Application of a smart 18F-FDG-PET adaptive threshold segmentation algorithm for the biological target volume delineation in head and neck cancer.

BACKGROUND: The aim of the present study is to evaluate the reliability of a 18F-fluorodeoxyglucose (18F-FDG) PET adaptive threshold segmentation (ATS) algorithm, previously validated in a preclinical setting on several scanners, for the biological target volume (BTV) delineation of head and neck radiotherapy planning. METHODS: [18F]FDG PET ATS algorithm was studied in treatment plans of head and neck squamous cell carcinoma on a dedicated workstation (iTaRT, Tecnologie Avanzate, Turin, Italy). BTVs segmented by the present ATS algorithm (BTVATS) were compared with those manually segmented for the original radiotherapy treatment planning (BTVVIS). We performed a qualitative and quantitative volumetric analysis with a comparison tool within the ImSimQA TM software package (Oncology Systems Limited, Shrewsbury, UK). We reported figures of merit (FOMs) to convey complementary information: Dice Similarity Coefficient, Sensitivity Index, and Inclusiveness Index. RESULTS: The study was conducted on 32 treatment plans. Median BTVATS was 11 cm3 while median BTVVIS was 14 cm3. The median Dice Similarity Coefficient, Sensitivity Index, Inclusiveness Index were 0.72, 63%, 88%, respectively. Interestingly, the median volume and the median distance of the voxels that are over contoured by ATS were respectively 1 cm3 and 1 mm. CONCLUSIONS: ATS algorithm could be a smart and an independent operator tool when implemented for 18F-FDG-PET-based tumor volume delineation. Furthermore, it might be relevant in case of BTV-based dose painting.

Radiotherapy for vestibular schwannoma: Review of recent literature results.

BACKGROUND: The management of vestibular schwannoma is still a quite controversial issue and can include wait and see policy, surgery and radiotherapy, mainly with stereotactic technique. The purpose of this study is to review the results of recent clinical series treated by radiotherapy. MATERIALS AND METHODS: Literature search was performed by Pubmed and Scopus by using the words "vestibular schwannoma, acoustic neuroma, radiotherapy, radiosurgery". RESULTS: Management options of VS include wait and see, surgery and radiotherapy. In case of small lesions, literature data report local control rates higher than 90% after radiosurgery (SRS) similar those of surgical techniques. Recent literature reviews show favourable functional outcome by using SRS. Several literature data support the use of fractionated stereotactic radiotherapy (FSRT) in case of large inoperable lesions. CONCLUSION: Radiotherapy plays a relevant role in the treatment of VS. In small-size lesions, SRS can guarantee similar local control and potentially better function outcome compared to surgery. In case of large and irregularly shaped lesions, FSRT can be the used when surgery is not feasible.

Stereotactic radiation therapy for skull base recurrences: Is a salvage approach still possible?

AIM: A literature review was performed to analyse the role of stereotactic radiotherapy given in a single shot or in a fractionated fashion for recurrent skull base tumours in order to ascertain if it can be a real salvage approach. BACKGROUND: The management of recurrent skull base tumours can have a curative or palliative intent and mainly includes surgery and RT. MATERIALS AND METHODS: One-thousand-ninety-one articles were found in the search databases and the most relevant of them were analysed and briefly described. RESULTS: Data on recurrences of meningioma, pituitary adenoma, craniopharyngioma, chordoma and chondrosarcoma, vestibular schwannoma, glomus jugulare tumours, olfactory neuroblastoma and recurrences from head and neck tumours invading the base of skull are reported highlighting the most relevant results in terms of local control, survival, side effects and complications. CONCLUSIONS: In conclusion, it emerges that SRS and FSRT are effective and safe radiation modalities of realize real salvage treatment for recurrent skull base tumours.

Clinical evaluation of a deep learning CBCT auto-segmentation software for prostate adaptive radiation therapy.

Purpose: Aim of the present study is to characterize a deep learning-based auto-segmentation software (DL) for prostate cone beam computed tomography (CBCT) images and to evaluate its applicability in clinical adaptive radiation therapy routine. Materials and methods: Ten patients, who received exclusive radiation therapy with definitive intent on the prostate gland and seminal vesicles, were selected. Femoral heads, bladder, rectum, prostate, and seminal vesicles were retrospectively contoured by four different expert radiation oncologists on patients CBCT, acquired during treatment. Consensus contours (CC) were generated starting from these data and compared with those created by DL with different algorithms, trained on CBCT (DL-CBCT) or computed tomography (DL-CT). Dice similarity coefficient (DSC), centre of mass (COM) shift and volume relative variation (VRV) were chosen as comparison metrics. Since no tolerance limit can be defined, results were also compared with the inter-operator variability (IOV), using the same metrics. Results: The best agreement between DL and CC was observed for femoral heads (DSC of 0.96 for both DL-CBCT and DL-CT). Performance worsened for low-contrast soft tissue organs: the worst results were found for seminal vesicles (DSC of 0.70 and 0.59 for DL-CBCT and DL-CT, respectively). The analysis shows that it is appropriate to use algorithms trained on the specific imaging modality. Furthermore, the statistical analysis showed that, for almost all considered structures, there is no significant difference between DL-CBCT and human operator in terms of IOV. Conclusions: The accuracy of DL-CBCT is in accordance with CC; its use in clinical practice is justified by the comparison with the inter-operator variability.

Hypofractionation and Concomitant Boost in Ductal Carcinoma In Situ (DCIS): Analysis of a Prospective Case Series with Long-Term Follow-Up.

We previously reported on a cohort of breast cancer patients affected with ductal carcinoma in situ (DCIS) that were treated with breast conservative surgery and hypofractionated whole-breast radiotherapy with a concomitant boost to the lumpectomy cavity. We now report on the long-term results of the oncological and toxicity outcomes, at a median follow-up of 11.2 years. We also include an analysis of the predictive factors for local recurrence (LR). Eighty-two patients with long-term observation were considered for this report. All received hypofractionated post-operative radiotherapy with a concomitant boost (45 Gy/20 fractions to the whole breast and 50 Gy/20 fractions to the lumpectomy cavity). We report on LC rates at 5 and 10 years, overall survival (OS), and breast-cancer-specific survival (BCSS), employing the Kaplan-Meier method. Cox proportional regression analysis was used to determine the role of selected clinical parameters on the risk of local recurrence, by the univariate and multivariate models. After a median follow-up of 11.2 years (range 5-15 years), 9 pts (11%) developed LR. The LR rates at 5 years and 10 years were 2.4% and 8.2%, respectively. The 5- and 10-year overall survival rates were 98.8% and 91.6%, respectively. The 5- and 10-year breast-cancer-specific survival rates were 100.0% and 99.0%. Late skin and subcutaneous toxicities were generally mild, and cosmetic results were good-excellent for most patients. For the univariate regression analysis, ER positive status (HR; 95% CI, p = 0.021), PgR positive status (HR; 95% CI, p = 0.012), and the aggregate data of positive hormonal status (HR; 95% CI, p = 0.021) were inversely correlated to LR risk. Conversely, a high tumor grade (G3) was directly correlated with the risk of LR (HR; 95% CI, p = 0.048). For the multivariate regression analysis, a high tumor grade (G3) confirmed its negative impact on LR (HR 0.40; 95% CI 0.19-0.75, p = 0.047). Our long-term data demonstrate hypofractionated whole-breast radiotherapy with a concomitant boost to be feasable, effective, and tolerable. Our experience suggests positive hormonal status to be protective with respect to LR risk. A high tumor grade is a risk factor for LR.

Implementation of a Commercial Deep Learning-Based Auto Segmentation Software in Radiotherapy: Evaluation of Effectiveness and Impact on Workflow.

Proper delineation of both target volumes and organs at risk is a crucial step in the radiation therapy workflow. This process is normally carried out manually by medical doctors, hence demanding timewise. To improve efficiency, auto-contouring methods have been proposed. We assessed a specific commercial software to investigate its impact on the radiotherapy workflow on four specific disease sites: head and neck, prostate, breast, and rectum. For the present study, we used a commercial deep learning-based auto-segmentation software, namely Limbus Contour (LC), Version 1.5.0 (Limbus AI Inc., Regina, SK, Canada). The software uses deep convolutional neural network models based on a U-net architecture, specific for each structure. Manual and automatic segmentation were compared on disease-specific organs at risk. Contouring time, geometrical performance (volume variation, Dice Similarity Coefficient-DSC, and center of mass shift), and dosimetric impact (DVH differences) were evaluated. With respect to time savings, the maximum advantage was seen in the setting of head and neck cancer with a 65%-time reduction. The average DSC was 0.72. The best agreement was found for lungs. Good results were highlighted for bladder, heart, and femoral heads. The most relevant dosimetric difference was in the rectal cancer case, where the mean volume covered by the 45 Gy isodose was 10.4 cm3 for manual contouring and 289.4 cm3 for automatic segmentation. Automatic contouring was able to significantly reduce the time required in the procedure, simplifying the workflow, and reducing interobserver variability. Its implementation was able to improve the radiation therapy workflow in our department.

Effect of delaying surgery by more than 10 weeks after neoadjuvant therapy in rectal cancer: a single institution experience.

The optimal timing of surgery after neoadjuvant chemoradiotherapy (CRT) in locally advanced rectal cancer is still controversial. Aim of this study was to evaluate the effect of increasing time interval between the end of CRT and surgery on pathological outcomes. This is a retrospective analysis on 114 patients treated with long-course neoadjuvant RT with or without chemotherapy between January 2005 and September 2020. 43 patients underwent surgery within 10 weeks from the end of CRT (1st group), whereas 71 patients underwent total mesorectal excision with a time interval equal or greater than 10 weeks (2nd group). Primary endpoint was pCR (pathological complete response). Secondary endpoints were near pCR (ypT0-1 N0), tumor downstaging (ypT less than cT), nodal downstaging (ypN less than cN), and overall response comparing clinical with pathological TN stage. Overall, the pCR rate was 8.8%, whereas we observed no significantly difference in primary endpoint between the two groups. Considering near pCR, a trend toward significant difference in favor of 2nd group was seen (p = 0.072). Tumor and nodal downstaging rates were 39.5%, 41.9%, 59.2%, and 56.3% in the 1st and 2nd group, respectively, with a statistically significant difference for T category (p = 0.042). Overall response rates (TN stage) showed a trend toward significant difference in favor of patients of the ≥ 10 week group (p = 0.059). Our study suggests that a prolonged time interval between the end of CRT and surgery (≥ 10 weeks) increases pathological response rates.

Delta4 Discover transmission detector: A comprehensive characterization for in-vivo VMAT monitoring.

OBJECTIVE: To investigate the dosimetric behaviour, influence on photon beam fluence and error detection capability of Delta4 Discover transmission detector. METHODS: The transmission detector (TRD) was characterized on a TrueBeam linear accelerator with 6 MV beams. Linearity, reproducibility and dose rate dependence were investigated. The effect on photon beam fluence was evaluated in terms of beam profiles, percentage depth dose, transmission factor and surface dose for different open field sizes. The transmission factor of the 10x10 cm2 field was entered in the TPS's configuration and its correct use in the dose calculation was verified recalculating 17 clinical IMRT/VMAT plans. Surface dose was measured for 20 IMRT fields. The capability to detect different delivery errors was investigated evaluating dose gamma index, MLC gamma index and leaf position of 15 manually modified VMAT plans. RESULTS: TRD showed a linear dependence on MU. No dose rate dependence was observed. Short-term and long-term reproducibility were within 0.1% and 0.5%. The presence of the TRD did not significantly affect PDDs and profiles. The transmission factor of the 10x10 cm2 field size was 0.985 and 0.983, for FF and FFF beams respectively. The 17 recalculated plans met our clinical gamma-index passing rate, confirming the correct use of the transmission factor by the TPS. The surface dose differences for the open fields increase for shorter SSDs and greater field size. Differences in surface dose for the IMRT beams were less than 2%. Output variation ≥2%, collimator angle variations within 0.3°, gantry angle errors of 1°, jaw tracking and leaf position errors were detected. CONCLUSIONS: Delta4 Discover shows good linearity and reproducibility, is not dependent on dose rate and does not affect beam quality and dose profiles. It is also capable to detect dosimetric and geometric errors and therefore it is suitable for monitoring VMAT delivery.