A deep learning-based framework (Co-ReTr) for auto-segmentation of non-small cell-lung cancer in computed tomography images.

PURPOSE: Deep learning-based auto-segmentation algorithms can improve clinical workflow by defining accurate regions of interest while reducing manual labor. Over the past decade, convolutional neural networks (CNNs) have become prominent in medical image segmentation applications. However, CNNs have limitations in learning long-range spatial dependencies due to the locality of the convolutional layers. Transformers were introduced to address this challenge. In transformers with self-attention mechanism, even the first layer of information processing makes connections between distant image locations. Our paper presents a novel framework that bridges these two unique techniques, CNNs and transformers, to segment the gross tumor volume (GTV) accurately and efficiently in computed tomography (CT) images of non-small cell-lung cancer (NSCLC) patients. METHODS: Under this framework, input of multiple resolution images was used with multi-depth backbones to retain the benefits of high-resolution and low-resolution images in the deep learning architecture. Furthermore, a deformable transformer was utilized to learn the long-range dependency on the extracted features. To reduce computational complexity and to efficiently process multi-scale, multi-depth, high-resolution 3D images, this transformer pays attention to small key positions, which were identified by a self-attention mechanism. We evaluated the performance of the proposed framework on a NSCLC dataset which contains 563 training images and 113 test images. Our novel deep learning algorithm was benchmarked against five other similar deep learning models. RESULTS: The experimental results indicate that our proposed framework outperforms other CNN-based, transformer-based, and hybrid methods in terms of Dice score (0.92) and Hausdorff Distance (1.33). Therefore, our proposed model could potentially improve the efficiency of auto-segmentation of early-stage NSCLC during the clinical workflow. This type of framework may potentially facilitate online adaptive radiotherapy, where an efficient auto-segmentation workflow is required. CONCLUSIONS: Our deep learning framework, based on CNN and transformer, performs auto-segmentation efficiently and could potentially assist clinical radiotherapy workflow.

A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis.

BACKGROUND: The precise prediction of epidermal growth factor receptor (EGFR) mutation status and gross tumor volume (GTV) segmentation are crucial goals in computer-aided lung adenocarcinoma brain metastasis diagnosis. However, these two tasks present continuous difficulties due to the nonuniform intensity distributions, ambiguous boundaries, and variable shapes of brain metastasis (BM) in MR images.The existing approaches for tackling these challenges mainly rely on single-task algorithms, which overlook the interdependence between these two tasks. METHODS: To comprehensively address these challenges, we propose a multi-task deep learning model that simultaneously enables GTV segmentation and EGFR subtype classification. Specifically, a multi-scale self-attention encoder that consists of a convolutional self-attention module is designed to extract the shared spatial and global information for a GTV segmentation decoder and an EGFR genotype classifier. Then, a hybrid CNN-Transformer classifier consisting of a convolutional block and a Transformer block is designed to combine the global and local information. Furthermore, the task correlation and heterogeneity issues are solved with a multi-task loss function, aiming to balance the above two tasks by incorporating segmentation and classification loss functions with learnable weights. RESULTS: The experimental results demonstrate that our proposed model achieves excellent performance, surpassing that of single-task learning approaches. Our proposed model achieves a mean Dice score of 0.89 for GTV segmentation and an EGFR genotyping accuracy of 0.88 on an internal testing set, and attains an accuracy of 0.81 in the EGFR genotype prediction task and an average Dice score of 0.85 in the GTV segmentation task on the external testing set. This shows that our proposed method has outstanding performance and generalization. CONCLUSION: With the introduction of an efficient feature extraction module, a hybrid CNN-Transformer classifier, and a multi-task loss function, the proposed multi-task deep learning network significantly enhances the performance achieved in both GTV segmentation and EGFR genotyping tasks. Thus, the model can serve as a noninvasive tool for facilitating clinical treatment.

Reduction of tumor volume during radiotherapy in patients with small-cell lung cancer and its prognostic significance.

BACKGROUND: Several studies have reported the potential prognostic significance of tumor volume reduction ratio (VRR) induced by radiotherapy (RT) in patients with non-small-cell lung cancer. However, there are no data yet on the prognostic significance of volumetric shrinkage in patients with small-cell lung cancer (SCLC). This study aimed to demonstrate the correlation between tumor volume reduction ratio and treatment outcomes. MATERIALS AND METHODS: The study included 61 patients with SCLC treated with fractionated RT of the primary tumor at our institution between 2013 and 2020. The relationship between volumetric changes in gross tumor volume (GTV) during radiotherapy and outcomes were analyzed and reported. RESULTS: The median radiation dose was 59.4 Gy (median fraction dose was 1.8 Gy). The median GTV before radiotherapy was 74 cm3, with a median GTV reduction of 48%. There was a higher VRR in patients receiving concurrent radiochemotherapy (p = 0.05). No volumetric parameters were identified as relevant predictors of outcome in the entire cohort. In multivariate analysis, only age had an impact on survival, while prophylactic whole-brain radiation influenced the progression-free survival significantly. CONCLUSION: Concurrent chemotherapy was associated with a higher VRR than sequential chemotherapy. No significant impact of VRR on patients' outcome or survival was detected.

Automatic segmentation of the gross target volume in radiotherapy for lung cancer using transresSEUnet 2.5D Network.

OBJECTIVE: This paper intends to propose a method of using TransResSEUnet2.5D network for accurate automatic segmentation of the Gross Target Volume (GTV) in Radiotherapy for lung cancer. METHODS: A total of 11,370 computed tomograms (CT), deriving from 137 cases, of lung cancer patients under radiotherapy developed by radiotherapists were used as the training set; 1642 CT images in 20 cases were used as the validation set, and 1685 CT images in 20 cases were used as the test set. The proposed network was tuned and trained to obtain the best segmentation model and its performance was measured by the Dice Similarity Coefficient (DSC) and with 95% Hausdorff distance (HD95). Lastly, as to demonstrate the accuracy of the automatic segmentation of the network proposed in this study, all possible mirrors of the input images were put into Unet2D, Unet2.5D, Unet3D, ResSEUnet3D, ResSEUnet2.5D, and TransResUnet2.5D, and their respective segmentation performances were compared and assessed. RESULTS: The segmentation results of the test set showed that TransResSEUnet2.5D performed the best in the DSC (84.08 ± 0.04) %, HD95 (8.11 ± 3.43) mm and time (6.50 ± 1.31) s metrics compared to the other three networks. CONCLUSIONS: The TransResSEUnet 2.5D proposed in this study can automatically segment the GTV of radiotherapy for lung cancer patients with more accuracy.

Primary gross tumor volume is prognostic and suggests treatment in upper esophageal cancer.

BACKGROUND: To aid clinicians strategizing treatment for upper esophageal squamous cell carcinoma (ESCC), this retrospective study investigated associations between primary gross tumor volume (GTVp) and prognosis in patients given surgical resection, radiotherapy, or both resection and radiotherapy. METHODS: The population comprised 568 patients with upper ESCC given definitive treatment, including 238, 216, and 114 who underwent surgery, radiotherapy, or combined radiotherapy and surgery. GTVp as a continuous variable was entered into the multivariate Cox model using penalized splines (P-splines) to determine the optimal cutoff value. Propensity score matching (PSM) was used to adjust imbalanced characteristics among the treatment groups. RESULTS: P-spline regression revealed a dependence of patient outcomes on GTVp, with 30 cm3 being an optimal cut-off for differences in overall and progression-free survival (OS, PFS). GTVp ≥30 cm3 was a negative independent prognostic factor for OS and PFS. PSM analyses confirmed the prognostic value of GTVp. For GTVp < 30 cm3, no significant survival differences were observed among the 3 treatments. For GTVp ≥30 cm3, the worst 5-year OS rate was experienced by those given surgery. The 5-year PFS rate of patients given combined radiotherapy and surgery was significantly better than that of patients given radiotherapy. The surgical complications of patients given the combined treatment were comparable to those who received surgery, but radiation side effects were significantly lower. CONCLUSION: GTVp is prognostic for OS and PFS in upper ESCC. For patients with GTVp ≥30 cm3, radiotherapy plus surgery was more effective than either treatment alone.

Accuracy of electroanatomical mapping-guided cardiac radiotherapy for ventricular tachycardia: pitfalls and solutions.

AIMS: To analyse and optimize the interobserver agreement for gross target volume (GTV) delineation on cardiac computed tomography (CCT) based on electroanatomical mapping (EAM) data acquired to guide radiotherapy for ventricular tachycardia (VT). METHODS AND RESULTS: Electroanatomical mapping data were exported and merged with the segmented CCT using manual registration by two observers. A GTV was created by both observers for predefined left ventricular (LV) areas based on preselected endocardial EAM points indicating a two-dimensional (2D) surface area of interest. The influence of (interobserver) registration accuracy and availability of EAM data on the final GTV and 2D surface location within each LV area was evaluated. The median distance between the CCT and EAM after registration was 2.7 mm, 95th percentile 6.2 mm for observer #1 and 3.0 mm, 95th percentile 7.6 mm for observer #2 (P = 0.9). Created GTVs were significantly different (8 vs. 19 mL) with lowest GTV overlap (35%) for lateral wall target areas. Similarly, the highest shift between 2D surfaces was observed for the septal LV (6.4 mm). The optimal surface registration accuracy (2.6 mm) and interobserver agreement (Δ interobserver EAM surface registration 1.3 mm) was achieved if at least three cardiac chambers were mapped, including high-quality endocardial LV EAM. CONCLUSION: Detailed EAM of at least three chambers allows for accurate co-registration of EAM data with CCT and high interobserver agreement to guide radiotherapy of VT. However, the substrate location should be taken in consideration when creating a treatment volume margin.

Comparing different CT, PET and MRI multi-modality image combinations for deep learning-based head and neck tumor segmentation.

BACKGROUND: Manual delineation of gross tumor volume (GTV) is essential for radiotherapy treatment planning, but it is time-consuming and suffers inter-observer variability (IOV). In clinics, CT, PET, and MRI are used to inform delineation accuracy due to their different complementary characteristics. This study aimed to investigate deep learning to assist GTV delineation in head and neck squamous cell carcinoma (HNSCC) by comparing various modality combinations. MATERIALS AND METHODS: This retrospective study had 153 patients with multiple sites of HNSCC including their planning CT, PET, and MRI (T1-weighted and T2-weighted). Clinical delineations of gross tumor volume (GTV-T) and involved lymph nodes (GTV-N) were collected as the ground truth. The dataset was randomly divided into 92 patients for training, 31 for validation, and 30 for testing. We applied a residual 3 D UNet as the deep learning architecture. We independently trained the UNet with four different modality combinations (CT-PET-MRI, CT-MRI, CT-PET, and PET-MRI). Additionally, analogical to post-processing, an average fusion of three bi-modality combinations (CT-PET, CT-MRI, and PET-MRI) was produced as an ensemble. Segmentation accuracy was evaluated on the test set, using Dice similarity coefficient (Dice), Hausdorff Distance 95 percentile (HD95), and Mean Surface Distance (MSD). RESULTS: All imaging combinations including PET provided similar average scores in range of Dice: 0.72-0.74, HD95: 8.8-9.5 mm, MSD: 2.6-2.8 mm. Only CT-MRI had a lower score with Dice: 0.58, HD95: 12.9 mm, MSD: 3.7 mm. The average of three bi-modality combinations reached Dice: 0.74, HD95: 7.9 mm, MSD: 2.4 mm. CONCLUSION: Multimodal deep learning-based auto segmentation of HNSCC GTV was demonstrated and inclusion of the PET image was shown to be crucial. Training on combined MRI, PET, and CT data provided limited improvements over CT-PET and PET-MRI. However, when combining three bimodal trained networks into an ensemble, promising improvements were shown.

Volumetric tumor response assessment is inefficient without overt clinical benefit compared to conventional, manual veterinary response assessment in canine nasal tumors.

Accurate assessment of tumor response to therapy is critical in guiding management of veterinary oncology patients and is most commonly performed using response evaluation criteria in solid tumors criteria. This process can be time consuming and have high intra- and interobserver variability. The primary aim of this serial measurements, secondary analysis study was to compare manual linear tumor response assessment to semi-automated, contoured response assessment in canine nasal tumors. The secondary objective was to determine if tumor measurements or clinical characteristics, such as stage, would correlate to progression-free interval. Three investigators evaluated paired CT scans of skulls of 22 dogs with nasal tumors obtained prior to and following radiation therapy. The automatically generated tumor volumes were not useful for canine nasal tumors in this study, characterized by poor intraobserver agreement between automatically generated contours and hand-adjusted contours. The radiologist's manual linear method of determining response evaluation criteria in solid tumors categorization and tumor volume is significantly faster (P < .0001) but significantly underestimates nasal tumor volume (P < .05) when compared to a contour-based method. Interobserver agreement was greater for volume determination using the contour-based method when compared to response evaluation criteria in solid tumors categorization utilizing the same method. However, response evaluation criteria in solid tumors categorization and percentage volume change were strongly correlated, providing validity to response evaluation criteria in solid tumors as a rapid method of tumor response assessment for canine nasal tumors. No clinical characteristics or tumor measurements were significantly associated with progression-free interval.

Radiotherapy for the treatment of pituitary adenomas: A dosimetric comparison of three planning techniques.

AIM: Our goal was to compare conformal 3D (C3D) radiotherapy (RT), modulated intensity RT (IMRT), and volumetric modulated arc therapy (VMAT) planning techniques in treating pituitary adenomas. BACKGROUND: RT is important for managing pituitary adenomas. Treatment planning advances allow for higher radiation dosing with less risk of affecting organs at risk (OAR). MATERIALS AND METHODS: We conducted a 5-year retrospective review of patients with pituitary adenoma treated with external beam radiation therapy (C3D with flattening filter, flattening filter-free [FFF], IMRT, and VMAT). We compared dose-volume histogram data. For OARs, we recorded D2%, maximum, and mean doses. For planning target volume (PTV), we registered V95%, V107%, D95%, D98%, D50%, D2%, minimum dose, conformity index (CI), and homogeneity index (HI). RESULTS: Fifty-eight patients with pituitary adenoma were included. Target-volume coverage was acceptable for all techniques. The HI values were 0.06, IMRT; 0.07, VMAT; 0.08, C3D; and 0.09, C3D FFF (p < 0.0001). VMAT and IMRT provided the best target volume conformity (CI, 0.64 and 0.74, respectively; p < 0.0001). VMAT yielded the lowest doses to the optic pathway, lens, and cochlea. The position of the neck in extreme flexion showed that it helps in planning mainly with VMAT by allowing only one arc to be used and achieving the desired conformity, decreasing the treatment time, while allowing greater protection to the organs of risk using C3D, C3DFFF. CONCLUSIONS: Our results confirmed that EBRT in pituitary adenomas using IMRT, VMAT, C3D, C3FFF provide adequate coverage to the target. VMAT with a single arc or incomplete arc had a better compliance with desired dosimetric goals, such as target coverage and normal structures dose constraints, as well as shorter treatment time. Neck extreme flexion may have benefits in treatment planning for better preservation of organs at risk. C3D with extreme neck flexion is an appropriate treatment option when other treatment techniques are not available.

Dosimetric impact on changes in target volumes during intensity-modulated radiotherapy for nasopharyngeal carcinoma.

BACKGROUND AND PURPOSE: To assess anatomic changes during intensity modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC) and to determine its dosimetric impact. PATIENTS AND METHODS: Twenty patients treated with IMRT for NPC were enrolled in this study. A second CT was performed at 38 Gy. Manual contouring of the macroscopic tumor volumes (GTV) and the planning target volumes (PTV) were done on the second CT. We recorded the volumes of the different structures, D98 %, the conformity, and the homogeneity indexes for each PTV. Volume percent changes were calculated. RESULTS: We observed a significant reduction in tumor volumes (58.56 % for the GTV N and 29.52 % for the GTV T). It was accompanied by a significant decrease in the D98 % for the 3 PTV (1.4 Gy for PTV H, p = 0.007; 0.3 Gy for PTV I, p = 0.03 and 1.15 Gy for PTV L, p = 0 0.0066). In addition, we observed a significant reduction in the conformity index in the order of 0.02 (p = 0.001) and 0.01 (p = 0.007) for PTV H and PTV I, respectively. The conformity variation was not significant for PTV L. Moreover, results showed a significant increase of the homogeneity index for PTV H (+ 0.03, p = 0.04) and PTV L (+ 0.04, p = 0.01). CONCLUSION: Tumor volume reduction during the IMRT of NPC was accompanied by deterioration of the dosimetric coverage for the different target volumes. It is essential that a careful adaptation of the treatment plan be considered during therapy for selected patients.

Major complications from radiotherapy following treatment for atypical meningiomas.

OBJECTIVEComplications from radiotherapy (RT), in a primary or adjuvant setting, have overall been described as uncommon, with few detailed descriptions of major complications. The authors present two cases involving significant complications and their management in their review of patients undergoing RT for treatment of atypical meningioma.METHODSThe authors conducted a retrospective review of all patients with pathologically confirmed atypical meningioma (WHO grade II) treated with primary or adjuvant RT from February 2011 through February 2019. They identified two patients with long-term, grade 3 toxicity. The cases of these patients are described in detail.RESULTSTwo patients had major complications associated with postoperative RT. Patients 1 and 2 both were treated with postoperative RT for pathologically confirmed atypical meningioma. Patient 1 experienced worsening behavioral changes, cognitive decline, and hydrocephalus following treatment. This required cerebrospinal fluid diversion. Patient 2 developed radiation necrosis with mass effect and cognitive decline. Neither patient returned to his/her initial post-RT status after steroid therapy, and each remained in need of supportive care. Both patients remained free of tumor progression at 52 and 38 months following treatment.CONCLUSIONSThe postoperative management of patients with atypical meningioma continues to be defined, with questions remaining regarding timing of RT, dose, target delineation, and fractionation. Both of the patients in this study received fractionated RT, which included a greater volume of normal brain than more focal treatment options such as would be required by stereotactic radiosurgery (SRS). Further research is needed to compare SRS and fractionated RT for the management of patients with grade II meningiomas. The more focused nature of SRS may make this a preferred option in certain cases of focal recurrence.

Impact of 68Ga-DOTATOC PET/MRI on robotic radiosurgery treatment planning in meningioma patients: first experiences in a single institution.

OBJECTIVEFor stereotactic radiosurgery (SRS) planning, precise contouring of tumor boundaries and organs at risk is of utmost importance. Correct interpretation of standard neuroimaging (i.e., CT and MRI) can be challenging after previous surgeries or in cases of skull base lesions with complex shapes. The aim of this study was to evaluate the impact of 68Ga-DOTATOC PET/MRI on treatment planning for image-guided SRS by CyberKnife.METHODSThe authors retrospectively identified 11 meningioma treatments in 10 patients who received a 68Ga-DOTATOC PET/MRI prior to SRS. The planning target volume (PTV) used for the patients' treatment was defined as the reference standard. This was contoured by a treating radiosurgeon (RS0) using fused planning CT and PET/MRI data sets. The same tumors were then contoured by another experienced radiosurgeon (RS1) and by a less-experienced radiosurgeon (RS2), both blinded to PET data sets. A comparison of target volumes with focus on volume-based metrics and distance to critical structures was performed. RS1 and RS2 also filled in a questionnaire analyzing the confidence level and the subjective need for the implementation of PET data sets for contouring.RESULTSAnalysis showed a subjective personal preference for PET/MRI in all cases for both radiosurgeons, particularly in proximity to critical structures. The analysis of the planning volumes per physician showed significantly smaller RS2-PTV in comparison to RS1-PTV and to RS0-PTV, whereas the median volumes were comparable between RS1-PTV and RS2-PTV (median: RS0: 4.3 cm3 [IQR 3.4-6.5 cm3] and RS1: 4.5 cm3 [IQR 2.7-6 cm3] vs RS2: 2.6 cm3 [IQR 2-5 cm3]; p = 0.003). This was also reflected in the best spatial congruency between the 2 experienced physicians (RS0 and RS1). The percentage of the left-out volume contoured by RS1 and RS2 compared to RS0 with PET/MRI demonstrated a relevant left-out-volume portion in both cases with greater extent for the less-experienced radiosurgeon (RS2) (RS1: 19.1% [IQR 8.5%-22%] vs RS2: 40.2% [IQR 34.2%-53%]). No significant differences were detected regarding investigated critical structures.CONCLUSIONSThis study demonstrated a relevant impact of PET/MRI on target volume delineation of meningiomas. The extent was highly dependent on the experience of the treating physician. This preliminary study supports the relevance of 68Ga-DOTATOC PET/MRI as a tool for radiosurgical treatment planning of meningiomas.

Retrospective assessment of a single fiducial marker tracking regimen with robotic stereotactic body radiation therapy for liver tumours.

AIM: To investigate tumour motion tracking uncertainties in the CyberKnife Synchrony system with single fiducial marker in liver tumours. BACKGROUND: In the fiducial-based CyberKnife real-time tumour motion tracking system, multiple fiducial markers are generally used to enable translation and rotation corrections during tracking. However, sometimes a single fiducial marker is employed when rotation corrections are not estimated during treatment. MATERIALS AND METHODS: Data were analysed for 32 patients with liver tumours where one fiducial marker was implanted. Four-dimensional computed tomography (CT) scans were performed to determine the internal target volume (ITV). Before the first treatment fraction, the CT scans were repeated and the marker migration was determined. Log files generated by the Synchrony system were obtained after each treatment and the correlation model errors were calculated. Intra-fractional spine rotations were examined on the spine alignment images before and after each treatment. RESULTS: The mean (standard deviation) ITV margin was 4.1 (2.3) mm, which correlated weakly with the distance between the fiducial marker and the tumour. The mean migration distance of the marker was 1.5 (0.7) mm. The overall mean correlation model error was 1.03 (0.37) mm in the radial direction. The overall mean spine rotations were 0.27° (0.31), 0.25° (0.22), and 0.23° (0.26) for roll, pitch, and yaw, respectively. The treatment time was moderately associated with the correlation model errors and weakly related to spine rotation in the roll and yaw planes. CONCLUSIONS: More caution and an additional safety margins are required when tracking a single fiducial marker.

Interobserver reliability of computed tomographic contouring of canine tonsils in radiation therapy treatment planning.

In radiation therapy (RT) treatment planning for canine head and neck cancer, the tonsils may be included as part of the treated volume. Delineation of tonsils on computed tomography (CT) scans is difficult. Error or uncertainty in the volume and location of contoured structures may result in treatment failure. The purpose of this prospective, observer agreement study was to assess the interobserver agreement of tonsillar contouring by two groups of trained observers. Thirty dogs undergoing pre- and post-contrast CT studies of the head were included. After the pre- and postcontrast CT scans, the tonsils were identified via direct visualization, barium paste was applied bilaterally to the visible tonsils, and a third CT scan was acquired. Data from each of the three CT scans were registered in an RT treatment planning system. Two groups of observers (one veterinary radiologist and one veterinary radiation oncologist in each group) contoured bilateral tonsils by consensus, obtaining three sets of contours. Tonsil volume and location data were obtained from both groups. The contour volumes and locations were compared between groups using mixed (fixed and random effect) linear models. There was no significant difference between each group's contours in terms of three-dimensional coordinates. However there was a significant difference between each group's contours in terms of the tonsillar volume (P < 0.0001). Pre- and postcontrast CT can be used to identify the location of canine tonsils with reasonable agreement between trained observers. Discrepancy in tonsillar volume between groups of trained observers may affect RT treatment outcome.

Interobserver variability in target volume delineation of hepatocellular carcinoma : An analysis of the working group "Stereotactic Radiotherapy" of the German Society for Radiation Oncology (DEGRO).

BACKGROUND: Definition of gross tumor volume (GTV) in hepatocellular carcinoma (HCC) requires dedicated imaging in multiple contrast medium phases. The aim of this study was to evaluate the interobserver agreement (IOA) in gross tumor delineation of HCC in a multicenter panel. METHODS: The analysis was performed within the "Stereotactic Radiotherapy" working group of the German Society for Radiation Oncology (DEGRO). The GTVs of three anonymized HCC cases were delineated by 16 physicians from nine centers using multiphasic CT scans. In the first case the tumor was well defined. The second patient had multifocal HCC (one conglomerate and one peripheral tumor) and was previously treated with transarterial chemoembolization (TACE). The peripheral lesion was adjacent to the previous TACE site. The last patient had an extensive HCC with a portal vein thrombosis (PVT) and an inhomogeneous liver parenchyma due to cirrhosis. The IOA was evaluated according to Landis and Koch. RESULTS: The IOA for the first case was excellent (kappa: 0.85); for the second case moderate (kappa: 0.48) for the peripheral tumor and substantial (kappa: 0.73) for the conglomerate. In the case of the peripheral tumor the inconsistency is most likely explained by the necrotic tumor cavity after TACE caudal to the viable tumor. In the last case the IOA was fair, with a kappa of 0.34, with significant heterogeneity concerning the borders of the tumor and the PVT. CONCLUSION: The IOA was very good among the cases were the tumor was well defined. In complex cases, where the tumor did not show the typical characteristics, or in cases with Lipiodol (Guerbet, Paris, France) deposits, IOA agreement was compromised.

Contouring and dose calculation in head and neck cancer radiotherapy after reduction of metal artifacts in CT images.

BACKGROUND: Delineation accuracy of the gross tumor volume (GTV) in radiotherapy planning for head and neck (H&N) cancer is affected by computed tomography (CT) artifacts from metal implants which obscure identification of tumor as well as organs at risk (OAR). This study investigates the impact of metal artifact reduction (MAR) in H&N patients in terms of delineation consistency and dose calculation precision in radiation treatment planning. MATERIAL AND METHODS: Tumor and OAR delineations were evaluated in planning CT scans of eleven oropharynx patients with streaking artifacts in the tumor region preceding curative radiotherapy (RT). The GTV-tumor (GTV-T), GTV-node and parotid glands were contoured by four independent observers on standard CT images and MAR images. Dose calculation was evaluated on thirty H&N patients with dental implants near the treated volume. For each patient, the dose derived from the clinical treatment plan using the standard image set was compared with the recalculated dose on the MAR image dataset. RESULTS: Reduction of metal artifacts resulted in larger volumes of all delineated structures compared to standard reconstruction. The GTV-T and the parotids were on average 22% (p < 0.06) and 7% larger (p = 0.005), respectively, in the MAR image plan compared to the standard image plan. Dice index showed reduced inter-observer variations after reduction of metal artifacts for all structures. The average surface distance between contours of different observers improved using the MAR images for GTV and parotids (p = 0.04 and p = 0.01). The median volume receiving a dose difference larger than ±3% was 2.3 cm3 (range 0-32 cm3). CONCLUSIONS: Delineation of structures in the head and neck were affected by metal artifacts and volumes were generally larger and more consistent after reduction of metal artifacts, however, only small changes were observed in the dose calculations.

The impact of histology and delivered dose on local control of spinal metastases treated with stereotactic radiosurgery.

OBJECTIVE An analysis of factors contributing to durable radiographic control of spinal metastases was undertaken, drawing from a large single-institution database in an attempt to elucidate indications and dose requirements for successful treatment. METHODS All patients treated at a single institution with stereotactic radiosurgery (SRS) of the spine as first-line therapy were assessed for local progression of the treated site, defined as radiographic enlargement of the treated tumor and/or biopsy-proven evidence of active tumor cells. All patients were followed with CT, PET, or MR imaging every 3-6 months until death. Treatment decisions were made by a multidisciplinary team of radiation oncologists, neurosurgeons, and neuroradiologists. Target volumes were defined according to the international consensus guidelines and were reviewed in a multidisciplinary conference. Image-guided techniques and intensity modulation were used for every case. The tumor's histological type, gross tumor volume (GTV), dose that covers 95% of the GTV (GTV D95), percentage of GTV covered by 95% of the prescribed dose (GTV V95), planning target volume (PTV), dose that covers 95% of the PTV (PTV D95), and percentage of PTV covered by 95% of the prescribed dose (PTV V95) were analyzed for significance in relation to local control, based on time to local progression. RESULTS A total of 811 lesions were treated in 657 patients between 2003 and 2015 at a single institution. The mean follow-up and overall survival for the entire cohort was 26.9 months (range 2-141 months). A total of 28 lesions progressed and the mean time to failure was 26 months (range 9.7-57 months). The median prescribed dose was 2400 cGy (range 1600-2600 cGy). Both GTV D95 and PTV D95 were highly significantly associated with local failure in univariate analysis, but GTV and PTV and histological type did not reach statistical significance. The median GTV D95 for the cohort equal to or above the GTV D95 1830 cGy cut point (high dose) was 2356 cGy, and it was 1709 cGy for the cohort of patients who received less than 1830 cGy (low dose). In terms of PTV D95, the median dose for those equal to or above the cut point of 1740 cGy (high dose) was 2233 cGy, versus 1644 cGy for those lesions below the PTV D95 cut point of 1740 cGy (low dose). CONCLUSIONS High-dose single-session SRS provides durable long-term control, regardless of the histological findings or tumor size. In this analysis, the only significant factors predictive of local control were related to the actual dose of radiation given. Although the target volumes were well treated with the intended dose, those lesions irradiated to higher doses (median GTV D95 2356 cGy, minimum 1830 cGy) had a significantly higher probability of durable local control than those treated with lower doses (median PTV D95 2232 cGy, minimum of 1740 cGy) (p < 0.001). Patients in the high-dose cohort had a 2% cumulative rate of local failure. Histological findings were not associated with local failure, suggesting that radioresistant histological types benefit in particular from radiosurgery. For patients with a favorable prognosis, a higher dose of SRS is important for long-term outcomes.

Peripheral nervous system injury after high-dose single-fraction image-guided stereotactic radiosurgery for spine tumors.

OBJECTIVE The object of this study was to determine the percentage of high-dose (1800-2600 cGy) single-fraction stereotactic radiosurgery (SF-SRS) treatments to the spine that result in peripheral nervous system (PNS) injury. METHODS All patients treated with SF-SRS for primary or metastatic spine tumors between January 2004 and May 2013 and referred to the Rehabilitation Medicine Service for evaluation and treatment of neuromuscular, musculoskeletal, or functional impairments or pain were retrospectively identified. RESULTS Five hundred fifty-seven SF-SRS treatments in 447 patients resulted in 14 PNS injuries in 13 patients. All injures resulted from SF-SRS delivered to the cervical or lumbosacral spine at 2400 cGy. The overall percentage of SF-SRS treatments resulting in PNS injury was 2.5%, increasing to 4.5% when the thoracic spine was excluded from analysis. The median time to symptom onset following SF-SRS was 10 months (range 4-32 months). The plexus (cervical, brachial, and/or lumbosacral) was affected clinically and/or electrophysiologically in 12 (86%) of 14 cases, the nerve root in 2 (14%) of 14, and both in 6 (43%) of 14 cases. All patients experienced pain and most (93%) developed weakness. Peripheral nervous system injuries were CTCAE Grade 1 in 14% of cases, 2 in 64%, and 3 in 21%. No dose relationship between SF-SRS dose and PNS injury was detected. CONCLUSIONS Single-fraction SRS to the spine can result in PNS injury with major implications for function and quality of life.

A quantitative analysis of craniopharyngioma cyst expansion during and after radiation therapy and surgical implications.

OBJECTIVE When complete resection of craniopharyngioma is not achievable or the sequelae are prohibitive, limited surgery and radiation therapy have demonstrated excellent local disease control while minimizing treatment-related sequelae. When residual tissue exists, there is a propensity for further cyst development and expansion during and after radiation therapy. This can result in obstructive hydrocephalus, visual changes, and/or clinical decline. The authors present a quantitative analysis of cyst expansion during and after radiotherapy and examine how it affected subsequent management. METHODS The authors performed an institutional review board-approved retrospective study of patients with histologically confirmed craniopharyngioma treated between 2000 and 2015 with surgery and intensity-modulated radiation therapy (IMRT) at a single institution. Volumetric measurements of cyst contours were generated by radiation oncology treatment planning software postoperatively, during IMRT, and up to 12 months after IMRT. Patient, tumor, and treatment-related variables were collected until the last known follow-up and were analyzed. RESULTS Twenty-seven patients underwent surgery and IMRT. The median total radiation dose was 54 Gy. Of the 27 patients, 11 patients (40.7%) demonstrated cyst expansions within 1 year of IMRT. Of note, all tumors with cyst expansion were radiographically Puget Grade 2. Maximal cyst expansion peaked at 4.27 months following radiation therapy, with a median volume growth of 4.1 cm3 (mean 9.61 cm3) above the postoperative cyst volume. Eight patients experienced spontaneous cyst regression without therapeutic intervention. Three patients experienced MRI-confirmed cyst enlargement during IMRT, all of whom required adaptive planning to ensure adequate coverage of the entire tumor volume. Two of these 3 patients required ventriculoperitoneal shunt placement and additional intervention. One underwent additional resection, and the other had placement of an intracystic catheter for aspiration and delivery of intracystic interferon within 12 months of completing IMRT. All 3 patients now have stable disease. CONCLUSIONS Craniopharyngioma cyst expansion occurred in approximately 40% of the patients during or after radiotherapy. In the majority of patients, cyst expansion was a self-limiting process and did not confer a worse outcome. During radiotherapy, cyst expansion may be apparent on image-guided radiation therapy. Adaptive IMRT planning may be required to ensure that the intended IMRT dose covers the entire tumor and cyst volume. The sequelae of cyst expansion include progressive hydrocephalus, which may be treated with a shunt. For patients with solitary cyst expansion, cyst aspiration and/or intracystic interferon may result in disease control.

A Kindler syndrome-associated squamous cell carcinoma treated with radiotherapy.

Kindler syndrome1, 2 is a genetic disorder mainly characterized by increased skin fragility and photosensitivity,3, 4 making the use of treatments based on radiation difficult or even prohibited. Thus, cases reporting Kindler syndrome patients treated with radiotherapy are rare. In this study, we report clinical outcomes and care provided for a rare case of a Kindler syndrome patient submitted to radiotherapy. Diagnosed with squamous cell carcinoma involving the buccal mucosa, the patient was exclusively treated with radiotherapy, with 70 Gy delivered on the PTV with the Volumetric Modulated Arc technique. The patient's reaction regarding control of the lesion is relevant compared to patients not affected by the syndrome. We noticed acute reactions of the skin and buccal mucosa after few radiotherapy sessions, followed by a fast reduction in the tumor volume. The efficacy of radiotherapy along with multidisciplinary actions allowed treatment continuity, leading to a complete control of the lesion and life quality improvement and showed that the use of radiotherapy on Kindler syndrome patients is possible.