Deep learning-based automatic detection of tuberculosis disease in chest X-ray images.

Purpose: To train a convolutional neural network (CNN) model from scratch to automatically detect tuberculosis (TB) from chest X-ray (CXR) images and compare its performance with transfer learning based technique of different pre-trained CNNs. Material and methods: We used two publicly available datasets of postero-anterior chest radiographs, which are from Montgomery County, Maryland, and Shenzhen, China. A CNN (ConvNet) from scratch was trained to automatically detect TB on chest radiographs. Also, a CNN-based transfer learning approach using five different pre-trained models, including Inception_v3, Xception, ResNet50, VGG19, and VGG16 was utilized for classifying TB and normal cases from CXR images. The performance of models for testing datasets was evaluated using five performances metrics, including accuracy, sensitivity/recall, precision, area under curve (AUC), and F1-score. Results: All proposed models provided an acceptable accuracy for two-class classification. Our proposed CNN architecture (i.e., ConvNet) achieved 88.0% precision, 87.0% sensitivity, 87.0% F1-score, 87.0% accuracy, and AUC of 87.0%, which was slightly less than the pre-trained models. Among all models, Exception, ResNet50, and VGG16 provided the highest classification performance of automated TB classification with precision, sensitivity, F1-score, and AUC of 91.0%, and 90.0% accuracy. Conclusions: Our study presents a transfer learning approach with deep CNNs to automatically classify TB and normal cases from the chest radiographs. The classification accuracy, precision, sensitivity, and F1-score for the detection of TB were found to be more than 87.0% for all models used in the study. Exception, ResNet50, and VGG16 models outperformed other deep CNN models for the datasets with image augmentation methods.

Automated deep learning-based segmentation of COVID-19 lesions from chest computed tomography images.

Purpose: The novel coronavirus COVID-19, which spread globally in late December 2019, is a global health crisis. Chest computed tomography (CT) has played a pivotal role in providing useful information for clinicians to detect COVID-19. However, segmenting COVID-19-infected regions from chest CT results is challenging. Therefore, it is desirable to develop an efficient tool for automated segmentation of COVID-19 lesions using chest CT. Hence, we aimed to propose 2D deep-learning algorithms to automatically segment COVID-19-infected regions from chest CT slices and evaluate their performance. Material and methods: Herein, 3 known deep learning networks: U-Net, U-Net++, and Res-Unet, were trained from scratch for automated segmenting of COVID-19 lesions using chest CT images. The dataset consists of 20 labelled COVID-19 chest CT volumes. A total of 2112 images were used. The dataset was split into 80% for training and validation and 20% for testing the proposed models. Segmentation performance was assessed using Dice similarity coefficient, average symmetric surface distance (ASSD), mean absolute error (MAE), sensitivity, specificity, and precision. Results: All proposed models achieved good performance for COVID-19 lesion segmentation. Compared with Res-Unet, the U-Net and U-Net++ models provided better results, with a mean Dice value of 85.0%. Compared with all models, U-Net gained the highest segmentation performance, with 86.0% sensitivity and 2.22 mm ASSD. The U-Net model obtained 1%, 2%, and 0.66 mm improvement over the Res-Unet model in the Dice, sensitivity, and ASSD, respectively. Compared with Res-Unet, U-Net++ achieved 1%, 2%, 0.1 mm, and 0.23 mm improvement in the Dice, sensitivity, ASSD, and MAE, respectively. Conclusions: Our data indicated that the proposed models achieve an average Dice value greater than 84.0%. Two-dimensional deep learning models were able to accurately segment COVID-19 lesions from chest CT images, assisting the radiologists in faster screening and quantification of the lesion regions for further treatment. Nevertheless, further studies will be required to evaluate the clinical performance and robustness of the proposed models for COVID-19 semantic segmentation.

Effectiveness of rectal displacement devices in managing prostate motion: a systematic review.

PURPOSE: To determine whether rectal displacement devices (RDDs) have a prostate-stabilizing effect during prostate external beam radiotherapy (EBRT). METHODS: A systematic literature search using the PubMed database from January 1, 2000 to December 30th, 2019 was conducted. The effect of RDDs on inter- and intra-fractional prostate displacements was extracted. RESULTS: From 356 articles identified via the PubMed database and hand search, 21 articles were included in the systematic review. There was no randomized study. Twelve studies evaluated the role of the endorectal balloon (ERB) in managing prostate motion. Four studies reported the effect of hydrogel spacer on prostate motion. Four studies examined the effect of the rectal retractor (RR) on intra-fractional prostate motion, and only one study assessed the impact of ProSpare (Nottinghamshire, UK) in reducing prostate motion. CONCLUSION: Using an ERB significantly reduces intra-fractional prostate motion. This prostate-stabilizing effect of the ERB can translate into reduced planning target volume (PTV) margins and additional rectal dose sparing. Even with an ERB in place, inter-fractional prostate displacements are seen. As a consequence, ERB application does not obviate daily verification; however, this is not a crucial topic because pretreatment imaging is always done nowadays. As compared with ERB, the hydrogel spacer significantly reduces rectal dose and toxicity without influencing prostate immobilization. The RR can increase prostate and rectal inter- and intra-fractional stability without a clear influence on the reduction of rectal toxicity. Finally, it is unclear whether ProSpare is a suitable device reducing prostate motion. Further study will be required to clarify whether the prostate-stabilizing effects of the ERB and RR can result in a safe reduction of PTV margins and further sparing of organs at risks, especially the rectum.

A historical literature review on the role of posterior axillary boost field in the axillary lymph node coverage and development of lymphedema following regional nodal irradiation in breast cancer.

To elucidate whether (1) a posterior axillary boost (PAB) field is an optimal method to target axillary lymph nodes (LNs); and (2) the addition of a PAB increases the incidence of lymphedema, a systematic review was undertaken. A literature search was performed in the PubMed database. A total of 16 studies were evaluated. There were no randomized studies. Seven articles have investigated dosimetric aspects of a PAB. The remaining 9 articles have determined the effect of a PAB field on the risk of lymphedema. Only 2 of 9 articles have prospectively reported the impact of a PAB on the risk of lymphedema development. There are conflicting reports on the necessity of a PAB. The PAB field provides a good coverage of level I/II axillary LNs because these nodes are usually at a greater depth. The main concern regarding a PAB is that it produces a hot spot in the anterior region of the axilla. Planning studies optimized a traditional PAB field. Prospective studies and the vast majority of retrospective studies have reported the use of a PAB field does not result in increasing the risk of lymphedema development over supraclavicular-only field. The controversies in the incidence of lymphedema suggest that field design may be more important than field arrangement. A key factor regarding the use of a PAB is the depth of axillary LNs. The PAB field should not be used unless there is an absolute indication for its application. Clinicians should weigh lymphedema risk in individual patients against the limited benefit of a PAB, in particular after axillary dissection. The testing of the inclusion of upper arm lymphatics in the regional LN irradiation target volume, and universal methodology measuring lymphedema are all areas for possible future studies.

Molecular imaging in tracking cancer stem cells: A review.

Cancer stem cells (CSCs) have critical roles in tumor development, progression, and recurrence. They are responsible for current cancer treatment failure and remain questionable for the design and development of new therapeutic strategies. With this issue, medical imaging provides several clues for finding biological mechanisms and strategies to treat CSCs. This review aims to summarize current molecular imaging approaches for detecting CSCs. In addition, some promising issues for CSCs finding and explaining biological mechanisms have been addressed. Among the molecular imaging approaches, modalities including Magnetic resonance imaging (MRI) and positron emission tomography (PET) have the greatest roles and several new approaches such as optical imaging are in progress.

Assessment of background radiation levels in the southeast of Iran.

Background: Measuring background radiation (BR) is highly important from different perspectives, especially from that of human health. This study was conducted to measure BR in the southeast of Iran. Methods: BR was measured in Hormozgan and Sistan-Bluchestan provinces using portable Environmental Radiation Meter Type 6- 80 detector. The average value was used to calculate the absorbed dose rate and indoor annual effective dose (AED) from BR. In addition, excess lifetime cancer risk (ELCR) was evaluated. Results: The results showed that the maximum and minimum absorbed dose rates were 71.9 and 34.2 nGy.h-1 in Abomoosa and Minab in Hormozgan province and 90.0 and 47.8 nGy.h-1 in Zahedan and Chabahar in Sistan-Bluchestan province, respectively. Data indicated that these areas had a lower BR level compared with the worldwide level. The ELCR from indoor AED was larger compared with the worldwide average of 0.29 × 10-3. Conclusion: This study provided a reference for designing and developing specific regional surveys associated with the measurement of natural BR in the southeast of Iran.

Analysis of trace elements in human hair through X-ray fluorescence spectroscopy for screening of prostate cancer.

Background: Use of hair samples to analyze the trace element concentrations is one of the interesting fields among many researchers. X-ray fluorescence (XRF) is considered as one of the most common methods in studying the concentration of elements in tissues and also crystalline materials, using low energy X-ray. In the present study, we aimed to evaluate the concentration of the trace elements in the scalp hair sample through XRF spectroscopy using signal processing techniques as a screening tool for prostate cancer. Methods: Hair samples of 22 men (including 11 healthy and 11 patients) were analyzed. All the sample donors were Iranian men. EDXRF method was used for the measurements. Signals were analyzed, and signal features such as mean, root-mean-square (RMS), variance, and standard deviation, skewness, and energy were investigated. The Man-Whitney U test was used to compare the trace element concentrations. The analysis of variance (ANOVA) test was used to identify which extracted feature could help to identify healthy and patient people. P values ≤ 0.05 were considered statistically significant. Statistical analysis was performed using SPSS 16.0 software. Results: The mean±SD age was 67.8±8.7 years in the patient group and 61.4±6.9 years in the healthy group. There were statistically significant differences in the aluminum (Al, P<0.001), silicon (Si, P=0.006), and phosphorus (P, P=0.028) levels between healthy and patient groups. Skewness and variance were found to be relevant in identifying people with cancer, as signal features. Conclusion: The use of EDXRF is a feasible method to study the concentration of elements in the hair sample, and this technique may be effective in prostate cancer screening. Further study with a large sample size will be required to elucidate the efficacy of the present method in prostate cancer screening.

Rectal retractor application during image-guided dose-escalated prostate radiotherapy.

PURPOSE: To investigate efficacy of a rectal retractor (RR) on rectal dose during image-guided dose-escalated prostate three-dimensional conformal radiotherapy (3DCRT). PATIENTS AND METHODS: In all, 21 patients with localized prostate cancer were treated with a RR for 3DCRT in 40â€¯× 2 Gy. Patient underwent two scans for radiotherapy planning, without and with RR. RR was used for the first half of the treatment sessions. Two plans were created for each patient to compare the effect of RR on rectal doses. PTW-31014 Pinpoint chamber embedded within RR was used for in vivo dosimetry in 6 of 21 patients. The patient tolerance and acute rectal toxicity were surveyed during radiotherapy using Common Terminology Criteria for Adverse Events (CTCAE) v.4.0. RESULTS: Patients tolerated the RR well during 20 fractions with mild degree of anal irritation. Using a RR significantly reduced the rectal wall (RW), anterior RW and posterior RW dose-volume parameters. The average RW Dmean was 29.4 and 43.0 Gy for plans with and without RR, respectively. The mean discrepancy between the measured dose and planned dose was -3.8% (±4.9%). Grade 1 diarrhea, rectal urgency and proctitis occurred in 4, 2 and 3 cases, respectively. There were no grade ≥2 acute rectal toxicities during the treatment. CONCLUSION: Rectal retraction resulted in a significant reduction of rectal doses with a safe toxicity profile, which may reduce rectal toxicity. Dosimeter inserted into the RR providing a practical method for in vivo dosimetric verification. Further prospective clinical studies will be necessary to demonstrate the clinical advantage of RR.

Analysis of the role of thrombomodulin in all-trans retinoic acid treatment of coagulation disorders in cancer patients.

BACKGROUND: Clinical studies have shown that all-trans retinoic acid (RA), which is often used in treatment of cancer patients, improves hemostatic parameters and bleeding complications such as disseminated intravascular coagulation (DIC). However, the mechanisms underlying this improvement have yet to be elucidated. In vitro studies have reported that RA upregulates thrombomodulin (TM) expression on the endothelial cell surface. The objective of this study was to investigate how and to what extent the TM concentration changes after RA treatment in cancer patients, and how this variation influences the blood coagulation cascade. RESULTS: In this study, we introduced an ordinary differential equation (ODE) model of gene expression for the RA-induced upregulation of TM concentration. Coupling the gene expression model with a two-compartment pharmacokinetic model of RA, we obtained the time-dependent changes in TM and thrombomodulin-mRNA (TMR) concentrations following oral administration of RA. Our results indicated that the TM concentration reached its peak level almost 14 h after taking a single oral dose (110 [Formula: see text]) of RA. Continuous treatment with RA resulted in oscillatory expression of TM on the endothelial cell surface. We then coupled the gene expression model with a mechanistic model of the coagulation cascade, and showed that the elevated levels of TM over the course of RA therapy with a single daily oral dose (110 [Formula: see text]) of RA, reduced the peak thrombin levels and endogenous thrombin potential (ETP) up to 50 and 49%, respectively. We showed that progressive reductions in plasma levels of RA, observed in continuous RA therapy with a once-daily oral dose (110 [Formula: see text]) of RA, did not affect TM-mediated reduction of thrombin generation significantly. This finding prompts the hypothesis that continuous RA treatment has more consistent therapeutic effects on coagulation disorders than on cancer. CONCLUSIONS: Our results indicate that the oscillatory upregulation of TM expression on the endothelial cells over the course of RA therapy could potentially contribute to the treatment of coagulation abnormalities in cancer patients. Further studies on the impacts of RA therapy on the procoagulant activity of cancer cells are needed to better elucidate the mechanisms by which RA therapy improves hemostatic abnormalities in cancer.

Fiducial markers in prostate cancer image-guided radiotherapy.

Background: Image-guided radiotherapy (IGRT) is recommended to reduce the risk of geometrical miss when modern radiotherapy technologies with high grades of conformity are used. The purpose of this study was to evaluate the efficacy of fiducial markers (FMs) for electronic portal imaging in prostate cancer radiotherapy in term of evaluating the complications associated with FMs implantation, quantifying inter-fraction prostate motion, and determination of optimal planning target volume (PTV) margins. Methods: In this single institution, prospective, consecutive study, 27 patients underwent implantation of three-gold seed FMs into the prostate gland before prostate radiotherapy. Prior to computed tomography planning, all patients were asked to report any complication associated with FMs implantation that have experienced to date. Daily pre-treatment electronic portal images were captured, and prostate position errors were corrected if they were greater than 2 mm along three translational directions. Optimal PTV expansions were computed using van Herk formula [PTV-margin= 2.5Σ + 0.7σ]. Results: FMs implantation was successful with an acceptable toxicity profile in all patients. Without IGRT, margins of 5.4 mm, 5.8 mm and 5.5 mm, in vertical, longitudinal and lateral directions, respectively, are needed for a 95% confidence level of complete clinical target volume (CTV) coverage in each treatment session. The PTV margins of 3.0 mm, 3.3 mm and 4.0 mm in corresponding directions were calculated when FMs based electronic portal imaging was applied. Conclusion: FMs based electronic portal imaging is an effective tool for prostate cancer IGRT.

Reject analysis in digital radiography: A local study on radiographers and students' attitude in Iran.

Reject analysis is as a quality indicator and critical tool for dose and image quality optimization in radiology departments. By reducing image rejection rate (RR), radiation dose to patients can be reduced effectively, yielding increased total cost-effectiveness. The aims of this study were to assess the rate of image rejection at 2 direct digital radiography (DR) departments to find the sources of rejection and to observe how radiology students and radiographers deal with image rejection. Two radiology departments were surveyed during a 3-month period for all imaging procedures. Type of examination, numbers, and reasons for digital image rejection were obtained by systems and questionnaire. A predefined questionnaire, including 13 causes for rejection, was filled by radiographers and students. Out of the 14 022 acquired images, 1116 were rejected, yielding an overall RR of 8%. Highest RRs were found for examination of cervical spine and lumbosacral. Positioning errors and improper patient preparation were the main reasons for digital image rejection. The image RR was small, but there is a need for optimizing radiographic practice, and enhancing radiographer's knowledge may enhance the performance.

Identification of influential proteins in the classical retinoic acid signaling pathway.

BACKGROUND: In the classical pathway of retinoic acid (RA) mediated gene transcription, RA binds to a nuclear hormone receptor dimer composed of retinoic acid receptor (RAR) and retinoid X receptor (RXR), to induce the expression of its downstream target genes. In addition to nuclear receptors, there are other intracellular RA binding proteins such as cellular retinoic acid binding proteins (CRABP1 and CRABP2) and cytochrome P450 (CYP) enzymes, whose contributions to the RA signaling pathway have not been fully understood. The objective of this study was to compare the significance of various RA binding receptors, i.e. CRABP1, CRABP2, CYP and RAR in the RA signaling pathway. In this regard, we developed a mathematical model of the RA pathway, which is one of the few models, if not the only one, that includes all main intracellular RA binding receptors. We then performed a global sensitivity analysis (GSA) to investigate the contribution of the RA receptors to RA-induced mRNA production, when the cells were treated with a wide range of RA levels, from physiological to pharmacological concentrations. RESULTS: Our results show that CRABP2 and RAR are the most and the least important proteins, respectively, in controlling the model performance at physiological concentrations of RA (1-10 nM). However, at higher concentrations of RA, CYP and RAR are the most sensitive parameters of the system. Furthermore, we found that depending on the concentrations of all RA binding proteins, the rate of metabolism of RA can either change or remain constant following RA therapy. The cellular levels of CRABP1 are more important than that of CRABP2 in controlling RA metabolite formation at pharmacological conditions (RA = 0.1-1 µM). Finally, our results indicate a significant negative correlation between total mRNA production and total RA metabolite formation at pharmacological levels of RA. CONCLUSIONS: Our simulations indicate that the significance of the RA binding proteins in the RA pathway of gene expression strongly depends on intracellular concentration of RA. This study not only can explain why various cell types respond to RA therapy differently, but also can potentially help develop pharmacological methods to increase the efficacy of the drug.

Rectal retractor in prostate radiotherapy: pros and cons.

Dose escalation in prostate radiotherapy (RT) have led to improved biochemical controls and reduced the risk of distant metastases. Over the past three decades, despite technological advancements in RT planning and delivery, the rectum is a dose-limiting structure in prostate RT owing to the close anatomical proximity of the anterior rectal wall (ARW) to the prostate gland. RT-induced rectal toxicities remain a clinical challenge, limiting the prescribed dose during prostate RT. To address the spatial proximity challenge by physically increasing the distance between the posterior aspect of the prostate and the ARW, several physical devices such as endorectal balloons (ERBs), rectal hydrogel spacers, and rectal retractor (RR) have been developed. Previously, various aspects of ERBs and rectal hydrogel spacers have extensively been discussed. Over recent years, given the interest in the application of RR in prostate external beam radiotherapy (EBRT), this editorial will discuss opportunities and challenges of using RR during prostate EBRT and provide information regarding which aspects of this device need attention.

Deep transfer learning-based fully automated detection and classification of Alzheimer's disease on brain MRI.

OBJECTIVES: To employ different automated convolutional neural network (CNN)-based transfer learning (TL) methods for both binary and multiclass classification of Alzheimer's disease (AD) using brain MRI. METHODS: Herein, we applied three popular pre-trained CNN models (ResNet101, Xception, and InceptionV3) using a fine-tuned approach of TL on 3D T1-weighted brain MRI from a subset of ADNI dataset (n = 305 subjects). To evaluate power of TL, the aforementioned networks were also trained from scratch for performance comparison. Initially, Unet network segmentedthe MRI scans into characteristic components of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). The proposed networks were trained and tested over the pre-processed and augmented segmented and whole images for both binary (NC/AD + progressive mild cognitive impairment (pMCI)+stable MCI (sMCI)) and 4-class (AD/pMCI/sMCI/NC) classification. Also, two independent test sets from the OASIS (n = 30) and AIBL (n = 60) datasets were used to externally assess the performance of the proposed algorithms. RESULTS: The proposed TL-based CNN models achieved better performance compared to the training CNN models from scratch. On the ADNI test set, InceptionV3-TL achieved the highest accuracy of 93.75% and AUC of 92.0% for binary classification, as well as the highest accuracy of 93.75% and AUC of 96.0% for multiclass classification of AD on the whole images. On the OASIS test set, InceptionV3-TL outperformed two other models by achieving 93.33% accuracy with 93.0% AUC in binary classification of AD on the whole images. On the AIBL test set, InceptionV3-TL also outperformed two other models in both binary and multiclass classification tasks on the whole MR images and achieved accuracy/AUC of 93.33%/95.0% and 90.0%/93.0%, respectively. The GM segment as input provided the highest performance in both binary and multiclass classification of AD, as compared to the WM and CSF segments. CONCLUSION: This study demonstrates the potential of applying deep TL approach for automated detection and classification of AD using brain MRI with high accuracy and robustness across internal and external test data, suggesting that these models can possibly be used as a supportive tool to assist clinicians in creating objective opinion and correct diagnosis. ADVANCES IN KNOWLEDGE: We used CNN-based TL approaches and the augmentation techniques to overcome the insufficient data problem. Our study provides evidence that deep TL algorithms can be used for both binary and multiclass classification of AD with high accuracy.

Automated detection of pneumonia cases using deep transfer learning with paediatric chest X-ray images.

OBJECTIVE: Pneumonia is a lung infection and causes the inflammation of the small air sacs (Alveoli) in one or both lungs. Proper and faster diagnosis of pneumonia at an early stage is imperative for optimal patient care. Currently, chest X-ray is considered as the best imaging modality for diagnosing pneumonia. However, the interpretation of chest X-ray images is challenging. To this end, we aimed to use an automated convolutional neural network-based transfer-learning approach to detect pneumonia in paediatric chest radiographs. METHODS: Herein, an automated convolutional neural network-based transfer-learning approach using four different pre-trained models (i.e. VGG19, DenseNet121, Xception, and ResNet50) was applied to detect pneumonia in children (1-5 years) chest X-ray images. The performance of different proposed models for testing data set was evaluated using five performances metrics, including accuracy, sensitivity/recall, Precision, area under curve, and F1 score. RESULTS: All proposed models provide accuracy greater than 83.0% for binary classification. The pre-trained DenseNet121 model provides the highest classification performance of automated pneumonia classification with 86.8% accuracy, followed by Xception model with an accuracy of 86.0%. The sensitivity of the proposed models was greater than 91.0%. The Xception and DenseNet121 models achieve the highest classification performance with F1-score greater than 89.0%. The plotted area under curve of receiver operating characteristics of VGG19, Xception, ResNet50, and DenseNet121 models are 0.78, 0.81, 0.81, and 0.86, respectively. CONCLUSION: Our data showed that the proposed models achieve a high accuracy for binary classification. Transfer learning was used to accelerate training of the proposed models and resolve the problem associated with insufficient data. We hope that these proposed models can help radiologists for a quick diagnosis of pneumonia at radiology departments. Moreover, our proposed models may be useful to detect other chest-related diseases such as novel Coronavirus 2019. ADVANCES IN KNOWLEDGE: Herein, we used transfer learning as a machine learning approach to accelerate training of the proposed models and resolve the problem associated with insufficient data. Our proposed models achieved accuracy greater than 83.0% for binary classification.

Rectal wall sparing effect of a rectal retractor in prostate intensity-modulated radiotherapy.

PURPOSE: The objective of the study was to evaluate the effectiveness of a rectal retractor (RR) designed to protect rectal tissue in intensity-modulated radiotherapy (IMRT) by pushing rectal wall (RW) away from the prostate. MATERIALS AND METHODS: Twelve patients with localized prostate cancer were enrolled into this study. Patients underwent two computed tomography (CT) scans without and with RR. A prescription of 80 Gy in 40 fractions was planned on CT scans with and without RR. This study evaluates the ability of the RR in RW dose reduction, in particular reduction of the RW V70Gy≥ 25% in comparison with the plan without RR dose-volume histograms were generated with and without RR. The patient's tolerance was assessed by patient-reported outcomes. RESULTS: The planning target volume coverage was equal for both without and with RR (P = 0.155). The mean dose to the RW was statistically significantly lower for the plan with RR than that for the plan without RR, a mean reduction of 5.8 Gy (P = 0.003). Significant relative reductions in rectal dose-volume parameters whether in absolute volume (cc) or as a percentage of contoured RW were detected. A relative reduction more than 25% in RW V70Gy(%) in 100% of patients was achieved. The rectal retraction resulted in a significant increase in the prostate to the rectum space at the prostate midgland level, an absolute increase of 2.7 mm. The retraction of the rectum induced a mean (±standard deviation) pain score of 2.7 (±1.3) according to the visual analog score. CONCLUSION: The application of a RR showed a remarkable rectal sparing effect during prostate IMRT. This may lead to reduced acute and late rectal toxicities in prostate IMRT.

Effectiveness of rectal displacement devices during prostate external-beam radiation therapy: A review.

Dose-escalated prostate radiotherapy (RT) can improve treatment outcomes, but rectal toxicity is the main limiting factor for introducing dose-escalated RT. Pushing rectal wall away from the prostate reduces the volume of the rectum in high-dose region, which can decrease both short- and long-term rectal toxicities after RT. This review focuses on the literature using different rectal displacement devices such as endorectal balloons, tissue spacers, rectal retractor, and ProSpare during prostate External beam radiotherapy, with regard to dosimetric effects, clinical benefits, prostate motion, and postoperative RT setting.