In-vivo Comparison of Planned and Measured Rectal Doses during Cobalt-60 HDR CT-based Intracavitary Brachytherapy Applications of Cervical Cancer Using the PTW 9112 Semiconductor Probe.

BACKGROUND: A semiconductor rectal probe was used to compare planned and measured rectal doses during Co-60 high dose rate (HDR) CT-based intracavitary brachytherapy applications (ICBT) of cervical cancer. MATERIALS AND METHODS: A total of 22 HDR brachytherapy applications were included from 11 patients who were first treated with EBRT to the whole pelvis with a total prescribed dose of 50 Gy in 25 fractions. During each application, a PTW 9112 probe rectal probe having a series of five semiconductor diodes (R1 to R5) was inserted into the patient's rectum and a CT-based HDR ICBT application with a prescribed dose per fraction of 7 or 7.5 Gy to HRCTV was performed. Measurements were carried in water phantom using PTW rectal and universal adaptor plugs. Doses measured in phantom and with patients were compared to those calculated by the treatment planning system. RESULTS: The mean percentage dose difference ΔD (%) between calculated and measured values from phantom study were -5.29%, 1.89%, -2.72%, -4.76, and 0.72% for R1, R2, R3, R4, and R3 diodes, respectively and the overall mean ΔD (%) value with standard deviation (SD) was -2.03%±9.6%. From the patient study, a ΔD (%) that ranged from -19.5% to 24.0%, which corresponded to dose disparities between -0.77 Gy and 0.66 Gy. The median ΔD (%) ranged from 0.4% to 1.3%, or -0.03 to 0.05 Gy, respectively. ΔD (%) values exceeded 10% in approximately 26.4% of measurements (29 out of 110 in 22 applications). The location of Rmax in computed and measured values differs in 5 of 22 applications might be due to possible displacement of rectal probe between simulation and treatment. CONCLUSION: Despite the likely geometrical shift of measuring detectors between insertion and treatment, in-vivo dosimetry is feasible and can be used to estimate the dose to the rectum during HDR ICBT.

Expression analysis and function of mitochondrial genome-encoded microRNAs.

MicroRNAs (miRNAs) play a significant role in nuclear and mitochondrial anterograde and retrograde signaling. Most of the miRNAs found inside mitochondria are encoded in the nuclear genome, with a few mitochondrial genome-encoded non-coding RNAs having been reported. In this study, we have identified 13 mitochondrial genome-encoded microRNAs (mitomiRs), which were differentially expressed in breast cancer cell lines (MCF-7, MDA-MB-468 and MDA-MB-231), non-malignant breast epithelial cell line (MCF-10A), and normal and breast cancer tissue specimens. We found that mitochondrial DNA (mtDNA) depletion and inhibition of mitochondrial transcription led to reduced expression of mitomiRs in breast cancer cells. MitomiRs physically interacted with Ago2, an RNA-induced silencing complex (RISC) protein, in the cytoplasm and inside mitochondria. MitomiRs regulate the expression of both nuclear and mitochondrial transcripts in breast cancer cells. We showed that mitomiR-5 targets the PPARGC1A gene and regulates mtDNA copy number in breast cancer cells. MitomiRs identified in the present study may be a promising tool for expression and functional analysis in patients with a defective mitochondrial phenotype, including cancer and metabolic syndromes. This article has an associated First Person interview with the first author of the paper.

LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images.

PURPOSE: Liver cancer is one of the most common types of cancers in Asia with a high mortality rate. A common method for liver cancer diagnosis is the manual examination of histopathology images. Due to its laborious nature, we focus on alternate deep learning methods for automatic diagnosis, providing significant advantages over manual methods. In this paper, we propose a novel deep learning framework to perform multi-class cancer classification of liver hepatocellular carcinoma (HCC) tumor histopathology images which shows improvements in inference speed and classification quality over other competitive methods. METHOD: The BreastNet architecture proposed by Togacar et al. shows great promise in using convolutional block attention modules (CBAM) for effective cancer classification in H&E stained breast histopathology images. As part of our experiments with this framework, we have studied the addition of atrous spatial pyramid pooling (ASPP) blocks to effectively capture multi-scale features in H&E stained liver histopathology data. We classify liver histopathology data into four classes, namely the non-cancerous class, low sub-type liver HCC tumor, medium sub-type liver HCC tumor, and high sub-type liver HCC tumor. To prove the robustness and efficacy of our models, we have shown results for two liver histopathology datasets-a novel KMC dataset and the TCGA dataset. RESULTS: Our proposed architecture outperforms state-of-the-art architectures for multi-class cancer classification of HCC histopathology images, not just in terms of quality of classification, but also in computational efficiency on the novel proposed KMC liver data and the publicly available TCGA-LIHC dataset. We have considered precision, recall, F1-score, intersection over union (IoU), accuracy, number of parameters, and FLOPs as metrics for comparison. The results of our meticulous experiments have shown improved classification performance along with added efficiency. LiverNet has been observed to outperform all other frameworks in all metrics under comparison with an approximate improvement of [Formula: see text] in accuracy and F1-score on the KMC and TCGA-LIHC datasets. CONCLUSION: To the best of our knowledge, our work is among the first to provide concrete proof and demonstrate results for a successful deep learning architecture to handle multi-class HCC histopathology image classification among various sub-types of liver HCC tumor. Our method shows a high accuracy of [Formula: see text] on the proposed KMC liver dataset requiring only 0.5739 million parameters and 1.1934 million floating point operations per second.

Fabrication and development of a thorax phantom to evaluate 3D CRT treatment planning techniques for post-mastectomy chest wall radiotherapy.

The aim of this study was to design and fabricate a thorax phantom to quantify the radiation doses to the region of the chest wall (with 3 ionization chambers), the organ at risk (OAR) (lung), and the surface using radiochromic films (EBT3) for three different 3D CRT treatment planning techniques. Anthropomorphic phantoms are one of the best tools for verifying the quality of the radiotherapy treatment plans generated by treatment planning systems since they can provide equivalent human tissue densities. Thirty acrylic plates were cut into ellipses 21 cm in height and 31 cm in width, and slots were created to insert lung equivalent cork material and bone equivalent Teflon material. Three treatment planning techniques were designed: (A) tangential pair beams, (B) tangential pair beams with wedges and (C) tangential beams followed by an anterior oblique beam. The percentage difference between the measured point doses and the calculated doses (measured with three CC13 ionization chambers) ranged from - 3.2 to 1.6%, with a mean deviation of - 1.04 ± 1.3%. The measured mean percentage doses on the target surface with EBT3 film were 90.3% and 95.1% of the prescribed dose with 5-mm and 10-mm boluses, respectively. Finally, the average absolute dose difference between the measured and calculated surface doses was within 10 cGy in all three planning techniques. The developed thorax phantom is suitable for point dose measurements using ionization chambers and for surface dose measurements using EBT3 Gafchromic films in post-mastectomy chest wall radiotherapy.

Effect of domperidone, ondansetron, olanzapine-containing antiemetic regimen on QTC interval in patients with malignancy: a prospective, observational, single-group, assessor-blinded study.

Domperidone, ondansetron and olanzapine can prolong the QT interval. The clinical use of combinations of these drugs is not uncommon. Our study aimed to determine the presence of any QTc prolonging effect of the combination when used as antiemetic in patients receiving cancer chemotherapy. We carried out a prospective, observational study of patients with malignancy who were to receive domperidone, ondansetron and olanzapine-containing antiemetic regimen. Electrocardiograms were recorded before and during the administration of antiemetics, for three consecutive days. A blinded assessor determined the QTc interval using Bazett and Fridericia formulae. Thirty-six patients completed the study; 23 (63.9%) were females. There was a statistically significant change in QTc with time (Fridericia, χ2(4) = 15.629, p = 0.004; Bazett, χ2(4) = 15.910, p = 0.003); QTc on Day 1 was more than that during baseline (p < 0.001); these differences were significant in females (Fridericia, χ2(4) = 13.753, p = 0.008; Bazett, χ2 (4) = 13.278, p = 0.010) but not in males (Fridericia, χ2 (4) = 4.419, p = 0.352; Bazett, χ2(4) = 4.280, p = 0.369). Two female patients had an absolute QTc prolongation (Bazett correction) of > 500 ms. However, no clinically significant adverse events occurred. The findings show that QTc prolongation is a concern with olanzapine alone and in combination with domperidone and ondansetron, and needs to be investigated further.

Randomized control trial evidence for the benefits of massage and relaxation therapy on sleep in cancer survivors-a systematic review.

PURPOSE: Cancer survivors may experience sleep disturbances during and after their cancer treatments. While pharmacological approaches are commonly used to address sleep disturbances, they may have a number of adverse effects. This review studied the effect of two non-pharmacological interventions (massage and relaxation therapy) on sleep disturbances in cancer survivors. METHODS: A search for randomised controlled trials (RCTs) was conducted on PubMed, Scopus, Web of Science, PEDro, and CINAHL using relevant keywords. RESULTS: The search yielded 371 articles, with 4 RCTs studying massage therapy and 3 RCTs studying relaxation therapy included for qualitative analysis. Massage therapy studies showed statistically significant improvement in self-reported sleep questionnaires and objectively recorded long sleep episodes, as assessed via an accelerometer. No significant improvements in sleep outcomes were observed in the relaxation therapy studies, although there were trends for improved self-reported sleep quality. CONCLUSION: While massage therapy provided by massage therapists may have some potential for improving sleep outcomes for cancer survivors, there is no such current evidence regarding relaxation therapy. IMPLICATIONS FOR CANCER SURVIVORS: Cancer survivors who experience sleep disturbances may benefit from regular sessions with a massage therapist. However, future studies should examine the long-term feasibility of massage therapist-delivered services, particularly for cancer survivors with limited finances, and determine if benefits can be obtained if massage is provided by non-certified individuals. Relaxation therapy appears to be safe for cancer survivors, but future RCTs involving larger sample sizes need to be conducted to better determine its feasibility and efficacy.

Drug-drug interactions in patients undergoing chemoradiotherapy and the impact of an expert team intervention.

Background Several studies have examined the drug-drug interaction patterns in different patient populations and treatment settings; however, there is a need, particularly in the field of oncology and radiotherapy, for evaluating methods targeted towards preventing potential drug-drug interactions. One of the measures proposed is identifying potential interactions using computer programs and their evaluation by pharmacologists or clinical pharmacists, thereby providing clinically relevant information to the treating physician regarding the required prescription changes. Objective To determine the prevalence of potential drug-drug interactions in patients receiving chemoradiotherapy and assess the usefulness of expert team recommendations in minimizing interactions. Setting Patients admitted to the radiotherapy and oncology ward of a tertiary care teaching hospital in Karnataka, India. Method We conducted a prospective, cross-sectional study of prescriptions written for patients receiving chemoradiotherapy. Prescriptions containing two or more drugs, at least one of the drugs being an anticancer drug, were analyzed. They were screened for potential drug-drug interactions using the Lexicomp® drug interaction software. The interactions were classified as X, drug combination to be avoided; D, modification of therapy to be considered; and C, therapy to be monitored, as per the Lexicomp criteria. Main outcome measure The number of drug-drug interactions detected that were accepted by the treating radio-oncologist as requiring prescription change before and after the prescription review by an expert team. Results Two hundred twenty-three prescriptions were screened for the presence of drug-drug interactions; 106 prescriptions (47.53%) containing 620 drugs and 211 drug-drug interactions were identified. Of the 211 interactions identified, 6.64% (14/211), 18.48% (39/211), and 74.88% (158/211) drug-drug interactions belonged to category X, D, and C, respectively. Twenty-seven (50.94%) of the 53 category X and D interactions identified were accepted the oncologist as requiring a change in the prescription; an additional 13 (24.53%) interactions were identified as significant by the expert team, and 11 (84.62%) of these were accepted by the oncologist. Conclusion A system of alerting the treating physician to a potential drug-drug interaction leads to avoidance of prescription of the interacting drug combination, and the assistance by an expert team adds significantly to avoidance of clinically relevant drug interactions.

Effectiveness of exercise-based rehabilitation on functional capacity and quality of life in head and neck cancer patients receiving chemo-radiotherapy.

PURPOSE: Fatigue, decreased functionality, and impaired quality of life are some of the most common adverse outcomes of chemo-radiotherapy (CRT). Head and neck cancers (HNC) affect more than half a million individuals globally and its treatment takes a heavy toll on the patient, often affecting their speech, swallowing, and respiratory functions, and as a result they often develop fatigue, depression, and physical inactivity. The purpose of this study was to evaluate the effectiveness of exercise-based rehabilitation on functional capacity, quality of life, fatigue, hemoglobin, and platelet counts in patients with HNC on CRT. PATIENTS AND METHODS: A randomized controlled trial was conducted on 148 patients with head and neck cancer undergoing CRT to evaluate the effectiveness of exercise on functional capacity measured by the 6-min walk test, quality of life measured by the Medical Outcomes Survey Short Form 36 v2 questionnaire, fatigue by the NCCN (0-10) scale, hemoglobin, and platelets. The control group received standard physical activity recommendations while the exercise group received a structured exercise program of aerobic and active resistance exercises for a period of 11 weeks. RESULTS: There was a significant improvement in the functional capacity (p < 0.001), quality of life (p < 0.001), and prevention of worsening of fatigue (p < 0.001) in the exercise group. The blood parameters did not show a significant difference between the control group and the exercise group. CONCLUSION: Our results elucidate that an 11-week structured exercise program for HNC patients receiving CRT helps in improving their functional capacity and quality of life. It also prevents deterioration of fatigue levels in the exercise group.