Effect of Sacubitril/Valsartan on Patients Having Heart Failure With Preserved Left Ventricular Ejection Fraction Undergoing Hemodialysis: A Long-term Observational Study

BACKGROUND/AIM

Sacubitril/valsartan (SV), a novel pharmacological class of angiotensin receptor neprilysin inhibitors, is effective in treating heart failure (HF) by inhibiting the degradation of natriuretic peptides and the renin-angiotensin-aldosterone system. However, no studies have observed the long-term effects of SV on patients with HF and preserved left ventricular ejection fraction (LVEF) undergoing hemodialysis (HD) over a long period.

PATIENTS AND METHODS

This single-center retrospective study of 21 months duration involved consecutive patients with HF and preserved LVEF undergoing HD, who received 50-200 mg/day. All patients were followed up regularly, and clinical, biochemical, and echocardiographic parameters were recorded at baseline and during follow-up. The efficacy and safety of SV were also analyzed.

RESULTS

This longitudinal study included nine patients, with a median age of 76 years. The median HD duration was 7 years. At baseline, the mean brain natriuretic peptide (BNP) was 133±73.6 pg/ml and that of LVEF was 66%±9%. After SV therapy, the systolic blood pressure, diastolic blood pressure, and heart rate decreased, albeit without statistical significance. BNP levels, LVEF, left atrial anteroposterior dimension, and left ventricular mass index did not change, compared to baseline values. No adverse effects were observed in any of the patients.

CONCLUSION

SV tended to decrease blood pressure and heart rate in patients with HF and preserved LVEF undergoing HD but did not alter cardiac function assessments, such as BNP or echocardiography.

Development and Validation of a Preoperative Nomogram for Endoscopic Management Decision Making in Upper Urinary Tract Urothelial Carcinoma

OBJECTIVE

We aimed to develop and validate a preoperative nomogram that predicts low-grade, non-muscle invasive upper urinary tract urothelial carcinoma (LG-NMI UTUC), thereby aiding in the accurate selection of endoscopic management (EM) candidates.

METHODS

This was a retrospective study that included 454 patients who underwent radical surgery (Cohort 1 and Cohort 2), and 26 patients who received EM (Cohort 3). Utilizing a multivariate logistic regression model, a nomogram predicting LG-NMI UTUC was developed based on data from Cohort 1. The nomogram's accuracy was compared with conventional European Association of Urology (EAU) and National Comprehensive Cancer Network (NCCN) models. External validation was performed using Cohort 2 data, and the nomogram's prognostic value was evaluated via disease progression metrics in Cohort 3.

RESULTS

In Cohort 1, multivariate analyses highlighted the absence of invasive disease on imaging (odds ratio [OR] 7.04; p = 0.011), absence of hydronephrosis (OR 2.06; p = 0.027), papillary architecture (OR 24.9; p < 0.001), and lack of high-grade urine cytology (OR 0.22; p < 0.001) as independent predictive factors for LG-NMI disease. The nomogram outperformed the two conventional models in predictive accuracy (0.869 vs. 0.759-0.821) and exhibited a higher net benefit in decision curve analysis. The model's clinical efficacy was corroborated in Cohort 2. Moreover, the nomogram stratified disease progression-free survival rates in Cohort 3.

CONCLUSION

Our nomogram ( https://kmur.shinyapps.io/UTUC_URS/ ) accurately predicts LG-NMI UTUC, thereby identifying suitable candidates for EM. Additionally, the model serves as a useful tool for prognostic stratification in patients undergoing EM.

Re-salvage focal low-dose rate brachytherapy for local recurrence of prostate cancer after salvage focal low-dose rate brachytherapy

Introduction

Salvage brachytherapy represents an effective treatment for local recurrence of prostate cancer after prior external beam radiotherapy. However, the optimal therapeutic strategies for local recurrence after salvage brachytherapy have not yet been determined.

Case presentation

We describe the case of a 77-year-old man who underwent re-salvage focal low-dose rate brachytherapy for local recurrence after carbon ion radiotherapy and salvage focal low-dose rate brachytherapy. We performed re-salvage focal low-dose rate brachytherapy for the recurrence with a different type of seed, which resulted in a significant reduction in the prostate-specific antigen level. During the 35-month follow-up after re-salvage focal low-dose rate brachytherapy, no recurrence of prostate cancer and no severe radiation-related toxicities were observed.

Conclusion

Our patient was successfully treated with re-salvage focal low-dose rate brachytherapy for local recurrence after salvage focal low-dose rate brachytherapy. This treatment strategy might be effective for such patients and is not associated with sexual dysfunction or severe adverse events.

Cone-beam computed-tomography-based delta-radiomic analysis for investigating prognostic power for esophageal squamous cell cancer patients undergoing concurrent chemoradiotherapy

PURPOSE

To investigate the prognostic power of cone-beam computed-tomography (CBCT)-based delta-radiomics in esophageal squamous cell cancer (ESCC) patients treated with concurrent chemoradiotherapy (CCRT).

METHODS

We collected data from 26 ESCC patients treated with CCRT. CBCT images acquired at five time points (1st-5th week) per patient during CCRT were used in this study. Radiomic features were extracted from the five CBCT images on the gross tumor volumes. Then, 17 delta-radiomic feature sets derived from five types of calculations were obtained for all the cases. Leave-one-out cross-validation was applied to investigate the prognostic power of CBCT-based delta-radiomic features. Feature selection and construction of a prediction model using Coxnet were performed using training samples. Then, the test sample was classified into high or low risk in each cross-validation fold. Survival analysis for the two groups were performed to evaluate the prognostic power of the extracted CBCT-based delta-radiomic features.

RESULTS

Four delta-radiomic feature sets indicated significant differences between the high- and low-risk groups (p < 0.05). The highest C-index in the 17 delta-radiomic feature sets was 0.821 (95 % confidence interval, 0.735-0.907). That feature set had p-value of the log-rank test and hazard ratio of 0.003 and 4.940 (95 % confidence interval, 1.391-17.544), respectively.

CONCLUSIONS

We investigated the potential of using CBCT-based delta-radiomics for prognosis of ESCC patients treated with CCRT. It was demonstrated that delta-radiomic feature sets based on the absolute value of relative difference obtained from the early to the middle treatment stages have high prognostic power for ESCC.

Prognostic value of radiomic features in patients with esophageal cancer treated with chemoradiotherapy

BACKGROUND

The aim of the present study was to evaluate the prognostic value of radiomic features in patients who underwent chemoradiotherapy for esophageal cancer.

METHODS

In this retrospective study, two independent cohorts of esophageal cancer patients treated with chemoradiotherapy were included. Radiomics features of each patient were extracted from pre-treatment computed tomography (CT) images. Radiomic features were selected by employing univariate and multivariate analyses in the test cohort. Selected radiomic features were verified in the validation cohort. The endpoint of the present study was overall survival.

RESULTS

A total of 101 esophageal cancer patients were included in our study, with 71 patients in the test cohort and 30 patients in the validation cohort. Univariate analysis identified 158 radiomic features as prognostic factors for overall survival in the test cohort. A multivariate analysis revealed that root mean squared and Low-High-High (LHH) median were prognostic factors for overall survival with a hazard ratio of 2.23 (95% confidence interval [CI]: 1.16-4.70, P = 0.017) and 0.26 (95% CI: 0.13-0.54, P < 0.001), respectively. In the validation cohort, root mean squared high/LHH median low group had the most preferable prognosis with a median overall survival of 73.30 months (95% CI: 32.13-NA), whereas root mean squared low/LHH median low group had the poorest prognosis with a median overall survival of 9.72 months (95% CI: 2.50-NA), with a P value of < 0.001.

CONCLUSIONS

We identified two radiomic features that might be independent prognostic factors of overall survival of esophageal cancer patients treated with chemoradiotherapy.

Effects of Oral Semaglutide on Renal Function in Diabetic Kidney Disease: A Short-term Clinical Study

BACKGROUND/AIM

In the SUSTAIN-6 trial, semaglutide reduced the risk of worsening nephropathy in patients with type 2 diabetes. The objective of this retrospective study was to elucidate the effect and safety of oral semaglutide (Rybelsus®) in patients with diabetic kidney disease (DKD).

PATIENTS AND METHODS

Six patients with DKD received 3 mg/day semaglutide orally. The observation period was 9.0±5.0 months. Changes in estimated glomerular filtration rate (eGFR), urinary protein, fasting blood glucose, and hemoglobin A1c were studied from 6 months before the administration of oral semaglutide until 6 months after administration.

RESULTS

The change in eGFR over the 6 months prior to semaglutide administration was -1.2±1.6 ml/min/1.73 m2, showing a trend for a decrease; although not statistically significant, the change at 6 months after oral semaglutide initiation showed improved eGFR (1-50.7±1.8 ml/min/1.73 m2). Proteinuria was not reduced after treatment with oral semaglutide. No significant adverse effects (including retinopathy) were observed in any patient during the study.

CONCLUSION

Despite the small sample size and short observation period, oral semaglutide was found to be a relatively well-tolerated drug for patients with DKD.

Hypoxia-inducible factor 2α protein and mRNA expression correlate with histomorphological features in clear cell renal cell carcinoma

Hypoxia-inducible factor 2α (HIF2α) has been identified as a potential biomarker and novel target for systemic therapy in clear cell renal cell carcinoma (ccRCC). The present study aims to evaluate the association of HIF2α protein and HIF2A mRNA expression with clinicopathological factors and histomorphological features related to vasculature and inflammation of ccRCC using a localized ccRCC cohort (n = 428) and The Cancer Genome Atlas (TCGA)-KIRC cohort (n = 433). HIF2α protein expression was immunohistochemically assessed using tissue microarrays and HIF2A mRNA expression was assessed using the TCGA RNA-sequencing data. Positive HIF2α protein and high HIF2A mRNA expression were observed in 145 (33.9 %) and 142 (32.8 %) patients, respectively. Positive nuclear HIF2α protein expression was significantly associated with the clear histological phenotype and architectural patterns related to rich vascular networks (p < 0.001), and no tumor-associated immune cells status (p < 0.05) in addition to favorable prognostic factors such as lower TNM stage, lower WHO/ISUP grade, or the absence of necrosis (p < 0.001). The HIF2A mRNA expression profile by the TCGA cohort showed similar trends as the HIF2α protein profile. In addition, positive HIF2α protein and high HIF2A mRNA expression were associated with higher recurrence-free survival and overall survival, respectively (both p < 0.001). In conclusion, we comprehensively demonstrated the association of HIF2α profiles with clinicopathological factors and histomorphological features related to vasculature and inflammation at both protein and mRNA levels. Histomorphological features expressing HIF2α may provide information on HIF2α targeted therapeutic response as well as prognosis in ccRCC patients.

Effect of finerenone on diabetic kidney disease outcomes with estimated glomerular filtration rate below 25 mL/min/1.73 m2

Background

In the Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease trial, finerenone reduced the risk of cardiovascular events in patients with chronic kidney disease (CKD) and type 2 diabetes, while in the Finerenone in Reducing Kidney Failure and Disease Progression in Diabetic Kidney Disease trial, it improved renal and cardiovascular outcomes in patients with advanced CKD. However, no previous studies have assessed patients with CKD and type 2 diabetes with an estimated glomerular filtration rate (eGFR) below 25 mL/min/1.73 m².

Methods

Nine patients with CKD and type 2 diabetes who received finerenone 10 mg/day were analyzed retrospectively. Changes in eGFR, urinary protein, and serum potassium levels were studied from 1 year before administration of finerenone until 6 months after administration.

Results

The mean baseline eGFR slope was -7.63 ± 9.84 (mL/min/1.73 m²/year). After finerenone treatment, the mean eGFR slope significantly improved -1.44 ± 3.17 (mL/min/1.73 m²/6 months, P=0.038). However, finerenone treatment did not significantly reduce proteinuria. Furthermore, finerenone did not increase serum potassium levels.

Conclusions

Patients treated with finerenone showed a significantly slower decline in eGFR. Furthermore, aside from the present study, no reports have indicated the effectiveness of finerenone in patients with advanced CKD with an eGFR below 25 mL/min/1.73 m². As confirmed in our clinical trials, the finding that finerenone is effective in a wide range of renal functions can be generalized to clinical practice. However, sample size in this study was small. Thus, further large-scale investigations will be needed.

Learning from the past and present to change the future: Endoscopic management of upper urinary tract urothelial carcinoma

Current guidelines recommend endoscopic management (EM) for patients with low-risk upper urinary tract urothelial carcinoma, as well as those with an imperative indication. However, regardless of the tumor risk, radical nephroureterectomy is still mainly performed worldwide despite the benefits of EM, such as renal function maintenance, no hemodialysis requirement, and treatment cost reduction. This might be explained by the association of EM with a high risk of local recurrence and progression. Furthermore, the need for rigorous patient selection and close surveillance following EM may be relevant. Nevertheless, recent developments in diagnostic modalities, pathological evaluation, surgical devices and techniques, and intracavitary regimens have been reported, which may contribute to improved risk stratification and treatments with superior oncological outcomes. In this review, considering recent advances in endourology and oncology, we propose novel treatment strategies for optimal EM.

Deep learning-based predictions of clear and eosinophilic phenotypes in clear cell renal cell carcinoma

We have recently shown that histological phenotypes focusing on clear and eosinophilic cytoplasm in clear cell renal cell carcinoma (ccRCC) correlated with prognosis and the response to angiogenesis inhibition and checkpoint blockade. This study aims to objectively show the diagnostic utility of clear or eosinophilic phenotypes of ccRCC by developing an artificial intelligence (AI) model using the TCGA-ccRCC dataset and to demonstrate if the clear or eosinophilic predicted phenotypes correlate with pathological factors and gene signatures associated with angiogenesis and cancer immunity. Before the development of the AI model, histological evaluation using hematoxylin and eosin whole-slide images of the TCGA-ccRCC cohort (n = 435) was performed by a urologic pathologist. The AI model was developed as follows. First, the highest-grade area on each whole slide image was captured for image processing. Second, the selected regions were cropped into tiles. Third, the AI model was trained using transfer learning on a deep convolutional neural network, and clear or eosinophilic predictions were scaled as AI scores. Next, we verified the AI model using a validation cohort (n = 95). Finally, we evaluated the accuracy of the prognostic predictions of the AI model and revealed that the AI model detected clear and eosinophilic phenotypes with high accuracy. The AI model stratified the patients' outcomes, and the predicted eosinophilic phenotypes correlated with adverse clinicopathological characteristics and high immune-related gene signatures. In conclusion, the AI-based histologic subclassification accurately predicted clear or eosinophilic phenotypes of ccRCC, allowing for consistently reproducible stratification for prognostic and therapeutic stratification.

MRI-Based Radiomics Differentiates Skull Base Chordoma and Chondrosarcoma: A Preliminary Study

Simple Summary

In this study, we created a novel MRI-based machine learning model to differentiate skull base chordoma and chondrosarcoma with multiparametric signatures. While these tumors share common radiographic characteristics, clinical behavior is distinct. Therefore, distinguishing these tumors before initial surgical intervention would be useful, potentially impacting the surgical strategy. Although there are some limitations, such as the risk of overfitting and the lack of an extramural cohort for truly independent final validation, our machine learning model distinguishing chordoma from chondrosarcoma yielded superior diagnostic accuracy to that achieved by 20 board-certified neurosurgeons.

Abstract

Chordoma and chondrosarcoma share common radiographic characteristics yet are distinct clinically. A radiomic machine learning model differentiating these tumors preoperatively would help plan surgery. MR images were acquired from 57 consecutive patients with chordoma (N = 32) or chondrosarcoma (N = 25) treated at the University of Tokyo Hospital between September 2012 and February 2020. Preoperative T1-weighted images with gadolinium enhancement (GdT1) and T2-weighted images were analyzed. Datasets from the first 47 cases were used for model creation, and those from the subsequent 10 cases were used for validation. Feature extraction was performed semi-automatically, and 2438 features were obtained per image sequence. Machine learning models with logistic regression and a support vector machine were created. The model with the highest accuracy incorporated seven features extracted from GdT1 in the logistic regression. The average area under the curve was 0.93 ± 0.06, and accuracy was 0.90 (9/10) in the validation dataset. The same validation dataset was assessed by 20 board-certified neurosurgeons. Diagnostic accuracy ranged from 0.50 to 0.80 (median 0.60, 95% confidence interval 0.60 ± 0.06%), which was inferior to that of the machine learning model (p = 0.03), although there are some limitations, such as the risk of overfitting and the lack of an extramural cohort for truly independent final validation. In summary, we created a novel MRI-based machine learning model to differentiate skull base chordoma and chondrosarcoma from multiparametric signatures.

Training of deep cross-modality conversion models with a small dataset, and their application in megavoltage CT to kilovoltage CT conversion

PURPOSE

In recent years, deep-learning-based image processing has emerged as a valuable tool for medical imaging owing to its high performance. However, the quality of deep-learning-based methods heavily relies on the amount of training data; the high cost of acquiring a large dataset is a limitation to their utilization in medical fields. Herein, based on deep learning, we developed a computed tomography (CT) modality conversion method requiring only a few unsupervised images.

METHODS

The proposed method is based on CycleGAN with several extensions tailored for CT images, which aims at preserving the structure in the processed images and reducing the amount of training data. This method was applied to realize the conversion of megavoltage computed tomography (MVCT) to kilovoltage computed tomography (kVCT) images. Training was conducted using several datasets acquired from patients with head and neck cancer. The size of the datasets ranged from 16 slices (two patients) to 2745 slices (137 patients) for MVCT and 2824 slices (98 patients) for kVCT.

RESULTS

The required size of the training data was found to be as small as a few hundred slices. By statistical and visual evaluations, the quality improvement and structure preservation of the MVCT images converted by the proposed model were investigated. As a clinical benefit, it was observed by medical doctors that the converted images enhanced the precision of contouring.

CONCLUSIONS

We developed an MVCT to kVCT conversion model based on deep learning, which can be trained using only a few hundred unpaired images. The stability of the model against changes in data size was demonstrated. This study promotes the reliable use of deep learning in clinical medicine by partially answering commonly asked questions, such as "Is our data sufficient?" and "How much data should we acquire?" This article is protected by copyright. All rights reserved.

Fast Statistical Iterative Reconstruction for Mega-voltage Computed Tomography

Statistical iterative reconstruction is expected to improve the image quality of computed tomography (CT). However, one of the challenges of iterative reconstruction is its large computational cost. The purpose of this review is to summarize a fast iterative reconstruction algorithm by optimizing reconstruction parameters. Megavolt projection data was acquired from a TomoTherapy system and reconstructed using in-house statistical iterative reconstruction algorithm. Total variation was used as the regularization term and the weight of the regularization term was determined by evaluating signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and visual assessment of spatial resolution using Gammex and Cheese phantoms. Gradient decent with an adaptive convergence parameter, ordered subset expectation maximization (OSEM), and CPU/GPU parallelization were applied in order to accelerate the present reconstruction algorithm. The SNR and CNR of the iterative reconstruction were several times better than that of filtered back projection (FBP). The GPU parallelization code combined with the OSEM algorithm reconstructed an image several hundred times faster than a CPU calculation. With 500 iterations, which provided good convergence, our method produced a 512 × 512 pixel image within a few seconds. The image quality of the present algorithm was much better than that of FBP for patient data. J. Med. Invest. 67 : 30-39, February, 2020.

Visual enhancement of Cone-beam CT by use of CycleGAN

PURPOSE

Cone-beam computed tomography (CBCT) offers advantages over conventional fan-beam CT in that it requires a shorter time and less exposure to obtain images. However, CBCT images suffer from low soft-tissue contrast, noise, and artifacts compared to conventional fan-beam CT images. Therefore, it is essential to improve the image quality of CBCT.

METHODS

In this paper, we propose a synthetic approach to translate CBCT images with deep neural networks. Our method requires only unpaired and unaligned CBCT images and planning fan-beam CT (PlanCT) images for training. The CBCT images and PlanCT images may be obtained from other patients as long as they are acquired with the same scanner settings. Once trained, three-dimensionally reconstructed CBCT images can be directly translated into high-quality PlanCT-like images.

RESULTS

We demonstrate the effectiveness of our method with images obtained from 20 prostate patients, and provide a statistical and visual comparison. The image quality of the translated images shows substantial improvement in voxel values, spatial uniformity, and artifact suppression compared to those of the original CBCT. The anatomical structures of the original CBCT images were also well preserved in the translated images.

CONCLUSIONS

Our method produces visually PlanCT-like images from CBCT images while preserving anatomical structures.

[Improvement in Image Quality of CBCT during Treatment by Cycle Generative Adversarial Network]

PURPOSE

Volumetric modulated arc therapy (VMAT) can acquire projection images during rotational irradiation, and cone-beam computed tomography (CBCT) images during VMAT delivery can be reconstructed. The poor quality of CBCT images prevents accurate recognition of organ position during the treatment. The purpose of this study was to improve the image quality of CBCT during the treatment by cycle generative adversarial network (CycleGAN).

METHOD

Twenty patients with clinically localized prostate cancer were treated with VMAT, and projection images for intra-treatment CBCT (iCBCT) were acquired. Synthesis of PCT (SynPCT) with improved image quality by CycleGAN requires only unpaired and unaligned iCBCT and planning CT (PCT) images for training. We performed visual and quantitative evaluation to compare iCBCT, SynPCT and PCT deformable image registration (DIR) to confirm the clinical usefulness.

RESULT

We demonstrated suitable CycleGAN networks and hyperparameters for SynPCT. The image quality of SynPCT improved visually and quantitatively while preserving anatomical structures of the original iCBCT. The undesirable deformation of PCT was reduced when SynPCT was used as its reference instead of iCBCT.

CONCLUSION

We have performed image synthesis with preservation of organ position by CycleGAN for iCBCT and confirmed the clinical usefulness.

Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis

We conducted a feasibility study to predict malignant glioma grades via radiomic analysis using contrast-enhanced T1-weighted magnetic resonance images (CE-T1WIs) and T2-weighted magnetic resonance images (T2WIs). We proposed a framework and applied it to CE-T1WIs and T2WIs (with tumor region data) acquired preoperatively from 157 patients with malignant glioma (grade III: 55, grade IV: 102) as the primary dataset and 67 patients with malignant glioma (grade III: 22, grade IV: 45) as the validation dataset. Radiomic features such as size/shape, intensity, histogram, and texture features were extracted from the tumor regions on the CE-T1WIs and T2WIs. The Wilcoxon-Mann-Whitney (WMW) test and least absolute shrinkage and selection operator logistic regression (LASSO-LR) were employed to select the radiomic features. Various machine learning (ML) algorithms were used to construct prediction models for the malignant glioma grades using the selected radiomic features. Leave-one-out cross-validation (LOOCV) was implemented to evaluate the performance of the prediction models in the primary dataset. The selected radiomic features for all folds in the LOOCV of the primary dataset were used to perform an independent validation. As evaluation indices, accuracies, sensitivities, specificities, and values for the area under receiver operating characteristic curve (or simply the area under the curve (AUC)) for all prediction models were calculated. The mean AUC value for all prediction models constructed by the ML algorithms in the LOOCV of the primary dataset was 0.902 ± 0.024 (95% CI (confidence interval), 0.873-0.932). In the independent validation, the mean AUC value for all prediction models was 0.747 ± 0.034 (95% CI, 0.705-0.790). The results of this study suggest that the malignant glioma grades could be sufficiently and easily predicted by preparing the CE-T1WIs, T2WIs, and tumor delineations for each patient. Our proposed framework may be an effective tool for preoperatively grading malignant gliomas.

RARE-16. A NOVEL RADIOMICS MODEL DIFFERENTIATING CHORDOMA AND CHONDROSARCOMA

BACKGROUND

Chordoma and chondrosarcoma account for the majority of skull base tumors affecting the petroclival region. Chondrosarcoma has better prognosis than chordoma; heavy particle therapy is often indicated for residual/recurrent chordoma. Preoperative, precise diagnosis of the tumor would be desirable, as it can potentially impact on the choice of a surgical approach and the aggressiveness of surgery.

METHODS

We conducted a radiomics study to create a machine learning model distinguishing chondrosarcoma from chordoma. We collected DICOM T2-weighted images and T1-weighted images with gadolinium (GdT1) enhancement in the consective patients of chordoma or chondrosarcoma who underwent surgery at The University of Tokyo Hospital from September of 2012 to January of 2019. We selected patients with uniform MRI images. VOI (volume of interest) was set using Monaco (https://www.elekta.com/software-solutions/treatment-management/external-beam-planning/monaco.html). Not only sematic features but also agnostic features were calculated. The original images and 8 wavelet transformed images were calculated for texture agnostic features such as Gray-Level Co-occurrence Matrix (GLCM). Features were selected by recursive feature elimination (RFE). The final model evaluation was performed by average area under the curve (AUC).

RESULTS

The study population included 17 chordomas and 22 chondrosarcomas in a total of 39 patients. 476 features were obtained per image sequence. The number of features per case was 476 × 2 = 952 The most accurate machine learning model was created using the extracted three features from only T2. The best AUC was 0.77 ± 0.11 in logistic regression (dataset was divided randomly into halves, average value of AUC calculated six times).

CONCLUSIONS

This novel machine learning model can differentiate chordoma and chondrosarcoma reasonably well. A validation study with a larger number of patients is warranted.

NIMG-11. VISUALIZATION OF JUDGMENT BASIS OF CNN TO GRADING GLIOMA

BACKGROUND

convolutional neural network (CNN) model using MRI imaging are likely to be effective for grading glioma. However, interpretation of the judgment basis of CNN is difficult. The purpose of this study is twofold. One is to create a high accuracy machine learning model that grading of glioma (Glioma grade II, between III and IV). The other is to visualize the judgment basis of the model.

METHODS

We targeted cases that were imaged at our Hospital during the period from August 2014 to January 2018. Five types of MRI are used. The five types are two types of DWI (b1000DWI and b2000DWI, respectively, with a value of 1000 and 2000), apparent diffusion coefficient (ADC), fractional anisotropy (FA), and mean kurtosis (MK). The images were input to CNN wtihout ROI. Seven types of CNN were prepared, and 100 epochs of learning were performed.

RESULTS

55 cases were included. There were 14 grade II, 12 grade III, and 29 grade IV). Of these, 44 cases up to July 2017 in chronological order were used as a dataset for learning, and 11 cases from August 2017 to January 2018 were taken as independent test dataset. The best results were obtained using MK as input, with a percentage of correct cases of test data of 0.82. Subsequently, we applied Grad-CAM to the model. Grad-CAM is visualized technique that shows where CNN focused on. The model focused on the tumor part of the image. In addition, in the cases of glioma and meningioma coexisting, grading was performed focusing on the glioma area not on meningioma area.

CONCLUSION

When grading glioma, it was considered that CNN decide glioma’s grade focusing on tumor part of the image, as well as humans.

[An Introduction to Radiomics: Toward a New Era of Precision Medicine]

Recently, in a medical field, quantitative data mining is a hot topic for performing a precision (or personalized) medicine. Although a molecular biological data has been mainly utilized for data mining in this field, medical images are also important minable data. Radiomics is a comprehensive analysis methodology for describing tumor phenotypes or molecular biological expressions (e.g. genotypes) using minable feature extracted from a large number of medical images. In this review paper, we introduce to a framework of the radiomics.

Cone Beam Computed Tomography Image Quality Improvement Using a Deep Convolutional Neural Network

Introduction

Cone beam computed tomography (CBCT) plays an important role in image-guided radiation therapy (IGRT), while having disadvantages of severe shading artifact caused by the reconstruction using scatter contaminated and truncated projections. The purpose of this study is to develop a deep convolutional neural network (DCNN) method for improving CBCT image quality.

Methods

CBCT and planning computed tomography (pCT) image pairs from 20 prostate cancer patients were selected. Subsequently, each pCT volume was pre-aligned to the corresponding CBCT volume by image registration, thereby leading to registered pCT data (pCT_r). Next, a 39-layer DCNN model was trained to learn a direct mapping from the CBCT to the corresponding pCT_r images. The trained model was applied to a new CBCT data set to obtain improved CBCT (i-CBCT) images. The resulting i-CBCT images were compared to pCT_r using the spatial non-uniformity (SNU), the peak-signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM).

Results

The image quality of the i-CBCT has shown a substantial improvement on spatial uniformity compared to that of the original CBCT, and a significant improvement on the PSNR and the SSIM compared to that of the original CBCT and the enhanced CBCT by the existing pCT-based correction method.

Conclusion

We have developed a DCNN method for improving CBCT image quality. The proposed method may be directly applicable to CBCT images acquired by any commercial CBCT scanner.

Volumetric and dosimetric comparison of organs at risk between the prone and supine positions in postoperative radiotherapy for prostate cancer

Background

The aim of this study was to evaluate the effects of patient positioning on the volume of organs at risk (OARs) in or near the planning target volume (PTV) and the dose distribution in adjuvant or salvage radiotherapy for prostate cancer after prostatectomy.

Methods

Seventeen patients who received intensity-modulated radiation therapy (66 Gy in 33 fractions) as adjuvant or salvage therapy after prostatectomy were evaluated. All patients underwent CT scans in both the prone (on a belly board) and supine positions. The target volumes and OARs were delineated on each CT series. The planning target volume (PTV) was extended in every direction to generate the PTV + 0.5 cm, PTV + 1 cm, PTV + 2 cm, PTV + 3 cm, and PTV + 4 cm values. The volumes of the OARs overlapping with the PTV and the extended target volumes in the prone and supine position were compared using the Wilcoxon signed-rank test. Dose-volume histogram (DVH) parameters in the prone and supine position were compared using the paired t-test.

Results

The mean overlapping volumes of the small intestine for each of the PTV values were as follows (prone position vs. supine position [mean ± SD]): PTV, 1.5 ± 5.5 cm³ vs. 7.9 ± 15.7 cm³ (P = 0.028); PTV + 0.5 cm, 2.6 ± 8.9 cm³ vs. 12.1 ± 22.6 cm³ (P = 0.028); PTV + 1 cm, 3.5 ± 11.4 cm³ vs. 17.1 ± 29.8 cm³ (P = 0.028); PTV + 2 cm, 5.6 ± 14.5 cm³ vs. 26.8 ± 46.9 cm³ (P = 0.028); and PTV + 3 cm, 9.0 ± 17.4 cm³ vs. 36.5 ± 63.2 cm³ (P = 0.019), respectively. Some of the overlapping volumes of the rectum and bladder were significantly smaller in the prone position. On the other hand, when the target volume was extended by ≥2 cm, the overlapping volumes of the femurs were significantly larger in the prone position. V15 of the rectum and mean dose and V65 of the bladder were significantly lower in the prone position.

Conclusions

This study indicated that the volumes of the small intestine, rectum, and bladder in or near the PTV decreased when the patient was placed in the prone position on a belly board in postoperative radiotherapy for prostate cancer. The dose distribution seemed superior in the prone position to the supine position.

Exploration of temporal stability and prognostic power of radiomic features based on electronic portal imaging device images

PURPOSE

We aimed to explore the temporal stability of radiomic features in the presence of tumor motion and the prognostic powers of temporally stable features.

METHODS

We selected single fraction dynamic electronic portal imaging device (EPID) (n = 275 frames) and static digitally reconstructed radiographs (DRRs) of 11 lung cancer patients, who received stereotactic body radiation therapy (SBRT) under free breathing. Forty-seven statistical radiomic features, which consisted of 14 histogram-based features and 33 texture features derived from the graylevel co-occurrence and graylevel run-length matrices, were computed. The temporal stability was assessed by using a multiplication of the intra-class correlation coefficients (ICCs) between features derived from the EPID and DRR images at three quantization levels. The prognostic powers of the features were investigated using a different database of lung cancer patients (n = 221) based on a Kaplan-Meier survival analysis.

RESULTS

Fifteen radiomic features were found to be temporally stable for various quantization levels. Among these features, seven features have shown potentials for prognostic prediction in lung cancer patients.

CONCLUSIONS

This study suggests a novel approach to select temporally stable radiomic features, which could hold prognostic powers in lung cancer patients.

The efficacy of the direct clinical intervention for infectious diseases by a pediatric infectious disease specialist in the pediatric ward of a tertiary medical facility without a pediatric antimicrobial stewardship program

Antimicrobial stewardship programs (ASPs) have been introduced in most hospital complexes; however, they are not always useful for pediatric patients. The aim of this study is to investigate the efficacy of direct clinical intervention for infectious diseases by a pediatric infectious disease specialist in a tertiary medical facility without pediatric ASP. This retrospective study included 1,821 patients who were hospitalized in the pediatric ward of a large metropolitan hospital from 2010 to 2015. The clinical course, the use of intravenous antimicrobial agents and the results of a microbiological analysis were compared between the period after the beginning of direct intervention by the specialist (post-intervention period) and the previous period (pre-intervention period). In the post-intervention period, the proportion of the patients who received intravenous antimicrobial agents, the number of antimicrobial agents used for each episode, and the proportion of episodes in which an antimicrobial agent was re-administrated were significantly lower (P = 0.006, P = 0.004, P = 0.036, respectively), and the duration of antimicrobial treatment was significantly shorter (P < 0.001). In addition, narrower spectrum antimicrobial agents were used, and the incidence of meropenem-sensitive Pseudomonas aeruginosa significantly increased (P = 0.037) in the post-intervention period. There was no change of mortality between the two periods. Direct clinical intervention by a pediatric infectious diseases specialist is useful for the treatment of infectious diseases in the pediatric ward of a tertiary medical facility without a pediatric ASP. The creation of a pediatric ASP is recommended in hospital complexes.

Comparison of Cosmesis and Body Image After Laparoendoscopic Single-Site Versus Conventional Laparoscopic Donor Nephrectomy

BACKGROUND

This study used a questionnaire to objectively assess the body image of donors who underwent conventional laparoscopic donor nephrectomy (L-DN) or laparoscopic single-site donor nephrectomy (LESS-DN). Surgical outcomes were compared between the two groups.

METHODS

Twenty patients underwent L-DN and 20 underwent LESS-DN. The postoperative outcomes of the two approaches were retrospectively compared and evaluated for differences in cosmesis and body image. The questionnaire comprised a body image questionnaire, including a body image scale (BIS) and cosmetic scale (CS), and a photo-series questionnaire (PSQ). A higher score indicated a more favorable assessment. Pain was assessed by comparing the number of times an analgesic was administered during hospitalization.

RESULTS

There were no significant differences in operative outcomes between L-DN and LESS-DN. The average BIS score (maximum possible, 20 points) was 18.5 points for patients who underwent L-DN and 19.5 points for patients who underwent LESS-DN (P = .025). Patients who underwent L-DN had a median CS score (maximum possible, 24 points) of 17.5 points, whereas patients who underwent LESS-DN had a median CS score of 19.0 points (P = .113). The average PSQ score was 7.1 points for patients who underwent L-DN and 8.8 points for patients who underwent LESS-DN (P = .01). Patients who underwent LESS-DN were administered an analgesic was significantly number of times less than patients who underwent DN (P = .01).

CONCLUSIONS

LESS-DN results in a better body image and better cosmetic appearance than does L-DN, indicating the clinical usefulness of LESS-DN.

Detection of Vascular Disease Risk in Women by Panoramic Radiography

Low bone mineral density and rapid bone loss of the skeleton are associated with mortality risk from vascular diseases in post-menopausal women. Panoramic radiographic measurements are considered as indicators of skeletal bone mineral density or bone turnover. We hypothesize that such measurements may be associated with vascular disease risk in post-menopausal women. Associations of mandibular cortical shape and width on panoramic radiographs with skeletal bone mineral density and risk factors related to vascular diseases were investigated in 87 post-menopausal women. Cortical shape was associated with skeletal bone mineral density, low-density lipoprotein cholesterol, apolipoprotein B, resting heart rate, and endothelial dysfunction. Cortical width was associated with skeletal bone mineral density, low-density lipoprotein cholesterol, and apolipoprotein A1. Dentists may be able to refer women with increased risk of vascular diseases, as well as low bone mineral density, to medical professionals for further examination by panoramic findings.

Applications of Machine Learning for Radiation Therapy

Radiation therapy has been highly advanced as image guided radiation therapy (IGRT) by making advantage of image engineering technologies. Recently, novel frameworks based on image engineering technologies as well as machine learning technologies have been studied for sophisticating the radiation therapy. In this review paper, the author introduces several researches of applications of machine learning for radiation therapy. For examples, a method to determine the threshold values for standardized uptake value (SUV) for estimation of gross tumor volume (GTV) in positron emission tomography (PET) images, an approach to estimate the multileaf collimator (MLC) position errors between treatment plans and radiation delivery time, and prediction frameworks for esophageal stenosis and radiation pneumonitis risk after radiation therapy are described. Finally, the author introduces seven issues that one should consider when applying machine learning models to radiation therapy.

Successful Treatment of Transplant Renal Artery Thrombosis With Systemic Infusion of Recombinant-Tissue-Plasminogen Activator After Renal Transplant

A 24-year-old man with end-stage renal disease secondary to congenital renal hypoplasia under-went a preemptive renal transplant. Although a vascular complication occurred during surgery, the operation was completed satisfactorily. However, postoperative Doppler ultrasound showed no perfusion of the renal artery, vein, and parenchyma, indicating a transplant renal artery thrombosis. A reoperation was promptly performed, with systemic infusion of recombinant-tissue-plasminogen activator during graft nephrectomy, followed by a reimplant that resulted in a salvage allograft. Immediate thrombolysis using systemically infused recombinant-tissue-plasminogen activator may be an effective treatment option for transplant renal artery thrombosis after renal transplant.

Bone Aging by Advanced Glycation End Products

The quality and quantity of mandibular bone are essential prerequisites for osseointegrated implants. Only the Hounsfield unit on preoperative computed tomography is currently used as a clinical index. Nevertheless, a considerable mismatch occurs between bone quality and the Hounsfield unit. Loss of bone toughness during aging has been accepted based on empirical evidence, but this concept is unlikely evidence based at the level of mechanical properties. Nonenzymatic bone matrix cross-links associated with advanced glycation end products predominate as a consequence of aging. Thus, loss of tissue integrity could diminish the bone toughening mechanism. Here, we demonstrate an impaired bone toughening mechanism caused by mimicking aging in rabbits on a methionine-rich diet, which enabled an enhanced nonenzymatically cross-linked bone matrix. A 3-point bending test revealed a greater reduction in femoral fracture resistance in rabbits on a methionine-rich diet, despite higher maximum and normalized breaking forces (287.3 N and 88.1%, respectively), than in rabbits on a normal diet (262.2 N and 79.7%, respectively). In situ nanoindentation on mandibular cortical bone obtained from rabbits on a methionine-rich diet did not enable strain rate–dependent stiffening and consequent large-dimensional recovery during rapid loading following constant displacement after a rapid-load indentation test as compared with those in rabbits on a normal diet. Such nanoscale structure-function relationships dictate resistance to cracking propagation at the material level and allow for the overall bone toughening mechanism to operate under large external stressors. The strain-dependent stiffening was likely associated with strain-energy transfer to the superior cross-linked bone matrix network of the normal diet, while the reduction in the enzymatically cross-linked matrix in bone samples from rabbits on a methionine-rich diet likely diminished the intrinsic bone toughening mechanism. The present study also provides a precise protocol for evaluating bone mechanical properties at the material level based on observations from a series of nanoindentation experiments.

Laparoscopic upper-pole heminephrectomy for duplicated renal collecting system with superselective artery clamping using virtual partial nephrectomy analysis of Synapse Vincent: A case report

A 22-year-old woman was diagnosed with a duplicated renal collecting system with hydronephrosis and parenchymal loss in the upper pole of the left kidney. She underwent laparoscopic left upper-pole nephrectomy. Although a complex hilar vascular anatomy was identified during the operation, preoperative three-dimensional computed tomographic reconstruction using a three-dimensional image analysis device (Synapse Vincent; Fuji Medical Systems, Tokyo, Japan) greatly helped to accurately identify the anatomical renal hilum. For further detail, virtual partial nephrectomy analysis using a Voronoi decomposition was used to visualize the area supplied by a selected arterial branch including the atrophic cleavage line. We controlled the bleeding with selective clamping and safely carried out upper-pole heminephrectomy according to the preoperative plan.

Conservative Treatment for Benign Prostatic Hyperplasia in Patients With Bladder Stones

OBJECTIVE

To determine whether conservative management of benign prostatic hyperplasia (BPH) is an appropriate option for patients with bladder stones.

METHODS

The study cohort comprised 34 men who underwent endoscopic bladder stone removal with subsequent conservative management of BPH, including watchful waiting and medical therapy (alpha-blocker ± dutasteride), between April 2006 and January 2014. We recorded BPH-related complications after stone removal and compared International Prostate Symptom Scores, quality of life scores, and postvoid residual urine volume before and after treatment. Cumulative BPH-related complication-free survival and the preoperative parameters associated with the occurrence of BPH-related complications were also analyzed.

RESULTS

Twenty-six patients (76.5%) treated with conservative management had no BPH-related complications, during a mean follow-up of 52.6 ± 30.9 months. Mean International Prostate Symptom Scores fell from 13.5 ± 7.1 before treatment to 9.7 ± 6.3 after treatment (P = .025). One of the 34 patients (2.9%) experienced recurrent urinary infections, 2 (5.9%) had urinary retention, and 6 (17.6%) developed recurrent bladder stones. The cumulative BPH-related complication-free survival was 97.0% at 1 year, 81.8% at 3 years, and 70.5% at 5 years. Six of the men (17.6%) underwent invasive intervention for BPH after occurrence of these complications. Prostate volume was the only preoperative parameter associated with the occurrence of complications after stone removal (P = .035).

CONCLUSION

Conservative management of BPH can be an appropriate treatment option in men with bladder stones and concurrent mild-to-moderate lower urinary tract symptoms.

Complete resolution of myoclonus-like involuntary movements under subarachnoid block after midazolam administration in a patient undergoing cesarean section: a case report

Involuntary movement during and after neuraxial anesthesia, such as spinal and epidural anesthesia, is rarely observed. In this report, we describe a case of myoclonus-like involuntary movement of the upper extremities in a patient undergoing a planned repeat cesarean section under spinal anesthesia with bupivacaine that completely subsided after administration of 2 mg of midazolam. The myoclonus-like movement did not recur or cause any apparent neurological side effects.

Functional differences in the acinar cells of the murine major salivary glands

In humans, approximately 90% of saliva is secreted by the 3 major salivary glands: the parotid (PG), the submandibular (SMG), and the sublingual glands (SLG). Even though it is known that all 3 major salivary glands secrete saliva by a Cl(-)-dependent mechanism, salivary secretion rates differ greatly among these glands. The goal of this study was to gain insight into the properties of the ion-transporting pathways in acinar cells that might account for the differences among the major salivary glands. Pilocarpine-induced saliva was simultaneously collected in vivo from the 3 major salivary glands of mice. When normalized by gland weight, the amount of saliva secreted by the PG was more than 2-fold larger than that obtained from the SMG and SLG. At the cellular level, carbachol induced an increase in the intracellular [Ca(2+)] that was more than 2-fold larger in PG and SMG than in SLG acinar cells. Carbachol-stimulated Cl(-) efflux and the protein levels of the Ca(2+)-activated Cl(-) channel TMEM16A, the major apical Cl(-) efflux pathway in salivary acinar cells, were significantly greater in PG compared with SMG and SLG. In addition, we evaluated the transporter activity of the Na(+)-K(+)-2Cl(-) cotransporters (NKCC1) and anion exchangers (AE), the 2 primary basolateral Cl(-) uptake mechanisms in acinar cells. The SMG NKCC1 activity was about twice that of the PG and more than 12-fold greater than that of the SLG. AE activity was similar in PG and SLG, and both PG and SLG AE activity was about 2-fold larger than that of SMG. In summary, the salivation kinetics of the 3 major glands are distinct, and these differences can be explained by the unique functional properties of each gland related to Cl(-) movement, including the transporter activities of the Cl(-) uptake and efflux pathways, and intracellular Ca(2+) mobilization.

Management of sleep-time masticatory muscle activity using stabilisation splints affects psychological stress

To treat sleep bruxism (SB), symptomatic therapy using stabilisation splints (SS) is frequently used. However, their effects on psychological stress and sleep quality have not yet been examined fully. The objective of this study was to clarify the effects of SS use on psychological stress and sleep quality. The subjects (11 men, 12 women) were healthy volunteers. A crossover design was used. Sleep measurements were performed for three consecutive days or longer without (baseline) or with an SS or palatal splint (PS), and data for the final day were evaluated. We measured masseter muscle activity during sleep using portable electromyography to evaluate SB. Furthermore, to compare psychological stress before and after sleep, assessments were made based on STAI-JYZ and the measurement of salivary chromogranin A. To compare each parameter among the three groups (baseline, SS and PS), Friedman's and Dunn's tests were used. From the results of the baseline measurements, eight subjects were identified as high group and 15 as low group. Among the high group, a marked decrease in the number of bruxism events per hour and an increase in the difference in the total STAI Y-1 scores were observed in the SS group compared with those at baseline (P < 0·05). No significant difference was observed in sleep stages. SS use may be effective in reducing the number of SB events, while it may increase psychological stress levels, and SS use did not apparently influence sleep stages.

A retrospective study of digital subtraction technique to detect sclerotic changes in alveolar bone on intraoral radiographs of bisphosphonate-treated patients

OBJECTIVES

Several reports have suggested that sclerotic changes in cancellous bone of the jaw and thickening of the lamina dura are characteristic radiographic changes of an early silent stage of bisphosphonate (BP)-related osteonecrosis of the jaw. No quantitative evaluation has been reported to support this hypothesis. Emago(®) software (Oral Diagnostic Systems, Amsterdam, Netherlands) can perform digital subtraction on intraoral radiographs even if they were obtained by non-standardized radiography, provided the dimensional error is within a certain limit. The purpose of this study was to evaluate whether sclerotic changes of alveolar bone or thickening of lamina dura in patients using BP can be detected using the subtraction function of Emago.

METHODS

The authors selected 46 pairs of intraoral radiographs of the mandibular molar area in dental patients. All radiographs were obtained at intervals of 6 months or more. Among the 46 pairs, 7 pairs were from patients who were being treated with BP (study subjects), and 39 pairs were from patients who had not been using BP (controls). All pairs of radiographs underwent digital subtraction by Emago. The number of pixels of the sclerotic areas was counted and compared between subjects and controls.

RESULTS

The sclerotic changes were significantly distinguishable in two of the seven subjects (28.6%) using BP.

CONCLUSIONS

Digital subtraction function of Emago was able to detect sclerotic changes in alveolar bone. Therefore, it is suggested that the subtraction function of Emago is a useful tool for quantitatively detecting sclerotic changes that are observed at an early, silent stage of BP-related osteonecrosis of the jaw.

Remineralization of artificial enamel lesions by theobromine

OBJECTIVE

This study investigated the remineralization potential of theobromine in comparison to a standard NaF dentifrice.

METHODS

Three tooth blocks were produced from each of 30 teeth. Caries-like lesion was created on each block using acidified gel. A smaller block was cut from each block for baseline scanning electron microscopy imaging and electron-dispersive spectroscopy (EDS) analysis for surface Ca level. A tooth slice was cut from each lesion-bearing block for transverse microradiography (TMR) quantification of baseline mineral loss (Δz) and lesion depth (LD). Then baseline surface microhardness (SMH) of each lesion was measured. The three blocks from each tooth were assigned to three remineralizing agents: (1) artificial saliva; (2) artificial saliva with theobromine (0.0011 mol/l), and (3) NaF toothpaste slurry (0.0789 mol/l F). Remineralization was conducted using a pH cycling model with storage in artificial saliva. After a 28-day cycle, samples were analyzed using EDS, TMR, and SMH. Intragroup comparison of pre- and posttest data was performed using t tests (p < 0.05). Intergroup comparisons were performed by post hoc multistep comparisons (Tukey).

RESULTS

SMH indicated significant (p < 0.01) remineralization only with theobromine (38 ± 32%) and toothpaste (29 ± 16%). With TMR (Δz/lD), theobromine and toothpaste exhibited significantly (p < 0.01) higher mineral gain relative to artificial saliva. With SMH and TMR, remineralization produced by theobromine and toothpaste was not significantly different. With EDS, calcium deposition was significant in all groups, but not significantly different among the groups (theobromine 13 ± 8%, toothpaste 10 ± 5%, and artificial saliva 6 ± 8%).

CONCLUSION

The present study demonstrated that theobromine in an apatite-forming medium can enhance the remineralization potential of the medium.

A retrospective study of digital subtraction technique to detect sclerotic changes in alveolar bone on intraoral radiographs of bisphosphonate-treated patients

OBJECTIVES

Several reports have suggested that sclerotic changes in cancellous bone of the jaw and thickening of the lamina dura are characteristic radiographic changes of an early silent stage of bisphosphonate (BP)-related osteonecrosis of the jaw. No quantitative evaluation has been reported to support this hypothesis. Emago® software (Oral Diagnostic Systems, Amsterdam, Netherlands) can perform digital subtraction on intraoral radiographs even if they were obtained by non-standardized radiography, provided the dimensional error is within a certain limit. The purpose of this study was to evaluate whether sclerotic changes of alveolar bone or thickening of lamina dura in patients using BP can be detected using the subtraction function of Emago.

METHODS

The authors selected 46 pairs of intraoral radiographs of the mandibular molar area in dental patients. All radiographs were obtained at intervals of 6 months or more. Among the 46 pairs, 7 pairs were from patients who were being treated with BP (study subjects), and 39 pairs were from patients who had not been using BP (controls). All pairs of radiographs underwent digital subtraction by Emago. The number of pixels of the sclerotic areas was counted and compared between subjects and controls.

RESULTS

The sclerotic changes were significantly distinguishable in two of the seven subjects (28.6%) using BP.

CONCLUSIONS

Digital subtraction function of Emago was able to detect sclerotic changes in alveolar bone. Therefore, it is suggested that the subtraction function of Emago is a useful tool for quantitatively detecting sclerotic changes that are observed at an early, silent stage of BP-related osteonecrosis of the jaw.