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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

In regard to Cuccia et al.: impact of hydrogel peri-rectal spacer insertion on prostate gland intra-fraction motion during 1.5 T MR-guided stereotactic body radiotherapy.

We read the article entitled "Impact of hydrogel peri-rectal spacer insertion on prostate gland intra-fraction motion during 1.5 T MR-guided stereotactic body radiotherapy" with great interest. In that study, the author reported that there is a statistically significant difference in the rotational antero-posterior shifts between the spacer and the non-spacer groups. Also, there was no statistically significant difference between the groups in terms of translational shifts. However, there are some points about the study. In this letter, we aimed to clarify these points.

Regulation of CSF and Brain Tissue Sodium Levels by the Blood-CSF and Blood-Brain Barriers During Migraine.

Cerebrospinal fluid (CSF) and brain tissue sodium levels increase during migraine. However, little is known regarding the underlying mechanisms of sodium homeostasis disturbance in the brain during the onset and propagation of migraine. Exploring the cause of sodium dysregulation in the brain is important, since correction of the altered sodium homeostasis could potentially treat migraine. Under the hypothesis that disturbances in sodium transport mechanisms at the blood-CSF barrier (BCSFB) and/or the blood-brain barrier (BBB) are the underlying cause of the elevated CSF and brain tissue sodium levels during migraines, we developed a mechanistic, differential equation model of a rat's brain to compare the significance of the BCSFB and the BBB in controlling CSF and brain tissue sodium levels. The model includes the ventricular system, subarachnoid space, brain tissue and blood. Sodium transport from blood to CSF across the BCSFB, and from blood to brain tissue across the BBB were modeled by influx permeability coefficients P BCSFB and P BBB , respectively, while sodium movement from CSF into blood across the BCSFB, and from brain tissue to blood across the BBB were modeled by efflux permeability coefficients P B C S F B ' and P B B B ' , respectively. We then performed a global sensitivity analysis to investigate the sensitivity of the ventricular CSF, subarachnoid CSF and brain tissue sodium concentrations to pathophysiological variations in P BCSFB , P BBB , P B C S F B ' and P B B B ' . Our results show that the ventricular CSF sodium concentration is highly influenced by perturbations of P BCSFB , and to a much lesser extent by perturbations of P B C S F B ' . Brain tissue and subarachnoid CSF sodium concentrations are more sensitive to pathophysiological variations of P BBB and P B B B ' than variations of P BCSFB and P B C S F B ' within 30 min of the onset of the perturbations. However, P BCSFB is the most sensitive model parameter, followed by P BBB and P B B B ' , in controlling brain tissue and subarachnoid CSF sodium levels within 3 h of the perturbation onset.

Optimization of prostate brachytherapy techniques with polyethylene glycol-based hydrogel spacers: A systematic review.

PURPOSE: The objective of this overview was to critically evaluate the effect of polyethylene glycol (PEG)-based hydrogel spacers during prostate brachytherapy with regard to dosimetric and clinical benefits, as well as procedure-related toxicity. METHODS AND MATERIALS: A systematic search in the PubMed database was performed. RESULTS: A total of 12 studies, involving 615 patients with PEG hydrogel injection, were included. Overall, patients well tolerated the implantation of PEG hydrogel spacers with an excellent safety profile. However, although there were some procedure-related complications, rates of these complications were very rare. Toxicities related to the spacer were limited to Grade 1 rectal discomfort and pain (9/615 patients), Grade 2 rectal ulceration (1 in 615 patients), perineal abscess (1 in 615 patients), and bacterial prostatitis (2/615 patients) according to Common Terminology Criteria for Adverse Events v4.0 grading scheme. The application of PEG hydrogel spacers significantly reduced radiation doses to the rectum during prostate brachytherapy in the different setting. Although there was no prospective randomized clinical trial, retrospective studies showed that reducing rectal doses by the implantation of PEG hydrogel may result in an improvement in rectal toxicity. CONCLUSIONS: The insertion of hydrogel spacers is safe, resulting in a significant decrease in rectal doses. This may lead to a reduction in rectal or gastrointestinal toxicity. Prospective randomized clinical trials are warranted to confirm the clinical impact of rectal dosimetric improvements.

Application of rectal retractor for postprostatectomy salvage radiotherapy of prostate cancer: A case report and literature review.

Using a rectal retractor (RR) during salvage radiotherapy after radical prostatectomy is a promising approach for reducing dose to the rectum. The patient well tolerated the daily RR insertion. This area of research encourages researchers for a comprehensive evaluation of the role of the RR in postprostatectomy radiotherapy.