 3 patients was the relief of symptoms such as difficulty in eating, talking, and hearing. All patients were treated with computed tomography (CT) image-guided interstitial HDR brachytherapy under local anesthesia in an outpatient setting, with a single dose of 10 Gy.
Results
Satisfactory palliative effects were achieved in all cases without serious side effects. The palliative effects were sustained in 2 patients until death, and 1 patient lived for 39 weeks before a relapse.
Conclusions
Our palliative treatment technique appears to be safe, effective, and less invasive, and could be a treatment option for symptomatic patients with head and neck cancer.
“…Recently, with the development of imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasonography, image-based HDR BT has been implemented. Using three-dimensional (3D) cross-sectional image sets, radiation oncologists and medical physicists can depict the target volume and critical structures, and calculate the volumetric doses delivered to these organs [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ]. In the gynecological region, there are recommendations about image-based BT, where authors referring to concepts and terms in 3D image-based treatment planning, 3D dose volume parameters, aspects of 3D image-based anatomy, radiation physics and radiobiology [ 13 , 14 ].…”
PurposeTo evaluate dose-volume relationships of target volume and critical structures in computed tomography (CT) image-based brachytherapy for head and neck cancer.Material and methodsThirty-seven patients with mobile tongue, floor of mouth, and base of tongue cancer treated with brachytherapy (post-operative alone and as a boost after external beam radiotherapy [EBRT], or definitive alone or as a boost after EBRT) were selected. Treatment plans were made using post-implant CT images. The fractionation schedule was 7-15 × 3-5 Gy for post-operative (with or without EBRT), 14-15 × 3 Gy for definitive alone, and 5-10 × 3 Gy for boost treatments. For the target volume, V100, D90, and dose non-uniformity ratio (DNR) were calculated. For the mandible, spinal cord and salivary glands doses to specified volumes were reported.ResultsThe median values of V100 and D90 were 89.9% and 99.9%, respectively; the median values of DNR was 0.46. The median D2cm
3 of the mandible and spinal cord were 48.3% and 5.8%, respectively. The ipsilateral median D2cm
3 of parotid and submandibular glands were 6.4% and 12.5%, whereas on the contralateral side, the corresponding values were 5.3% and 7.0%, respectively.ConclusionsUsing conformal treatment planning, it was desirable to keep the dose to the mandible, spinal cord, and salivary glands at an acceptable level. The quantitative plan evaluation may help us find correlations between dosimetric parameters and clinical outcome, which may lead to improve the quality of the treatment, but it requires longer follow-up and results from other studies.
“…The enlarged lymph nodes are mainly located in the deep upper cervical lymph node group in the upper neck. It then starts to be unilateral, and then develops to bilateral, and can spread to the middle and lower parts of the neck, and even aggravate the condition (Tselis et al, 2017;Wu et al, 2016). Therefore, it is necessary to diagnose and treat the lymph node metastasis of NPC as early as possible.…”
This article was to explore the adoption value of deep learning combined with computed tomography (CT) imaging omics in the prediction of metastatic lymph nodes of nasopharyngeal carcinoma (NPC). An end-to-end neural network architecture was designed based on the fully convolutional neural network (FCNN), which was applied to the CT image analysis of 52 patients with lymphatic metastasis and 36 patients without lymphatic metastasis. Patient's lymph node volume (V), the largest crosssectional shortest diameter (d-value), and other macro characteristics were recorded.The microscopic features of its CT imaging omics were extracted. Moreover, receiver operating characteristic (ROC) curve was utilized to analyse the prediction performance (accuracy, area under the curve [AUC], and Youden index) of each feature for lymphatic metastasis. The results showed that the lymph node volume (4.37 ± 0.67) and the shortest diameter of the largest cross section (12.35 ± 2.31) of patients with lymph node metastasis were greatly larger than those without lymph node metastasis (1.84 ± 0.65, 7.98 ± 2.04) (P < 0.05). There were five features that met the conditions of AUC > 0.7 and Yoden index>0.5, including lymph node volume (AUC area 0.945, Youden index 0.597), the shortest diameter of the largest cross section (AUC area 0.746, Youden index 0.539), Surface Area Density (AUC area 0.809, Youden index 0.552), Compactness1 (AUC area 0.751, Youden index 0.537), and Convex Hull Volume (AUC area 0.751, Youden index 0.537). The AUC of V+ Surface Area Density + Compactness1 + Convex Hull Volume was 0.876, and the prediction accuracy was 92.11%. In short, the prediction model composed of the macroscopic features of CT images and some imaging omics features based on deep learning showed high accuracy and AUC for the prediction of NPC metastatic lymph nodes. Moreover, V + Surface Area Density + Compactness1 + Convex Hull Volume can be used as the optimal feature combination model for predicting NPC lymphatic metastasis.
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