Evaluation of safety margins for cone beam CT-based adaptive prostate radiotherapy

Adaptive radiotherapy is characterized by the use of a daily imaging system, such as CBCT (Cone-Beam Computed Tomography) images to re-optimize the treatment based on the daily anatomy and position of the patient. By systematically re-delineating the Clinical Target Volume (CTV) at each fraction, target delineation uncertainty features a random component instead of a pure systematic. The goal of this work is to identify the random and systematic contributions of the delineation error and compute a new relevant Planning Target Volume (PTV) safety margin. 169 radiotherapy sessions from 10 prostate cancer patients treated on the Varian ETHOS treatment system have been analyzed. Intra-patient and inter-patient delineation variabilities were computed in six directions, by considering the prostate as a rigid, non-rotating volume. By doing so, we were able to directly compare the delineations done by the physicians on daily CBCT images with the initial delineation done on the CT-sim and MRI, and sort them by direction using the polar coordinates of the points. The computed variabilities were then used to compute a PTV margin based on Van Herk margin recipe. The total margin computed with random and systematic delineation uncertainties was of 2.7, 2.4, 5.6, 4.8, 4.9 and 3.6 mm in the left, right, anterior, posterior, cranial and caudal directions, respectively. According to our results, the gain offered by the separation of the delineation uncertainty into systematic and random contributions due to the adaptive delineation process justifies a reduction of the PTV margin down to 3 to 5 mm in every direction.

[Proposal for the delineation of postoperative primary clinical target volumes in maxillary sinus and nasal cavity cancers]

In this article, we propose a consensus delineation of postoperative clinical target volumes for the primary tumour in maxillary sinus and nasal cavity cancers. These guidelines are developed based on radioanatomy and the natural history of those cancers. They require the fusion of the planning CT with preoperative imaging for accurate positioning of the initial GTV and the combined use of the geometric and anatomical concepts for the delineation of clinical target volume for the primary tumour. This article does not discuss the indications of external radiotherapy (nor concurrent systemic treatment) but focuses on target volumes when there is an indication for radiotherapy.

Contouring aid tools in radiotherapy. Smoothing: the false friend

OBJECTIVE

Contouring accuracy is critical in modern radiotherapy. Several tools are available to assist clinicians in this task. This study aims to evaluate the performance of the smoothing tool in the ARIA system to obtain more consistent volumes.

METHODS

Eleven different geometric shapes were delineated in ARIA v15.6 (Sphere, Cube, Square Prism, Six-Pointed Star Prism, Arrow Prism, And Cylinder and the respective volumes at 45° of axis deviation (_45)) in 1, 3, 5, 7, and 10 cm side or diameter each. Post-processing drawing tools to smooth those first-generated volumes were applied in different options (2D-ALL vs 3D) and grades (1, 3, 5, 10, 15, and 20). These volumetric transformations were analyzed by comparing different parameters: volume changes, center of mass, and DICE similarity coefficient index. Then we studied how smoothing affected two different volumes in a head and neck cancer patient: a single rounded node and the volume delineating cervical nodal areas.

RESULTS

No changes in data were found between 2D-ALL or 3D smoothing. Minimum deviations were found (range from 0 to 0.45 cm) in the center of mass. Volumes and the DICE index decreased as the degree of smoothing increased. Some discrepancies were found, especially in figures with cleft and spikes that behave differently. In the clinical case, smoothing should be applied only once throughout the target delineation process, preferably in the largest volume (PTV) to minimize errors.

CONCLUSION

Smoothing is a good tool to reduce artifacts due to the manual delineation of radiotherapy volumes. The resulting volumes must be always carefully reviewed.

Using multiparametric Magnetic Resonance Imaging and Prostate Specific Membrane Antigen Positron Emission Tomography to detect and delineate the gross tumour volume of intraprostatic lesions - A systematic review and meta-analysis

BACKGROUND AND PURPOSE

Radiation therapy is used frequently for patients with prostate cancer. Dose escalation to intraprostatic lesions (IPLs) has been shown to improve oncologic outcomes, without increasing toxicity. Both multiparametric MRI (mpMRI) and PSMA PET can be used to identify IPLs.

MATERIALS AND METHODS

A systematic review was conducted to determine the ability of mpMRI, PSMA PET and their combination to detect IPLs prior to radical prostatectomy (RP) as correlated with the histology. Trials included patients that had mpMRI, PSMA PET, or both, prior to RP. The quality of the histopathological-radiological co-registration was assessed as high or low for each study. Recorded outcomes include sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). A meta-analysis was conducted using a bivariate model to determine the pooled sensitivity and specificity for each imaging modality. This systematic review was registered through PROSPERO (CRD42023389092).

RESULTS

Altogether, 42 studies were included in the systematic review. Of these, 20 could be included in the meta-analysis. The pooled sensitivity (95 % CI), specificity (95 % CI) and AUROC for mpMRI (n = 13 studies) were 64.7 % (50.2 % - 76.9 %), 86.4 % (79.7 % - 91.1 %), and 0.852; the pooled outcomes for PSMA PET (n = 12) were 75.7 % (64.0 % - 84.5 %), 87.1 % (80.2 % - 91.9 %), and 0.889; for their combination (n = 5), the pooled outcomes were 70.3 % (64.1 % - 75.9 %), 81.9 % (71.9 % - 88.8 %), and 0.796. When reviewing studies with a high-quality histopathological-radiological co-registration, IPL delineation recommendations varied by study and the imaging modality used.

CONCLUSION

All of mpMRI, PSMA PET or their combination were found to have very good diagnostic outcomes for detecting IPLs. Recommendations for delineating IPLs varied based on the imaging modalities used and between research groups. Consensus guidelines for IPL delineation would help with creating consistency for focal boost radiation treatments in future studies.

How to contour the different heart subregions for future deep-learning modeling of the heart: A practical pictorial proposal for radiation oncologists

There are currently no accurate rules for manually delineating the subregions of the heart (cavities, vessels, aortic/mitral valves, Planning organ at Risk Volumes for coronary arteries) with the perspective of deep-learning based modeling. Our objective was to present a practical pictorial view for radiation oncologists, based on the RTOG atlas and anatomical complementary considerations for the cases where the RTOG guidelines are missing.

Involved-site Radiotherapy Delineation Dilemmas in the Treatment of Adult Hodgkin Lymphoma: Turkish Society for Radiation Oncology Hematological Oncology, Pediatric Oncology and TBI Study Group Case-based Questionnaire Review (TROD 03-005)

AIMS

The International Lymphoma Radiation Oncology Group (ILROG) defined involved-site radiotherapy (ISRT) guidelines. These rules offer a certain variability that allows for autonomous decision-making in diverse clinical settings. However, this flexibility also gives rise to conflicts about the selection of treatment fields in the daily decision-making process. The aim of this study was to show the extent of interobserver variability when ILROG-ISRT recommendations were used in different clinical scenarios.

MATERIALS AND METHODS

The 10-question survey used in our study consisted of two parts (part A and part B) and was prepared by four senior radiation oncologists experienced in the haemato-oncology field. The results were presented by stratifying according to clinical experience (<10 years, ≥10 years). Binomial tests (one-sided) were conducted to assess whether answers for each group and the whole group reached a consensus.

RESULTS

Twenty-six radiation oncologists, 13 of whom had less than 10 years of experience and 13 seniors, participated in the survey. Eighty per cent of respondents thought ILROG did not bring sufficient solutions for all clinical scenarios but offered solutions in some cases. In different case-based scenarios, the consensus among the respondents decreased down to 38%. Senior radiation oncologists were found to have more doubts about the adequacy of current guidelines.

CONCLUSIONS

ILROG guidelines allow for a high degree of variability in real-life clinical scenarios and different interpretation of the recommendations may lead to increased toxicity and recurrences. Therefore, there is a need for refinement in ISRT delineation strategies. On behalf of the Turkish Society for Radiation Oncology Hematological Oncology, Pediatric Oncology and TBI Study Group, we are planning to carry out further educational contouring sessions to detect the interobserver variability in real-life contouring cases.

Dosimetric analysis of brachial plexopathy after stereotactic body radiotherapy: Significance of organ delineation

OBJECTIVES

Examine the significance of contouring the brachial plexus (BP) for toxicity estimation and select metrics for predicting radiation-induced brachial plexopathy (RIBP) after stereotactic body radiotherapy.

MATERIALS AND METHODS

Patients with planning target volume (PTV) ≤ 2 cm from the BP were eligible. The BP was contoured primarily according to the RTOG 1106 atlas, while subclavian-axillary veins (SAV) were contoured according to RTOG 0236. Apical PTVs were classified as anterior (PTV-A) or posterior (PTV-B) PTVs. Variables predicting grade 2 or higher RIBP (RIBP2) were selected through least absolute shrinkage and selection operator regression and logistic regression.

RESULTS

Among 137 patients with 140 BPs (median follow-up, 32.1 months), 11 experienced RIBP2. For patients with RIBP2, the maximum physical dose to the BP (BP-Dmax) was 46.5 Gy (median; range, 35.7 to 60.7 Gy). Of these patients, 54.5 % (6/11) satisfied the RTOG limits when using SAV delineation; among them, 83.3 % (5/6) had PTV-B. For patients with PTV-B, the maximum physical dose to SAV (SAV-Dmax) was 11.2 Gy (median) lower than BP-Dmax. Maximum and 0.3 cc biologically effective doses to the BP based on the linear-quadratic-linear model (BP-BEDmax LQL and BP-BED0.3cc LQL, α/β = 3) were selected as predictive variables with thresholds of 118 and 73 Gy, respectively.

CONCLUSION

Contouring SAV may significantly underestimate the RIBP2 risk in dosimetry, especially for patients with PTV-B. BP contouring indicated BP-BED0.3cc LQL and BP-BEDmax LQL as potential predictors of RIBP2.

Pan-genomic comparison of a potential solvent-tolerant alkaline protease-producing Exiguobacterium sp. TBG-PICH-001 isolated from a marine habitat

The identification and applicability of bacteria are inconclusive until comprehended with genomic repositories. Our isolate, Exiguobacterium sp. TBG-PICH-001 exhibited excellent halo- and organic solvent tolerance with simultaneous production of alkaline protease/s (0.512 IU/mL). The crude protease (1 IU) showed a 43.57% degradation of whey protein. The bulk proteins in the whey were hydrolyzed to smaller peptides which were evident in the SDS-PAGE profile. With such characteristics, the isolate became interesting for its genomic studies. The TBG-PICH-001 genome was found to be 3.14 Mb in size with 17 contigs and 47.33% GC content. The genome showed 3176 coding genes, and 2699 genes were characterized for their functionality. The Next-Generation-Sequencing of the genome identified only the isolate's genus; hence we attempted to delineate its species position. The genomes of the isolate and other representative Exiguobacterium spp. were compared based on orthologous genes (Orthovenn2 server). A pan-genomic analysis revealed the match of TBG-PICH-001 with 15 uncharacterized Exiguobacterium genomes at the species level. All these collectively matched with Exiguobacterium indicum, and the results were reconfirmed through phylogenetic studies. Further, the Exiguobacterium indicum genomes were engaged for homology studies rendering 11 classes of protease genes. Two putative proteases (Zinc metalloprotease and Serine protease) obtained from homology were checked for PCR amplification using genomic DNA of TBG-PICH-001 and other Exiguobacterium genomes. The results showed amplification only in the Exiguobacterium indicum genome. These protease genes, after sequencing, were matched with the TBG-PICH-001 genome. Their presence in its whole genome experimentally validated the study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03796-5.

Comparison of magnetic resonance imaging and CT scan-based delineation of target volumes and organs at risk in the radiation treatment planning of head and neck malignancies

INTRODUCTION

Accuracy of target definition is paramount in radiation treatment planning. The optimal choice of imaging modality to define the tumor volume in head and neck tumors is debatable. The study compared MRI and CT scan-based delineation of target volume and Organs At Risk in head and neck cancers.

MATERIALS AND METHODS

54 head and neck carcinoma patients underwent rigid image registration of planning CT images with MRI images. The gross tumor volume of the primary tumor, node, and organs at risk were delineated on both CT and MRI images. A volumetric evaluation was done for gross tumors, nodes, and organs at risk. Dice Similarity coefficient (DSC), Conformity index(CI), Sensitivity index(SI), and Inclusion index(II) were calculated for gross tumor, node, brainstem, and bilateral parotids.

RESULTS

The mean volume of the tumor in CT and MRI obtained were 41 .94 cc and 34.76 ccs, mean DSC, CI, SI, and II of the tumor were 0.71, 0.56, 67.37, and 79.80. The mean volume of the node in CT and MRI were 12.16 cc and 10.24 cc, mean DSC, CI, SI, and II of the node were 0.61, 0.45, 62.47, and 64. The mean volume of the brainstem in CT and MRI was 24.13 cc and 21.21 cc. The mean volume of the right parotid in CT and MRI was 24.39 cc, 26.04 ccs. The mean volume of left parotid in CT and MRI, respectively, were 23.95 ccs and 25.04 ccs.

CONCLUSIONS

The study shows that MRI may be used in combination with CT for better delineation of target volume and organs at risk for head and neck malignancies.

Target volume delineation for radiotherapy of meningiomas: an ANOCEF consensus guideline

PURPOSE

Radiotherapy is, with surgery, one of the main therapeutic treatment strategies for meningiomas. No prospective study has defined a consensus for the delineation of target volumes for meningioma radiotherapy. Therefore, target volume definition is mainly based on information from retrospective studies that include heterogeneous patient populations. The aim is to describe delineation guidelines for meningioma radiotherapy as an adjuvant or definitive treatment with intensity-modulated radiation therapy and stereotactic radiation therapy techniques. This guideline is based on a consensus endorsed by a multidisciplinary group of brain tumor experts, members of the Association of French-speaking Neuro-oncologists (ANOCEF).

MATERIALS AND METHODS

A 3-step procedure was used. First, the steering group carried out a comprehensive review to identify divergent issues on meningiomas target volume delineation. Second, an 84-item web-questionnaire has been developed to precisely define meningioma target volume delineation in the most common clinical situations. Third, experts members of the ANOCEF were requested to answer. The first two rounds were completed online. A third round was carried out by videoconference to allow experts to debate and discuss the remaining uncertain questions. All questions remained in a consensus.

RESULTS

Limits of the target volume were defined using visible landmarks on computed tomography and magnetic resonance imaging, considering the pathways of tumor extension. The purpose was to develop clear and precise recommendations on meningiomas target volumes.

CONCLUSION

New recommendations for meningiomas delineation based on simple anatomic boundaries are proposed by the ANOCEF. Improvement in uniformity in target volume definition is expected.

The role of standard and novel radiotherapy approaches in management of retroperitoneal sarcomas

Primary non-metastatic retroperitoneal soft tissue sarcoma patients can be cured by radical surgery. However there remains a risk for patients to develop a local recurrence. To minimize this risk, patients with low grade liposarcomas might benefit from preoperative radiotherapy. This review summarizes all issues that should be considered for the irradiation of patients with retroperitoneal soft tissue sarcoma.

Benefits of automated gross tumor volume segmentation in head and neck cancer using multi-modality information

PURPOSE

Gross tumor volume (GTV) delineation for head and neck cancer (HNC) radiation therapy planning is time consuming and prone to interobserver variability (IOV). The aim of this study was (1) to develop an automated GTV delineation approach of primary tumor (GTVp) and pathologic lymph nodes (GTVn) based on a 3D convolutional neural network (CNN) exploiting multi-modality imaging input as required in clinical practice, and (2) to validate its accuracy, efficiency and IOV compared to manual delineation in a clinical setting.

METHODS

Two datasets were retrospectively collected from 150 clinical cases. CNNs were trained for GTV delineation with consensus delineation as ground truth, with either single (CT) or co-registered multi-modal (CT + PET or CT + MRI) imaging data as input. For validation, GTVs were delineated on 20 new cases by two observers, once manually, once by correcting the delineations generated by the CNN.

RESULTS

Both multi-modality CNNs performed better than the single-modality CNN and were selected for clinical validation. Mean Dice Similarity Coefficient (DSC) for (GTVp, GTVn) respectively between automated and manual delineations was (69%, 79%) for CT + PET and (59%,71%) for CT + MRI. Mean DSC between automated and corrected delineations was (81%,89%) for CT + PET and (69%,77%) for CT + MRI. Mean DSC between observers was (76%,86%) for manual delineations and (95%,96%) for corrected delineations, indicating a significant decrease in IOV (p < 10^-5), while efficiency increased significantly (48%, p < 10^-5).

CONCLUSION

Multi-modality automated delineation of GTV of HNC was shown to be more efficient and consistent compared to manual delineation in a clinical setting and beneficial over a single-modality approach.

A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition

PURPOSE

Infrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore, we propose the exploitation of these common spectral changes for brain tumor recognition.

METHODS

Attenuated total reflection IR spectroscopy was performed on fresh specimens of 790 patients within minutes after resection. Using principal component analysis and linear discriminant analysis, a classification model was developed on a subset of glioblastoma (n = 135) and non-neoplastic brain (n = 27) specimens, and then applied to classify the IR spectra of several types of brain tumors.

RESULTS

The model correctly classified 82% (517/628) of specimens as "tumor" or "non-tumor", respectively. While the sensitivity was limited for infiltrative glioma, this approach recognized GBM (86%), other types of primary brain tumors (92%) and brain metastases (92%) with high accuracy and all non-tumor samples were correctly identified.

CONCLUSION

The concept of differentiation of brain tumors from non-tumor brain based on a common spectroscopic tumor signature will accelerate clinical translation of infrared spectroscopy and related technologies. The surgeon could use a single instrument to detect a variety of brain tumor types intraoperatively in future clinical settings. Our data suggests that this would be associated with some risk of missing infiltrative regions or tumors, but not with the risk of removing non-tumor brain.

Recent advances in lean NAFLD

As the predominant type of chronic liver disease, the growing prevalence of nonalcoholic fatty liver disease (NAFLD) has become a concern worldwide. Although obesity plays the most pivotal role in NAFLD, approximately 10-20% of individuals with NAFLD who are not overweight or obese (BMI < 25 kg/m2, or BMI < 23 kg/m2 in Asians) have "lean NAFLD." Lean individuals with NAFLD have a lower prevalence of diabetes, hypertension, hypertriglyceridemia, central obesity, and metabolic syndrome than nonlean individuals with NAFLD, but higher fibrosis scores and rates of cardiovascular morbidity and all-cause mortality in advanced stages. The pathophysiological mechanisms of lean NAFLD remain poorly understood. Studies have shown that lean NAFLD is more correlated with factors such as environmental, genetic susceptibility, and epigenetic regulation. This review will examine the way in which the research progress and characteristic of lean NAFLD, and explore the function of epigenetic modification to provide the basis for the clinical treatment and diagnosis of lean NAFLD.

Improving the accuracy and consistency of clinical target volume delineation for rectal cancer by an education program

BACKGROUND

Accurate target volume delineation is the premise for the implementation of precise radiotherapy. Inadequate target volume delineation may diminish tumor control or increase toxicity. Although several clinical target volume (CTV) delineation guidelines for rectal cancer have been published in recent years, significant interobserver variation (IOV) in CTV delineation still exists among radiation oncologists. However, proper education may serve as a bridge that connects complex guidelines with clinical practice.

AIM

To examine whether an education program could improve the accuracy and consistency of preoperative radiotherapy CTV delineation for rectal cancer.

METHODS

The study consisted of a baseline target volume delineation, a 150-min education intervention, and a follow-up evaluation. A 42-year-old man diagnosed with stage IIIC (T3N2bM0) rectal adenocarcinoma was selected for target volume delineation. CTVs obtained before and after the program were compared. Dice similarity coefficient (DSC), inclusiveness index (IncI), conformal index (CI), and relative volume difference [ΔV (%)] were analyzed to quantitatively evaluate the disparities between the participants’ delineation and the standard CTV. Maximum volume ratio (MVR) and coefficient of variation (CV) were calculated to assess the IOV. Qualitative analysis included four common controversies in CTV delineation concerning the upper boundary of the target volume, external iliac area, groin area, and ischiorectal fossa.

RESULTS

Of the 18 radiation oncologists from 10 provinces in China, 13 completed two sets of CTVs. In quantitative analysis, the average CTV volume decreased from 809.82 cm³ to 705.21 cm³ (P = 0.001) after the education program. Regarding the indices for geometric comparison, the mean DSC, IncI, and CI increased significantly, while ΔV (%) decreased remarkably, indicating improved agreement between participants’ delineation and the standard CTV. Moreover, an 11.80% reduction in MVR and 18.19% reduction in CV were noted, demonstrating a smaller IOV in delineation after the education program. Regarding qualitative analysis, the greatest variations in baseline were observed at the external iliac area and ischiorectal fossa; 61.54% (8/13) and 53.85% (7/13) of the participants unnecessarily delineated the external iliac area and the ischiorectal fossa, respectively. However, the education program reduced these variations.

CONCLUSION

Wide variations in CTV delineation for rectal cancer are present among radiation oncologists in mainland China. A well-structured education program could improve delineation accuracy and reduce IOVs.

Delineating and sparing functional nephrons for radiotherapy in the case of lymphoma with polycystic kidney disease

PURPOSE

It is imperative to spare functioning kidneys from high radiation doses when they are near enough to radiotherapy (RT) target volumes in patients with polycystic kidney disease (PKD). To achieve this intent, we designed the unique approach that we report here.

METHODS AND MATERIALS

The patient who has PKD, presented with B-cell lymphoma involving paraaortic lymph nodes. After completing chemotherapy, RT was planned to the residual nodal disease. The diagnostic positron emission tomography computed tomography (PETCT) scan was fused with the RT planning CT scan. 18F-2-deoxy-2(F)-fluro-d-glucose (FDG) avid active kidneys were contoured separately, and the treatment plan was optimized to avoid these volumes.

RESULTS

The functional volume was 17.52% of the right kidney whereas it was 7.44% of the left. The mean doses were 4.61 Gy and 4.2 Gy, respectively. The baseline estimated glomerular filtration rate (eGFR) was >60 mL/min; at 18 months follow-up, it was 62 mL/min.

CONCLUSIONS

Delineation of functional nephrons was feasible while utilizing the staging FDG-PETCT scan for radiotherapy contouring in our patient, which aided to achieve the optimal dose-volume constraints. Further studies are warranted to analyze and quantify the benefit of this easily accessible method in the future.

Land cover based simulation of urban stormwater runoff and pollutant loading

Urban stormwater models such as PCSWMM are important tools for evaluating urban stormwater quantity and quality. However, due to the lack of consideration of land covers, traditional catchment delineation methods have defects in model precision, parameter transferability and assessment of contribution from individual land cover types. This paper used PCSWMM model as a foundation, built a new land-cover based (LCB) model and made a systematic comparison with the traditional watershed delineation tool (WDT) model to study the impacts of land cover on the simulation of stormwater runoff and pollutant loading. The models were applied to two urban catchments in Calgary, Canada. The results revealed that the LCB model performed better than the WDT model in hydrological simulation, and land cover consideration can considerably improve model accuracy. The two models showed comparable performances in simulation of total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) loading. The LCB model parameters could be regionalized based on land cover types. The hydrologic-hydraulic parameters can be satisfactorily transferred from neighboring gauged catchments to similar ungauged catchments. The transferring of water quality parameters did not perform as satisfactory. The LCB model could quantitively evaluate the contribution to runoff and pollutant loads of different land covers. Roads and roofs were found to be the major contributors to urban runoff and pollutants in the two urban catchments. Green space became important only during large storms events and its contribution could be ignored during dryer years.

Radiotherapy for laryngeal cancers

We present the update of the recommendations of the French society of oncological radiotherapy on radiotherapy of laryngeal cancers. Intensity modulated radiotherapy is the standard of care radiotherapy for the management of laryngeal cancers. Early stage T1 or T2 tumours can be treated either by radiotherapy or conservative surgery. For tumours requiring total laryngectomy (T2 or T3), an organ preservation strategy by either induction chemotherapy followed by radiotherapy or chemoradiotherapy with cisplatin is recommended. For T4 tumours, a total laryngectomy followed by radiotherapy is recommended when feasible. Dose regimens for definitive and postoperative radiotherapy are detailed in this article, as well as the selection and delineation of tumour and lymph node target volumes.

Radiotherapy for hypopharynx cancers

We present the update of the recommendations of the French society of oncological radiotherapy on radiotherapy for hypopharynx. Intensity-modulated radiotherapy is the gold standard treatment for hypopharynx cancers. Early T1 and T2 tumors could be treated by exclusive radiotherapy or surgery followed by postoperative radiotherapy in case of high recurrence risk. For locally advanced tumours requiring total pharyngolaryngectomy (T2 or T3) or with significant lymph nodes involvement, induction chemotherapy followed by exclusive radiotherapy or concurrent chemoradiotherapy were possible. For T4 tumour, surgery must be proposed. The treatment of lymph nodes is based on initial primary tumour treatment. In non-surgical procedure, for 35 fractions, curative dose is 70Gy (2Gy per fraction) and prophylactic dose are 50 to 56Gy (2Gy per fraction in case of sequential radiotherapy or 1.6Gy in case of integrated simultaneous boost) radiotherapy; for 33 fractions, curative dose is 69.96Gy (2.12Gy per fraction) and prophylactic dose is 52.8Gy (1.6Gy per fraction in integrated simultaneous boost radiotherapy or 54Gy in 1.64Gy per fraction); for 30 fractions, curative dose is 66Gy (2.2Gy per fraction) and prophylactic dose is 54Gy (1.8Gy per fraction in integrated simultaneous boost radiotherapy). Doses over 2Gy per fraction could be done when chemotherapy is not used regarding potential larynx toxicity. Postoperatively, radiotherapy is used in locally advanced cancer with dose levels based on pathologic criteria, 60 to 66Gy for R1 resection and 54 to 60Gy for complete resection in bed tumour; 50 to 66Gy in lymph nodes areas regarding extracapsular spread. Volume delineation were based on guidelines cited in this article.

ESTRO ACROP guidelines for the delineation of lymph nodal areas in upper gastrointestinal malignancies

The European SocieTy for Radiation and Oncology -Advisory Committee on Radiation Oncology Practice (ESTRO-ACROP) endorsed a project to provide guidelines (GL) for the identification and delineation of clinically negative lymph-nodal stations (LNs) involved in upper gastrointestinal clinical scenarios. The presented GL is focused on preoperative (or definitive) setting. The project aim is to improve the consistency of clinical target volume (CTV) delineation by providing: a description of the anatomical boundaries of the LNs; a radiological computed tomography-based atlas depicting the LNs areas; a free, web-based, interactive example case for independent training of radiation oncologists on LNs delineation according to the presented GL, by both qualitative and quantitative analysis (through the FALCON EduCase platform). This project was carried out with the intention to facilitate and improve uniformity of future upper gastrointestinal guidelines on nodal CTV delineation. We report methodology and results from the collaboration of a working group panel selected by the ESTRO-ACROP.

Tricks and tips for target volume definition and delineation in breast cancer: Lessons learned from ESTRO breast courses

Delineation of target and 'organ at risk' volumes is a critical part of modern radiation therapy planning, the next essential step after deciding the indication, patient discussion and image acquisition. Adoption of volume-based treatment planning for non-metastatic breast cancer has increased greatly along with the use of improved planning techniques, essential for modern therapy. However, identifying the volumes on a planning CT is no easy task. The current paper is written by ESTRO's breast course faculty, providing tricks and tips for target volume definition and delineation for optimal postoperative breast cancer irradiation.

Delineation of organs at risk

The delineation of organs at risk is the basis of radiotherapy oncologists' work. Indeed, the knowledge of this delineation enables to better identify the target volumes and to optimize dose distribution, involving the prognosis of the patients but also their future. The learning of this delineation must continue throughout the clinician's career. Some contour changes have appeared with better imaging, some volumes are now required due to development of knowledge of side effects. In addition, the increasing survival time of patients requires to be more systematic and precise in the delineations, both to avoid complications until now exceptional but also because re-irradiations are becoming more and more frequent. We present the update of the recommendations of the French Society for Radiation Oncology (SFRO) on new findings or adaptations to volumes at risk.

A new method to visualize and to spare the ureters during SBRT for oligo metastatic patients

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Ureteral injury following abdominal irradiation may have serious consequences.

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Urography CT scan is a simple procedure to spare ureters during SBRT.

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Using a urography CT scan can significantly reduce the dose to the ureters.

This article describes a ureter-sparing procedure used to treat lymph node metastases with SBRT. We delivered 35 Gy in 5 fractions of 7 Gy to patients with lesions located less than 7 mm from the ureters using a urography CT scan for planification. Two dosimetry plans were created, one using a CT scan urography-based contour and the other using the native phase. PTV coverage were not statistically different but this technique was able to significantly reduce median delivered Dmax to the ureters. These preliminary results demonstrate the feasibility of locating the ureters in a planning CT scan to protect them.

Automated assessment of functional lung imaging with 68Ga-ventilation/perfusion PET/CT using iterative histogram analysis

PURPOSE

Functional lung mapping from Ga⁶⁸-ventilation/perfusion (V/Q) PET/CT, which has been shown to correlate with pulmonary function tests (PFTs), may be beneficial in a number of clinical applications where sparing regions of high lung function is of interest. Regions of clumping in the proximal airways in patients with airways disease can result in areas of focal intense activity and artefact in ventilation imaging. These artefacts may even shine through to subsequent perfusion images and create a challenge for quantitative analysis of PET imaging. We aimed to develop an automated algorithm that interprets the uptake histogram of PET images to calculate a peak uptake value more representative of the global lung volume.

METHODS

Sixty-six patients recruited from a prospective clinical trial underwent both V/Q PET/CT imaging and PFT analysis before treatment. PET images were normalised using an iterative histogram analysis technique to account for tracer hotspots prior to the threshold-based delineation of varying values. Pearson's correlation between fractional lung function and PFT score was calculated for ventilation, perfusion, and matched imaging volumes at varying threshold values.

RESULTS

For all functional imaging thresholds, only FEV1/FVC PFT yielded reasonable correlations to image-based functional volume. For ventilation, a range of 10-30% of adapted peak uptake value provided a reasonable threshold to define a volume that correlated with FEV1/FVC (r = 0.54-0.61). For perfusion imaging, a similar correlation was observed (r = 0.51-0.56) in the range of 20-60% adapted peak threshold. Matched volumes were closely linked to ventilation with a threshold range of 15-35% yielding a similar correlation (r = 0.55-0.58).

CONCLUSIONS

Histogram normalisation may be implemented to determine the presence of tracer clumping hotspots in Ga-68 V/Q PET imaging allowing for automated delineation of functional lung and standardisation of functional volume reporting.

Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients

PURPOSE

Identification and delineation of the gross tumour and malignant nodal volume (GTV) in medical images are vital in radiotherapy. We assessed the applicability of convolutional neural networks (CNNs) for fully automatic delineation of the GTV from FDG-PET/CT images of patients with head and neck cancer (HNC). CNN models were compared to manual GTV delineations made by experienced specialists. New structure-based performance metrics were introduced to enable in-depth assessment of auto-delineation of multiple malignant structures in individual patients.

METHODS

U-Net CNN models were trained and evaluated on images and manual GTV delineations from 197 HNC patients. The dataset was split into training, validation and test cohorts (n= 142, n = 15 and n = 40, respectively). The Dice score, surface distance metrics and the new structure-based metrics were used for model evaluation. Additionally, auto-delineations were manually assessed by an oncologist for 15 randomly selected patients in the test cohort.

RESULTS

The mean Dice scores of the auto-delineations were 55%, 69% and 71% for the CT-based, PET-based and PET/CT-based CNN models, respectively. The PET signal was essential for delineating all structures. Models based on PET/CT images identified 86% of the true GTV structures, whereas models built solely on CT images identified only 55% of the true structures. The oncologist reported very high-quality auto-delineations for 14 out of the 15 randomly selected patients.

CONCLUSIONS

CNNs provided high-quality auto-delineations for HNC using multimodality PET/CT. The introduced structure-wise evaluation metrics provided valuable information on CNN model strengths and weaknesses for multi-structure auto-delineation.

[Proposal for the delineation of postoperative primary clinical target volumes in ethmoid cancers]

It is proposed to delineate the anatomo-clinical target volumes of primary tumor (CTV-P) in ethmoid cancers treated with post-operative radiotherapy. This concept is based on the use of radioanatomy and the natural history of cancer. It is supported by the repositioning of the planning scanner with preoperative imaging for the replacement of the initial GTV and the creation of margins around it extended to the microscopic risk zones according to the anatomical concept. This article does not discuss the indications of external radiotherapy but specifies the volumes to be delineated if radiotherapy is considered.

Recommendation regarding the cranial upper border of level IIb in delineating clinical target volumes (CTV) for nasopharyngeal carcinoma

PURPOSE

To recommend a cranial border for level IIb in delineating clinical target volumes (CTV) for nasopharyngeal carcinoma (NPC) patients receiving intensity-modulated radiotherapy and to help reach a consensus on contouring level IIb in CTV.

METHODS

From 2012 to 2016, 331 nonmetastatic NPC patients treated with IMRT were retrospectively enrolled. Based on the AJCC 8th staging system of NPC, there were 15 stage I, 76 stage II, 103 stage III, and 137 stage IV patients. The distribution of cervical lymph nodes in NPC was assessed based on imaging. Comparisons of the safety and parotid dose parameters between patients with and without a reduction in the size of level IIb were conducted using SPSS 25.0 and R 2.14.2 software.

RESULTS

Metastasis rates in the most commonly involved lymph nodes, the lateral retropharyngeal and IIb nodes, were 82.8% and 64.0%, respectively. Among patients with level IIb involvement, the upper borders of the metastatic nodes were beyond the caudal edge of C1 in 13.7% of cases. The parotid gland D50 and V26 values were significantly reduced after modifying the upper bound of level IIb used to delineate the CTV (P = 0.000).

CONCLUSION

In principle, the upper bound of level IIb should reach the lateral skull base during delineation of the cervical CTV for NPC. To protect the parotid glands, however, individualized reduction of the upper bound of level IIb is recommended for patients who meet certain criteria.

DeepTarget: Gross tumor and clinical target volume segmentation in esophageal cancer radiotherapy

Gross tumor volume (GTV) and clinical target volume (CTV) delineation are two critical steps in the cancer radiotherapy planning. GTV defines the primary treatment area of the gross tumor, while CTV outlines the sub-clinical malignant disease. Automatic GTV and CTV segmentation are both challenging for distinct reasons: GTV segmentation relies on the radiotherapy computed tomography (RTCT) image appearance, which suffers from poor contrast with the surrounding tissues, while CTV delineation relies on a mixture of predefined and judgement-based margins. High intra- and inter-user variability makes this a particularly difficult task. We develop tailored methods solving each task in the esophageal cancer radiotherapy, together leading to a comprehensive solution for the target contouring task. Specifically, we integrate the RTCT and positron emission tomography (PET) modalities together into a two-stream chained deep fusion framework taking advantage of both modalities to facilitate more accurate GTV segmentation. For CTV segmentation, since it is highly context-dependent-it must encompass the GTV and involved lymph nodes while also avoiding excessive exposure to the organs at risk-we formulate it as a deep contextual appearance-based problem using encoded spatial distances of these anatomical structures. This better emulates the margin- and appearance-based CTV delineation performed by oncologists. Adding to our contributions, for the GTV segmentation we propose a simple yet effective progressive semantically-nested network (PSNN) backbone that outperforms more complicated models. Our work is the first to provide a comprehensive solution for the esophageal GTV and CTV segmentation in radiotherapy planning. Extensive 4-fold cross-validation on 148 esophageal cancer patients, the largest analysis to date, was carried out for both tasks. The results demonstrate that our GTV and CTV segmentation approaches significantly improve the performance over previous state-of-the-art works, e.g., by 8.7% increases in Dice score (DSC) and 32.9mm reduction in Hausdorff distance (HD) for GTV segmentation, and by 3.4% increases in DSC and 29.4mm reduction in HD for CTV segmentation.

Deep learning for elective neck delineation: More consistent and time efficient

BACKGROUND/PURPOSE

Delineation of the lymph node levels of the neck for irradiation of the elective clinical target volume in head and neck cancer (HNC) patients is time consuming and prone to interobserver variability (IOV), although international consensus guidelines exist. The aim of this study was to develop and validate a 3D convolutional neural network (CNN) for semi-automated delineation of all nodal neck levels, focussing on delineation accuracy, efficiency and consistency compared to manual delineation.

MATERIAL/METHODS

The CNN was trained on a clinical dataset of 69 HNC patients. For validation, 17 lymph node levels were manually delineated in 16 new patients by two observers, independently, using international consensus guidelines. Automated delineations were generated by applying the CNN and were subsequently corrected by both observers separately as needed for clinical acceptance. Both delineations were performed two weeks apart and blinded to each other. IOV was quantified using Dice similarity coefficient (DSC), mean surface distance (MSD) and Hausdorff distance (HD). To assess automated delineation accuracy, agreement between automated and corrected delineations were evaluated using the same measures. To assess efficiency, the time taken for manual and corrected delineations were compared. In a second step, only the clinically relevant neck levels were selected and delineated, once again manually and by applying and correcting the network.

RESULTS

When all lymph node levels were delineated, time taken for correcting automated delineations compared to manual delineations was significantly shorter for both observers (mean: 35 vs 52 min, p < 10^-5). Based on DSC, automated delineation agreed best with corrected delineation for lymph node levels Ib, II-IVa, VIa, VIb, VIIa, VIIb (DSC >85%). Manual corrections necessary for clinical acceptance were 1.4 mm MSD on average and were especially low (<1mm) for levels II-IVa, VIa, VIIa and VIIb. IOV was significantly smaller with automated compared to manual delineations (MSD: 1.4 mm vs 2.5 mm, p < 10^-11). When delineating only the clinically relevant neck levels, the correction time was also significantly shorter (mean: 8 vs 15 min, p < 10^-5). Based on DSC, automated delineation agreed very well with corrected delineation (DSC > 87%). Manual corrections necessary for clinical acceptance were 1.3 mm MSD on average. IOV was significantly smaller with automated compared to manual delineations (MSD: 0.8 mm vs 2.3 mm, p < 10^-3).

CONCLUSION

The CNN developed for automated delineation of the elective lymph node levels in the neck in HNC was shown to be more efficient and consistent compared to manual delineation, which justifies its implementation in clinical practice.

Evaluation of a software for automatic delineation of the mammary gland and organs at risk in patients treated for breast cancer in lateral position

PURPOSE OF THE STUDY

The purpose of this study was to assess the potential for improvement of routine breast and organs at risk contouring in patients treated in the lateral decubitus position using Workflow Box™ (Mirada Medical™, UK) automatic contouring software.

MATERIALS AND METHODS

Automatic contouring of the breast by this software is currently based on an atlas created from isodoses representing 95% of the prescribed dose in a population of patients previously treated at institut Curie. Forty cases of breast cancer (20 right breasts and 20 left breasts) were contoured by three radiation oncologists specialized in breast cancer, allowing the creation of a new atlas in the automatic contouring software. This study assessed the quality of contouring in 20 patients (ten right breasts and ten left breasts) by comparing manual contouring performed by the expert radiation oncologists (reference) with those generated by the old and new atlases developed at Institut Curie. The accuracy of contouring was assessed by overlap volume and the associated standard deviations.

RESULTS

Breast contouring based on the new atlas and by radiation oncologists presented a mean overlap of 0.80±0.09 for the right breast and 0.81±0.06 for the left breast. By comparing volumes of interest contoured by radiation oncologists and those obtained from the old atlas, mean overlap volumes were 0.75±0.08 and 0.74±0.13 for the right and left breasts, respectively. Twenty cases (ten right breasts and ten left breasts) used to create the new atlas were also reprocessed by this same atlas in order to assess the quality of automatic contouring of the breast when the case was already known to the software. The mean overlap volume in this case was 0.84±0.08 for the right breast and 0.83±0.06 for the left breast. Finally, after automatic contouring of organs at risk by means of the new atlas, the mean overlap volume was 0.87±0.04 for the heart and 0.93 for each lung (±0.05 for the right lung and±0.04 for the left lung).

CONCLUSION

Workflow Box™ automatic contouring software, based on our new atlas provides reliable and clinically relevant organs at risk and breast contouring. The contours proposed by the software from the new atlas were better than those obtained with the previous atlas based on 95% isodoses obtained from old treatment plans. This software has therefore become more efficient, justifying its use in routine clinical practice for breast cancer contouring in patients treated in the lateral decubitus position. Investigations are currently underway to develop a fully automated process to ensure reliable, robust and operator-independent contouring and breast cancer treatment dosimetry in the lateral decubitus position. Promising preliminary results have already been obtained.

Optimal 68Ga-PSMA and 18F-PSMA PET window levelling for gross tumour volume delineation in primary prostate cancer

PURPOSE

This study proposes optimal tracer-specific threshold-based window levels for PSMA PET-based intraprostatic gross tumour volume (GTV) contouring to reduce interobserver delineation variability.

METHODS

Nine ⁶⁸Ga-PSMA-11 and nine ¹⁸F-PSMA-1007 PET scans including GTV delineations of four expert teams (GTV_manual) and a majority-voted GTV (GTV_majority) were assessed with respect to a registered histopathological GTV (GTV_histo) as the gold standard reference. The standard uptake values (SUVs) per voxel were converted to a percentage (SUV%) relative to the SUV_max. The statistically optimised SUV% threshold (SOST) was defined as those that maximises accuracy for threshold-based contouring. A leave-one-out cross-validation receiver operating characteristic (ROC) curve analysis was performed to determine the SOST for each tracer. The SOST analysis was performed twice, first using the GTV_histo contour as training structure (GTV_SOST-H) and second using the GTV_majority contour as training structure (GTV_SOST-MA) to correct for any limited misregistration. The accuracy of both GTV_SOST-H and GTV_SOST-MA was calculated relative to GTV_histo in the 'leave-one-out' patient of each fold and compared with the accuracy of GTV_manual.

RESULTS

ROC curve analysis for ⁶⁸Ga-PSMA-11 PET revealed a median threshold of 25 SUV% (range, 22-27 SUV%) and 41 SUV% (40-43 SUV%) for GTV_SOST-H and GTV_SOST-MA, respectively. For ¹⁸F-PSMA-1007 PET, a median threshold of 42 SUV% (39-45 SUV%) for GTV_SOST-H and 44 SUV% (42-45 SUV%) for GTV_SOST-MA was found. A significant pairwise difference was observed when comparing the accuracy of the GTV_SOST-H contours with the median accuracy of the GTV_manual contours (median, - 2.5%; IQR, - 26.5-0.2%; p = 0.020), whereas no significant pairwise difference was found for the GTV_SOST-MA contours (median, - 0.3%; IQR, - 4.4-0.6%; p = 0.199).

CONCLUSIONS

Threshold-based contouring using GTV_majority-trained SOSTs achieves an accuracy comparable with manual contours in delineating GTV_histo. The median SOSTs of 41 SUV% for ⁶⁸Ga-PSMA-11 PET and 44 SUV% for ¹⁸F-PSMA-1007 PET form a base for tracer-specific window levelling.

TRIAL REGISTRATION

Clinicaltrials.gov ; NCT03327675; 31-10-2017.

Automatic evaluation of contours in radiotherapy planning utilising conformity indices and machine learning

BACKGROUND AND PURPOSE

Peer-review of Target Volume (TV) and Organ at Risk (OAR) contours in radiotherapy planning are typically conducted visually; this can be time consuming and subject to interobserver variation. This study investigated automatic evaluation of contouring using conformity indices and supervised machine learning.

METHODS

A total of 393 contours from 253 Stereotactic Ablative Body Radiotherapy (SABR) benchmark cases (adrenal gland, liver, pelvic lymph node and spine), delineated by 132 clinicians from 25 centres, were visually evaluated for conformity against gold standard contours. Contours were scored as "pass" or "fail" on visual peer review and six Conformity Indices (CIs) were applied. CI values were mapped to pass/fail scores for each contour and used to train supervised machine learning models. A 5-fold cross validation method was employed to determine the predictive accuracies of each model.

RESULTS

The stomach structure produced models with the highest predictive accuracy overall (96% using Support Vector Machine and Ensemble models), whilst the liver GTV produced models with the lowest predictive accuracy (76% using Logistic Regression). Predictive accuracies across all models ranged from 68-96% (68-87% for TV and 71-96% for OARs).

CONCLUSIONS

Although a final visual review by an experienced clinician is still required, the automatic contour evaluation method could reduce the time for benchmark case reviews by identifying gross contouring errors. This method could be successfully implemented to support departmental training and the continuous assessment of outlining for clinical staff in the peer-review process, to reduce interobserver variability in contouring and improve interpretation of radiological anatomy.

Deep Learning Model for the Automated Detection and Histopathological Prediction of Meningioma

The volumetric assessment and accurate grading of meningiomas before surgery are highly relevant for therapy planning and prognosis prediction. This study was to design a deep learning algorithm and evaluate the performance in detecting meningioma lesions and grade classification. In total, 5088 patients with histopathologically confirmed meningioma were retrospectively included. The pyramid scene parsing network (PSPNet) was trained to automatically detect and delineate the meningiomas. The results were compared to manual segmentations by evaluating the mean intersection over union (mIoU). The performance of grade classification was evaluated by accuracy. For the automated detection and segmentation of meningiomas, the mean pixel accuracy, tumor accuracy, background accuracy and mIoU were 99.68%, 81.36%, 99.88% and 81.36% for all patients; 99.52%, 84.86%, 99.93% and 84.86% for grade I meningiomas; 99.57%, 80.11%, 99.92% and 80.12% for grade II meningiomas; and 99.75%, 78.40%, 99.99% and 78.40% for grade III meningiomas, respectively. For grade classification, the accuracy values of the training and test datasets were 99.93% and 81.52% for all patients; 99.98% and 98.51% for grade I meningiomas; 99.91% and 66.67% for grade II meningiomas; and 99.88% and 73.91% for grade III meningiomas, respectively. The automated detection, segmentation and grade classification of meningiomas based on deep learning were accurate and reliable and may improve the monitoring and treatment of this frequently occurring tumor entity. Furthermore, the method could function as a useful tool for preassessment and preselection for radiologists, offering auxiliary information for clinical decision making in presurgical evaluation.

Restricted bowel loop contouring: Improving efficiency in radiotherapy contouring for abdomino-pelvic Stereotactic Ablative Radiotherapy (SABR)

We present a time-saving alternative to individual bowel loop delineation for abdomino-pelvic Stereotactic Ablative Radiotherapy. Here, individual bowel loop contouring is only performed within a 3 cm circumferential and 2 cm superio-inferior expansion of the PTV. A bowel bag structure represents distal bowel. No relevant doses are 'missed' with this time-saving strategy.

[Impact of reconstructive or minimal invasive surgery on the assessment of current definitions of postoperative clinical target volume for head and neck cancers]

Advances in the reconstructive surgery and minimally invasive endonasal endoscopic surgery of head and neck is poorly evaluated in terms of their impact on radiotherapy planning and outcomes. These surgical advances have resulted in reduced morbidity with equivalent or better tumor control. In the absence of a recommendation on how to delineate target volumes in patients with flaps or to consider margins after endoscopic endonasal surgery, radiotherapy practices are inevitably heterogeneous. Efforts are needed to increase the therapeutic index of postoperative radiotherapy in these situations. We analysed the rare existing literature and outlined a preliminary basis for a recommendation. Strengthening of multidisciplinarity to accurately define target volumes in these complex and relatively new situations, and "delineation concertation meetings" between radiologists, surgeons and radiation oncologists could probably contribute to improved outcomes.

Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy

BACKGROUND

Structure delineation is a necessary, yet time-consuming manual procedure in radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and automatise this procedure, obtaining promising results. With the advent of magnetic resonance imaging (MRI)-guided radiotherapy, MR-based segmentation is becoming increasingly relevant. However, the majority of the studies investigated automatic contouring based on computed tomography (CT).

PURPOSE

In this study, we investigate the feasibility of clinical use of deep learning-based automatic OARs delineation on MRI.

MATERIALS AND METHODS

We included 150 patients diagnosed with prostate cancer who underwent MR-only radiotherapy. A three-dimensional (3D) T1-weighted dual spoiled gradient-recalled echo sequence was acquired with 3T MRI for the generation of the synthetic-CT. The first 48 patients were included in a feasibility study training two 3D convolutional networks called DeepMedic and dense V-net (dV-net) to segment bladder, rectum and femurs. A research version of an atlas-based software was considered for comparison. Dice similarity coefficient, 95% Hausdorff distances (HD95), and mean distances were calculated against clinical delineations. For eight patients, an expert RTT scored the quality of the contouring for all the three methods. A choice among the three approaches was made, and the chosen approach was retrained on 97 patients and implemented for automatic use in the clinical workflow. For the successive 53 patients, Dice, HD95 and mean distances were calculated against the clinically used delineations.

RESULTS

DeepMedic, dV-net and the atlas-based software generated contours in 60 s, 4 s and 10-15 min, respectively. Performances were higher for both the networks compared to the atlas-based software. The qualitative analysis demonstrated that delineation from DeepMedic required fewer adaptations, followed by dV-net and the atlas-based software. DeepMedic was clinically implemented. After retraining DeepMedic and testing on the successive patients, the performances slightly improved.

CONCLUSION

High conformality for OARs delineation was achieved with two in-house trained networks, obtaining a significant speed-up of the delineation procedure. Comparison of different approaches has been performed leading to the succesful adoption of one of the neural networks, DeepMedic, in the clinical workflow. DeepMedic maintained in a clinical setting the accuracy obtained in the feasibility study.

Comparison of tumor delineation using dual energy computed tomography versus magnetic resonance imaging in head and neck cancer re-irradiation cases

•

GTVs on the 60 kV and 140 kV from DECT, and the T1c and T2 from MRI were compared.

•

Delineation was the most consistent using T1c (no interobserver difference in DSC).

•

T1c MRI provided higher interobserver agreement for skull base tumors.

•

60 kV DECT provided higher interobserver agreement for non-skull base tumors.

In treatment planning, multiple imaging modalities can be employed to improve the accuracy of tumor delineation but this can be costly. This study aimed to compare the interobserver consistency of using dual energy computed tomography (DECT) versus magnetic resonance imaging (MRI) for delineating tumors in the head and neck cancer (HNC) re-irradiation scenario. Twenty-three patients with recurrent HNC and had planning DECT and MRI were identified. Contoured tumor volumes by seven radiation oncologists were compared. Overall, T1c MRI performed the best with median DSC of 0.58 (0–0.91) for T1c. T1c MRI provided higher interobserver agreement for skull base sites and 60 kV DECT provided higher interobserver agreement for non-skull base sites.

Validation of automated magnetic resonance image segmentation for radiation therapy planning in prostate cancer

Background and purpose

Magnetic resonance imaging (MRI) is increasingly used in radiation therapy planning of prostate cancer (PC) to reduce target volume delineation uncertainty. This study aimed to assess and validate the performance of a fully automated segmentation tool (AST) in MRI based radiation therapy planning of PC.

Material and methods

Pelvic structures of 65 PC patients delineated in an MRI-only workflow according to established guidelines were included in the analysis. Automatic vs manual segmentation by an experienced oncologist was compared with geometrical parameters, such as the dice similarity coefficient (DSC). Fifteen patients had a second MRI within 15 days to assess repeatability of the AST for prostate and seminal vesicles. Furthermore, we investigated whether hormonal therapy or body mass index (BMI) affected the AST results.

Results

The AST showed high agreement with manual segmentation expressed as DSC (mean, SD) for delineating prostate (0.84, 0.04), bladder (0.92, 0.04) and rectum (0.86, 0.04). For seminal vesicles (0.56, 0.17) and penile bulb (0.69, 0.12) the respective agreement was moderate. Performance of AST was not influenced by neoadjuvant hormonal therapy, although those on treatment had significantly smaller prostates than the hormone-naïve patients (p < 0.0001). In repeat assessment, consistency of prostate delineation resulted in mean DSC of 0.89, (SD 0.03) between the paired MRI scans for AST, while mean DSC of manual delineation was 0.82, (SD 0.05).

Conclusion

Fully automated MRI segmentation tool showed good agreement and repeatability compared with manual segmentation and was found clinically robust in patients with PC. However, manual review and adjustment of some structures in individual cases remain important in clinical use.

Radiotherapy for Hepatocellular Carcinoma in Russia: a Survey-Based Analysis of Current Practice and the Impact of an Educational Workshop on Clinical Expertise

Radiation therapy (RT) is an effective treatment modality for hepatocellular carcinoma (HCC), but globally, it is underutilized. In Russia, practice patterns with regard to liver-directed radiation are unknown. Under the auspices of Russian Society of Clinical Oncology (RUSSCO), our team conducted an IRB-approved contouring workshop for Russian radiation oncologists. Pre- and post-workshop surveys were analyzed to determine baseline clinical experience and patterns of care for liver-directed RT among Russian providers. The effect of the contouring workshop on participants' knowledge was tested using mixed effects model. Forty pre-workshop and 24 post-workshop questionnaires were analyzable with a 100% response rate. Sixty percent of respondents had never evaluated a patient with HCC and only 8% (3 out of 40) reported treating an HCC patient with liver-directed RT. Nonetheless, 73% of respondents were comfortable offering liver-directed RT prior to the workshop. After the workshop, 85% of respondents felt comfortable treating a patient with HCC with liver-directed RT and 50% were comfortable recommending stereotactic body radiation therapy (SBRT). Measures of knowledge pertaining to evaluation of HCC patients and selection for appropriate liver-directed therapies were dramatically improved after the workshop. Liver-directed RT is not commonly used in Russia in the management of patients with HCC, and few centers are equipped for motion management. Our contouring workshop resulted in dramatically improved understanding of the evaluation and management of HCC patients. We recommend starting with a more protracted fractionated RT and building experience through attendance of additional educational activities, participation in multidisciplinary liver tumor boards, and prospective analysis of treatment toxicity and outcomes.

Analysis of Clinical Target Volume Delineation in Local-regional Failure of Nasopharyngeal Carcinoma after Intensity-modulated Radiotherapy

OBJECTIVE: To analyze the pattern of local failure in patients with nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT) and find a more reasonable delineation of the clinical target volume (CTV).

METHODS AND MATERIALS: A total of 212 patients with non-metastatic NPC who underwent IMRT were analyzed. Radiation therapy was run at a total dose of 66-74 Gy (2.0-2.2 Gy fractions). The follow-up of local recurrence and the recurrence-related features were analyzed for the original treatment situation. The failures were delimited as “in-field failure” if V_recur within the 95% isodose curve (V95%) was ≥95%; “marginal failure” if V95% was less than 95% and not less than 20%; or “out-field failure” if V95% was< 20%. Kaplan-Meier method was used to calculate the survival rates.

RESULTS: The median follow-up was 43.4 months. The 5-year local relapse-free survival and overall survival rates were 85.6 and 77.8%, respectively. A total of 18 patients have relapsed. The in-field failure, marginal failure, and out-field failure accounted for 83.3%, 11.1%, and 5.6%, respectively. The site of recurrence was basically in the high dose area.

CONCLUSION: These findings suggested that IMRT provide a good local control for patients with NPC, and the in-field failure is the main mode. A wide range of CTV cannot prevent the local recurrence, narrowing the CTV to protect the adjacent organs should be taken into consideration.

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineation given only 2D annotations in Maximum Intensity Projections (MIP) of the training volumes. This significantly reduces the annotation time: We conducted a user study that suggests that annotating 2D projections is on average twice as fast as annotating the original 3D volumes. Our technical contribution is a loss function that evaluates a 3D prediction against annotations of 2D projections. It is inspired by space carving, a classical approach to reconstructing complex 3D shapes from arbitrarily-positioned cameras. It can be used to train any deep network with volumetric output, without the need to change the network's architecture. Substituting the loss is all it takes to enable 2D annotations in an existing training setup. In extensive experiments on 3D light microscopy images of neurons and retinal blood vessels, and on Magnetic Resonance Angiography (MRA) brain scans, we show that, when trained on projection annotations, deep delineation networks perform as well as when they are trained using costlier 3D annotations.

[Proposal for the selection and delineation of clinical target volumes for the radiotherapy of submandibular gland tumours]

This article provides a proposal for the selection and delineation of clinical target volumes for the treatment with radiation of submandibular glands tumours. This article does not deal with external radiotherapy indications but specifies the volumes to be treated if radiotherapy is chosen. High-risk and low-risk peritumoral clinical target volumes are described based on the probability of local tumoral spread. High-risk and low-risk clinical target volumes are illustrated on CT-scan slices. A proposal for the selection of nodal clinical target volumeis also proposed.

Validation of different PSMA-PET/CT-based contouring techniques for intraprostatic tumor definition using histopathology as standard of reference

PURPOSE

Accurate definition of the intraprostatic gross tumor volume (GTV) is crucial for diagnostic and therapeutic approaches in patients with primary prostate cancer (PCa). The optimal methodology for contouring of GTV using Prostate specific membrane antigen positron emission tomography (PSMA-PET) information has not yet been defined.

METHODS AND MATERIALS

PCa patients who underwent a [68Ga]PSMA-11-PET/CT followed by radical prostatectomy were prospectively enrolled (n = 20). Six observer teams with different levels of experience and using different PET image scaling techniques performed manual contouring of GTV. Additionally, semi-automatic segmentation of GTVs was performed using SUVmax thresholds of 20-50%. Coregistered histopathological gross tumor volume (GTV-Histo) served as reference. Inter-observer agreement was assessed by calculating the Dice similarity coefficient (DSC).

RESULTS

Most contouring methods provided high sensitivity and specificity. For manual delineation, scaling the PET images from SUVmin-max: 0-5 resulted in high sensitivity (>86%). The highest specificity (100%) was obtained by scaling the PET images from SUVmin-max: 0-SUVmax. High interobserver agreement (median DSC 0.8) was observed when using the same PET image scaling technique (PET images SUVmin-max: 0-5). For semi-automatic segmentation, a low SUVmax threshold of 20% optimized sensitivity (SUVmax threshold 20%, 100% sensitivity, 32% of prostatic volume), whereas a higher threshold optimized specificity (SUVmax threshold 40%-50%, 100% specificity).

CONCLUSIONS

Contouring of regions with high tracer-uptake resulted in very high specificities and should be used for biopsy guidance. Both manual and semi-automatic approaches using validated SUV scaling (SUVmin-max: 0-5) or thresholding (20%) may provide high sensitivity, and should be considered for PSMA-PET-based focal therapy approaches.

[Delineation of the primary tumour clinical target volumes and neck node levels selection of parotid cancers]

Salivary glands tumours are uncommon tumours showing a large diversity of histological types. This article presents a synthesis of patterns and paths of invasion of parotid glands tumours in order to propose an approach of the delineation of primary tumour clinical target volumes and of the selection of lymph nodes target volumes. This article does not discuss treatment indications but defines clinical target volumes to treat if radiotherapy is indicated. Postoperative situation being the most frequent, the delineation of primary tumour clinical target volume is based on an anatomical approach.

A review of automatic lung tumour segmentation in the era of 4DCT

Aim

To review the literature on auto-contouring methods of lung tumour volumes on four-dimensional computed tomography (4DCT).

Background

Manual delineation of lung tumour on 4DCT has been the gold standard in clinical practice. However, it is resource intensive due to the high volume of data which results in longer contouring duration and uncertainties in defining target. Auto-contouring may present as an attractive alternative by decreasing manual inputs required, thus improving the contouring process. This review aims to assess the accuracy, variability and contouring duration of automatic contouring compared with manual contouring in lung cancer on 4DCT datasets.

Materials and methods

A search and review of literature were conducted to identify studies regarding lung tumour contouring on 4DCT. Manual and auto-contours were assessed and compared based on accuracy, variability and contouring duration.

Results

Thirteen studies were included in this review and their results were compared. Accuracy of auto-contours was found to be comparable to manual contours. Auto-contouring resulted in lesser inter-observer variation when compared to manual contouring, however there was no significant reduction in intra-observer variability. Additionally, contouring duration was reduced with auto-contouring although long computation time could present as a bottleneck.

Conclusion

Auto-contouring is reliable and efficient, producing accurate contours with better consistency compared to manual contours. However, manual inputs would still be required both before and after auto-propagation.

Harmonization of practices between radiotherapy centres in the Nord and Pas-de-Calais regions (France): A three-year evaluation

PURPOSE

The delineation of volumes of interest can be a source of significant interobserver variability. The purpose of this study was to improve the homogeneity of delineation between oncologist-radiotherapists in the territorial departments of Nord and Pas-de-Calais (France) through discussions of clinical cases and the adoption of common published reference documents.

MATERIALS AND METHODS

All eleven radiotherapy centres in the Nord and Pas-de-Calais departments of France participated. The localizations assessed to date included prostate, head and neck, breast and brain cancers. For each localization, the junior or senior physician(s) in charge of pathology delineated the volumes of interest according to their usual practices. Validated indices, including the Dice similarity coefficient, were used to quantify the delineation differences. The anonymized results were presented at two to three annual meetings. A second delineation of the clinical cases was then carried out to quantify homogenization. An evaluation of dosimetry practices was also conducted for prostate cancer. Wilcoxon assay matched data were used.

RESULTS

Our work showed either satisfactory delineation concordance after the initial assessment or improved delineation concordance. For prostate cancer, the Dice similarity coefficient values were greater than 0.6 initially in two of the three clinical cases. For head and neck cancers, a statistically significant improvement was observed for only one of the clinical target volumes. More than half of the Dice similarity coefficient values were greater than 0.6 in the first comparison. The study of clinical cases of breast cancer allowed a homogenization of the delineation of five of the six lymph node clinical target volumes. The dosimetry study of prostate cancer allowed for a homogenization of practices.

CONCLUSION

This work makes it possible to harmonize the delineation practices around validated standards. An extension to the entire Hauts-de-France region is planned.

Usefulness of Narrow-Band Imaging in Endoscopic Submucosal Dissection of the Stomach

There have been many advances in endoscopic imaging technologies. Magnifying endoscopy with narrow-band imaging is an innovative optical technology that enables the precise discrimination of structural changes on the mucosal surface. Several studies have demonstrated its usefulness and superiority for tumor detection and differential diagnosis in the stomach as compared with conventional endoscopy. Furthermore, magnifying endoscopy with narrow-band imaging has the potential to predict the invasion depth and tumor margins during gastric endoscopic submucosal dissection. Classifications of the findings of magnifying endoscopy with narrow-band imaging based on microvascular and pit patterns have been proposed and have shown excellent correlations with invasion depth confirmed by microscopy. In terms of tumor margin prediction, magnifying endoscopy with narrow-band imaging offers superior delineation of gastric tumor margins compared with traditional chromoendoscopy with indigo carmine. The limitations of narrow-band imaging, such as the need for considerable training, long procedure time, and lack of studies about its usefulness in undifferentiated cancer, should be resolved to confirm its value as a complementary method to endoscopic submucosal dissection. However, the role of magnifying endoscopy with narrow-band imaging is expected to increase steadily with the increasing use of endoscopic submucosal dissection for the treatment of gastric tumors.

Delineation of lung cancer with FDG PET/CT during radiation therapy

OBJECTIVES

To propose an easily applicable segmentation method (perPET-RT) for delineation of tumour volume during radiotherapy on interim fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with non-small cell lung cancer (NSCLC).

MATERIAL AND METHODS

Sixty-seven patients (51 primary tumours, 60 lymph nodes), from 4 prospective studies, underwent an FDG PET/CT scan during the fifth week of radiation therapy, using different generations of PET/CT. Per-therapeutic PET/CT scans were delineated in consensus by two experienced physicians leading to the gold standard threshold to be applied. The mathematical expression of Th_opt, the optimal threshold to be applied as a function of the maximum standard uptake value (SUV_max), was determined. The performance of this method (perPET-RT) was assessed by computing the DICE similarity coefficient (DSC) and was compared with 8 fixed threshold values and 3 adaptive thresholding methods.

RESULTS

Th_opt verified the following expression: Th_opt = A.ln(1/SUV_max) + B where A and B were 2 constants. A and B were independent from the generation of PET/CT, but depended on the type of lesions (primary lung tumours vs. lymph nodes). PerPET-RT showed good to very good agreement in comparison to the gold standard. The mean and standard deviation of DSC value was 0.81 ± 0.13 for lung lesions and 0.78 ± 0.15 for lymph nodes. PerPET-RT showed a significant better agreement than the other segmentation methods (p < 0.001), except for one of the adaptive thresholding method ADT (p = 0.11).

CONCLUSION

On the database used, perPET-RT has proven its reliability and accuracy for tumour delineation on per-therapeutic FDG PET/CT using only SUV_max measurement. This method may be used to delineate tumour volume for dose-escalation planning.

TRIAL REGISTRATION

NCT01261598 , NCT01261585 , NCT01576796 .

Contouring workload in adjuvant breast cancer radiotherapy

PURPOSE

To measure the impact of contouring on worktime in the adjuvant radiation treatment of breast cancer, and to identify factors that might affect the measurements.

MATERIAL AND METHODS

The dates and times of contouring clinical target volumes and organs at risk were recorded by a senior and by two junior radiation oncologists. Outcome measurements were contour times and the time from start to approval. The factors evaluated were patient age, type of surgery, radiation targets and setup, operator, planning station, part of the day and day of the week on which the contouring started. The Welch test was used to comparatively assess the measurements.

RESULTS

Two hundred and three cases were included in the analysis. The mean contour time per patient was 34minutes for a mean of 4.72 structures, with a mean of 7.1minutes per structure. The clinical target volume and organs at risk times did not differ significantly. The mean time from start to approval per patient was 29.4hours. Factors significantly associated with longer contour times were breast-conserving surgery (P=0.026), prone setup (P=0.002), junior operator (P<0.0001), Pinnacle planning station (P=0.026), contouring start in the morning (P=0.001), and contouring start by the end of the week (P<0.0001). Factors significantly associated with time from start to approval were age (P=0.038), junior operator (P<0.0001), planning station (P=0.016), and contouring start by the end of the week (P=0.004).

CONCLUSION

Contouring is a time-consuming process. Each delineated structure influences worktime, and many factors may be targeted for optimization of the workflow. These preliminary data will serve as basis for future prospective studies to determine how to establish a cost-effective solution.

[Anal canal cancer: In the era of intensity-modulated radiotherapy, outstanding issues]

Intensity-modulated radiotherapy makes possible to optimize the irradiation and spare normal tissues. The toxicity remains important with concomitant chemotherapy often associated. The improvement of MRI and PET-CT define more precisely the target volumes, which need a higher dose, but necessitates to respect the rules of contouring. The treatment is uniform whatever the stage but should be individualized based on clinical stage and tumor response. New paradigms concern biology, staging, volumes and doses, fractionation and combined treatments.