Cancer Radiotherapie最新文献

Purpose

Many series have compared voice quality after radiotherapy or surgery for cT1 glottic carcinoma. Different meta-analyses identify better results for radiotherapy while others do not identify any difference, some finally find a superiority of surgery. The purpose of this study was to compare the voice quality in the long term of patients who underwent transoral surgery versus exclusive irradiation for the treatment of cT1 glottic carcinoma.

Material and methods

The VOQUAL study was a pilot comparative multicenter cross-sectional study. The primary endpoint was the Voice Handicap Index comparison between two groups (radiotherapy or surgery). The voice assessment also consisted in the heteroevaluation of voice quality by the Grade, Roughness, Breathness, Asthenia, and Strain rating scale reported by Hirano.

Results

The study included 41 adult patients with cT1 carcinoma of the vocal cord treated by cordectomy or exclusive radiation in two oncologic centers. The median Voice Handicap Index value was 20 [8; 32.5] in the surgery group and 10 [4; 18.5] in the radiotherapy group. There was no statistically significant difference between the median values and the various components F, P and E of the questionnaire (P = 0.1585). The median value of the numeric dysphonia Grade, Roughness, Breathness, Asthenia, and Strain scale was 2 [0; 5] in the surgery group and 2 [0.25; 3.75] in the radiotherapy group. There was no statistically significant difference between these values (P = 0.78).

Conclusion

Our study did not show any significant difference on the primary endpoints of Voice Handicap Index and Grade, Roughness, Breathness, Asthenia, and Strain scores.

Level of evidence

III. Clinical trial registration: The VOQUAL study was registered on the ClinicalTrials.gov platform under the number NCT04447456, in July 2020.

Purpose

This study aimed to design an autodelineation model based on convolutional neural networks for generating high-risk clinical target volumes and organs at risk in image-guided adaptive brachytherapy for cervical cancer.

Materials and methods

A novel SERes-u-net was trained and tested using CT scans from 98 patients with locally advanced cervical cancer who underwent image-guided adaptive brachytherapy. The Dice similarity coefficient, 95th percentile Hausdorff distance, and clinical assessment were used for evaluation.

Results

The mean Dice similarity coefficients of our model were 80.8%, 91.9%, 85.2%, 60.4%, and 82.8% for the high-risk clinical target volumes, bladder, rectum, sigmoid, and bowel loops, respectively. The corresponding 95th percentile Hausdorff distances were 5.23 mm, 4.75 mm, 4.06 mm, 30.0 mm, and 20.5 mm. The evaluation results revealed that 99.3% of the convolutional neural networks-generated high-risk clinical target volumes slices were acceptable for oncologist A and 100% for oncologist B. Most segmentations of the organs at risk were clinically acceptable, except for the 25% sigmoid, which required significant revision in the opinion of oncologist A. There was a significant difference in the clinical evaluation of convolutional neural networks-generated high-risk clinical target volumes between the two oncologists (P < 0.001), whereas the score differences of the organs at risk were not significant between the two oncologists. In the consistency evaluation, a large discrepancy was observed between senior and junior clinicians. About 40% of SERes-u-net-generated contours were thought to be better by junior clinicians.

Conclusion

The high-risk clinical target volumes and organs at risk of cervical cancer generated by the proposed convolutional neural networks model can be used clinically, potentially improving segmentation consistency and efficiency of contouring in image-guided adaptive brachytherapy workflow.

Purpose

The purpose of this study was to assess if multicriteria optimization could limit interoperator variability in radiation therapy planning and assess if this method could contribute to target volume coverage and sparing of organ at risk for intensity-modulated curative radiation therapy of head and neck cancers.

Material and methods

We performed a retrospective analysis on 20 patients treated for an oropharyngeal or oral cavity squamous cell carcinoma. We carried out a comparative dosimetric study of manual plans produced with Precision® software, compared with the plans proposed using the multicriteria optimization method (RayStation®). We assessed interoperator reproducibility on the first six patients, and dosimetric contribution in sparing organs at risk using the multicriteria optimization method.

Results

Median age was 69 years, most lesions were oropharyngeal carcinoma (65%), and 35% lesions were stage T3. First, we obtained a high degree of similarity between the four operator measurements for each patient at the level of each organ. Intraclass correlation coefficients were greater than 0.85. Second, we observed a significant dosimetric benefit for contralateral parotid gland, homolateral and contralateral masseter muscles, homolateral and contralateral pterygoid muscles and for the larynx (P < 0.05). For the contralateral parotid gland, the mean dose difference between the multicriteria optimization and manual plans was −2.0 Gy (P = 0.01). Regarding the larynx, the mean dose difference between the two plans was −4.6 Gy (P < 0.001).

Conclusion

Multicriteria optimization is a reproducible technique and faster than manual optimization. It allows dosimetric advantages on organs at risk, especially for those not usually taken into consideration in manual dosimetry. This may lead to improved quality of life.

Over the last decades, the use of artificial intelligence, machine learning and deep learning in medical fields has skyrocketed. Well known for their results in segmentation, motion management and posttreatment outcome tasks, investigations of machine learning and deep learning models as fast dose calculation or quality assurance tools have been present since 2000. The main motivation for this increasing research and interest in artificial intelligence, machine learning and deep learning is the enhancement of treatment workflows, specifically dosimetry and quality assurance accuracy and time points, which remain important time-consuming aspects of clinical patient management. Since 2014, the evolution of models and architectures for dose calculation has been related to innovations and interest in the theory of information research with pronounced improvements in architecture design. The use of knowledge-based approaches to patient-specific methods has also considerably improved the accuracy of dose predictions. This paper covers the state of all known deep learning architectures and models applied to external radiotherapy with a description of each architecture, followed by a discussion on the performance and future of deep learning predictive models in external radiotherapy.

Neoadjuvant chemoradiotherapy is the standard treatment for patients with locally advanced rectal cancers owing to its ability to downstage primary tumours. Some patients can achieve pathological complete response after neoadjuvant therapy, and can adopt a “watch and wait” treatment strategy to avoid overtreatment. Therefore, it is essential to develop strategies for predicting responses to neoadjuvant therapy. Radiomics has shown great potential in extracting tumour features from high-throughput medical images for the construction of mathematics models for predicting the effects of anticancerous therapies. Herein, we explored MRI-based radiomics and found that it can predict responses of locally advanced rectal cancers to chemoradiation. Efficient radiomics model allow early-stage prediction of the effect of neoadjuvant chemoradiotherapy on locally advanced rectal cancers. It helps clinicians to make informed therapeutic decisions. In this review, we discuss the workflow of radiomics, and summarize the clinical application of MRI-based radiomics in predicting pathological complete response to neoadjuvant chemoradiotherapy of locally advanced rectal cancer.

Purpose

Neurocytomas represent 0.25 to 0.5% of primary brain tumours and are mainly found in young adults. These tumours have neuronal differentiation. The cornerstone treatment is neurosurgery. The efficacy of other therapies, including radiotherapy, is still unclear. The objective of this study was to evaluate the management of central neurocytomas and the role of radiotherapy.

Materials and methods

All adult patients (age 18 years or older) newly diagnosed with a histologically confirmed neurocytoma between 2006 and 2015 in France were included.

Results

One hundred and sixteen patients were diagnosed with a central neurocytoma during the study period. All patients underwent surgical resection, and six received adjuvant radiotherapy. Eleven patients received radiotherapy due to progression. After a median follow-up of 68.7 months, local failure occurred in 29 patients. The 5-year local control rate was 73.4%. According to univariate analysis, marker of proliferation Ki67 index greater than 2% (hazard ratio [HR]: 1.48; confidence interval [CI]: 1.40–1.57; P = 0.027) and subtotal resection (HR: 8.48; CI: 8.01–8.99; P < 0.001) were associated with an increase in local failure. Gross total resection was associated with a higher risk of sequelae epilepsy (HR: 3.62; CI: 3.42–3.83; P < 0.01) and memory disorders (HR: 1.35; CI: 1.07–1.20; P < 0.01). Ten patients (8.6%) died during the follow-up. The 10-year overall survival rate was 89.0%. No prognostic factors for overall survival were found.

Conclusion

The analysis showed that patients who underwent subtotal surgical resection, particularly when the tumour had a Ki67 index greater than 2%, had an increased risk of local recurrence. These patients could benefit from adjuvant radiotherapy.

Purpose

Prostate cancer is the most frequent cancer among men and radiotherapy hypofractionation regimens have become standard treatments for the localized stages, but the absence of increased risk of acute and late genitourinary or gastrointestinal toxicity of the dose escalation still must be demonstrated.

Material and methods

The study population included all patients with localized prostatic adenocarcinoma treated at the institut Curie from February 2016 to March 2018 by external radiation delivered by a linear accelerator using an image-guided conformal intensity modulation technique at a total dose of 75 Gy in 30 fractions of 2.5 Gy in the planning target volume that included the prostate and the proximal seminal vesicles, and could be paired with a prophylactic lymph node radiotherapy at 46 Gy in 23 fractions with simultaneous integrated boost.

Results

A total of 166 patients were included. Among them, 68.6% were unfavourable intermediate or (very) high risk. The median age and follow-up were 71.4 years and 3.96 years. One hundred and forty-nine patients received prophylactic lymph node radiotherapy (89.8%). One hundred and thirty-one patients received hormonotherapy (78.9%). Genito-urinary toxicity events of grades 2 or above during radiotherapy, at 6 months, 1 year and 5 years were respectively 36.7%, 8.8%, 3.1% and 4.7%. Two patients had late grade 4 toxicity at 5 years (1.6%). Grade 2 gastrointestinal toxicity events during radiotherapy, 6 months, 1 year and 5 years were respectively 15.1%, 1.9%, 14.6% and 9.3%. Of these, eight patients had grade 3 toxicity (6.2%). There was no grade 4 toxicity. Analyses did not reveal any predictive factor for toxicity. The 5-year overall, progression-free, and specific survival rates were respectively 82.4%, 85.7%, and 93.3%. Serum prostate specific antigen concentration and cardiovascular risk factors were found to be predictive factors of deterioration in overall survival (P = 0.0028 for both).

Conclusion

External radiotherapy for localized prostatic cancer with our moderately hypofractionated dose escalation regimen is well tolerated. In the absence of increased late toxicity, the analysis of the modes of long-term relapses will be interesting to determine the benefit of this dose escalation on local and distant relapses.

Purpose

This study aimed to develop nomograms that combine clinical factors and MRI tumour regression grade to predict the pathological response of mid-low locally advanced rectal cancer to neoadjuvant chemoradiotherapy.

Methods

The retrospective study included 204 patients who underwent neoadjuvant chemoradiotherapy and surgery between January 2013 and December 2021. Based on pathological tumour regression grade, patients were categorized into four groups: complete pathological response (pCR, n = 45), non-complete pathological response (non-pCR; n = 159), good pathological response (pGR, n = 119), and non-good pathological response (non-pGR, n = 85). The patients were divided into a training set and a validation set in a 7:3 ratio. Based on the results of univariate and multivariate analyses in the training set, two nomograms were respectively constructed to predict complete and good pathological responses. Subsequently, these predictive models underwent validation in the independent validation set. The prognostic performances of the models were evaluated using the area under the curve (AUC).

Results

The nomogram predicting complete pathological response incorporates tumour length, post-treatment mesorectal fascia involvement, white blood cell count, and MRI tumour regression grade. It yielded an AUC of 0.787 in the training set and 0.716 in the validation set, surpassing the performance of the model relying solely on MRI tumour regression grade (AUCs of 0.649 and 0.530, respectively). Similarly, the nomogram predicting good pathological response includes the distance of the tumour's lower border from the anal verge, post-treatment mesorectal fascia involvement, platelet/lymphocyte ratio, and MRI tumour regression grade. It achieved an AUC of 0.754 in the training set and 0.719 in the validation set, outperforming the model using MRI tumour regression grade alone (AUCs of 0.629 and 0.638, respectively).

Conclusions

Nomograms combining MRI tumour regression grade with clinical factors may be useful for predicting pathological response of mid-low locally advanced rectal cancer to neoadjuvant chemoradiotherapy. The proposed models could be applied in clinical practice after validation in large samples.

Purpose

Secondary breast cancer is a frequent late adverse event of mediastinal Hodgkin lymphoma radiotherapy. Secondary breast cancers overwhelmingly correspond to ductal carcinoma and develop from the glandular mammary tissue. In addition, during childhood, radiation overexposure of the glandular tissue may lead to a late breast hypotrophy at adult age. The aim of this study was to evaluate the radiation exposure to the glandular tissue in patients treated for mediastinal Hodgkin lymphoma with intensity-modulated proton therapy, in order to evaluate the potential dosimetric usefulness of its delineation for breast sparing.

Materials and methods

Sixteen consecutive intermediate-risk mediastinal female patients with Hodgkin lymphoma treated with consolidation radiation with deep inspiration breath hold intensity-modulated proton therapy to the total dose of 30 Gy were included. Breasts were delineated according to the European Society for Radiotherapy and Oncology guidelines for treatment optimization (“clinical organ at risk”). The glandular tissue (“glandular organ at risk”) was retrospectively contoured on the initial simulation CT scans based on Hounsfield unit (HU) values, using a range between −80 HU and 500 HU.

Results

The mean and maximum doses delivered to the glandular organ at risk were significantly lower than the mean and maximum doses delivered to the clinical organ at risk, but were statistically correlated. Glandular organ at risk volumes were significantly smaller.

Conclusion

Optimizing the treatment plans on the clinical breast contours will systematically lead to overestimation of the dose received to the glandular tissue and, consequently, to an indistinct and involuntary improved glandular tissue sparing. As such, our findings do not support the consideration of the glandular tissue as an additional organ at risk when planning intensity-modulated proton therapy for mediastinal Hodgkin lymphoma in female patients.