Enhancing Diagnostic Precision: Evaluation of Preprocessing Filters in Simple Diffusion Kurtosis Imaging for Head and Neck Tumors.

Background: Our initial clinical study using simple diffusion kurtosis imaging (SDI), which simultaneously produces a diffusion kurtosis image (DKI) and an apparent diffusion coefficient map, confirmed the usefulness of SDI for tumor diagnosis. However, the obtained DKI had noticeable variability in the mean kurtosis (MK) values, which is inherent to SDI. We aimed to improve this variability in SDI by preprocessing with three different filters (Gaussian [G], median [M], and nonlocal mean) of the diffusion-weighted images used for SDI. Methods: The usefulness of filter parameters for diagnosis was examined in basic and clinical studies involving 13 patients with head and neck tumors. Results: The filter parameters, which did not change the median MK value, but reduced the variability and significantly homogenized the MK values in tumor and normal tissues in both basic and clinical studies, were identified. In the receiver operating characteristic curve analysis for distinguishing tumors from normal tissues using MK values, the area under curve values significantly improved from 0.627 without filters to 0.641 with G (σ = 0.5) and 0.638 with M (radius = 0.5). Conclusions: Thus, image pretreatment with G and M for SDI was shown to be useful for improving tumor diagnosis in clinical practice.

Characteristic Mean Kurtosis Values in Simple Diffusion Kurtosis Imaging of Dentigerous Cysts.

We evaluated the usefulness of simple diffusion kurtosis (SD) imaging, which was developed to generate diffusion kurtosis images simultaneously with an apparent diffusion coefficient (ADC) map for 27 cystic disease lesions in the head and neck region. The mean kurtosis (MK) and ADC values were calculated for the cystic space. The MK values were dentigerous cyst (DC): 0.74, odontogenic keratocyst (OKC): 0.86, ranula (R): 0.13, and mucous cyst (M): 0, and the ADC values were DC: 1364 × 10-6 mm2/s, OKC: 925 × 10-6 mm2/s, R: 2718 × 10-6 mm2/s, and M: 2686 × 10-6 mm2/s. The MK values of DC and OKC were significantly higher than those of R and M, whereas their ADC values were significantly lower. One reason for the characteristic signal values in diffusion-weighted images of DC may be related to content components such as fibrous tissue and exudate cells. When imaging cystic disease in the head and neck region using SD imaging, the maximum b-value setting at the time of imaging should be limited to approximately 1200 s/mm2 for accurate MK value calculation. This study is the first to show that the MK values of DC are characteristically higher than those of other cysts.

Evaluation of the accuracy of heart dose prediction by machine learning for selecting patients not requiring deep inspiration breath­hold radiotherapy after breast cancer surgery.

Increased heart dose during postoperative radiotherapy (RT) for left-sided breast cancer (BC) can cause cardiac injury, which can decrease patient survival. The deep inspiration breath-hold technique (DIBH) is becoming increasingly common for reducing the mean heart dose (MHD) in patients with left-sided BC. However, treatment planning and DIBH for RT are laborious, time-consuming and costly for patients and RT staff. In addition, the proportion of patients with left BC with low MHD is considerably higher among Asian women, mainly due to their smaller breast volume compared with that in Western countries. The present study aimed to determine the optimal machine learning (ML) model for predicting the MHD after RT to pre-select patients with low MHD who will not require DIBH prior to RT planning. In total, 562 patients with BC who received postoperative RT were randomly divided into the trainval (n=449) and external (n=113) test datasets for ML using Python (version 3.8). Imbalanced data were corrected using synthetic minority oversampling with Gaussian noise. Specifically, right-left, tumor site, chest wall thickness, irradiation method, body mass index and separation were the six explanatory variables used for ML, with four supervised ML algorithms used. Using the optimal value of hyperparameter tuning with root mean squared error (RMSE) as an indicator for the internal test data, the model yielding the best F2 score evaluation was selected for final validation using the external test data. The predictive ability of MHD for true MHD after RT was the highest among all algorithms for the deep neural network, with a RMSE of 77.4, F2 score of 0.80 and area under the curve-receiver operating characteristic of 0.88, for a cut-off value of 300 cGy. The present study suggested that ML can be used to pre-select female Asian patients with low MHD who do not require DIBH for the postoperative RT of BC.

Mean Heart Dose Prediction Using Parameters of Single-Slice Computed Tomography and Body Mass Index: Machine Learning Approach for Radiotherapy of Left-Sided Breast Cancer of Asian Patients.

Deep inspiration breath-hold (DIBH) is an excellent technique to reduce the incidental radiation received by the heart during radiotherapy in patients with breast cancer. However, DIBH is costly and time-consuming for patients and radiotherapy staff. In Asian countries, the use of DIBH is restricted due to the limited number of patients with a high mean heart dose (MHD) and the shortage of radiotherapy personnel and equipment compared to that in the USA. This study aimed to develop, evaluate, and compare the performance of ten machine learning algorithms for predicting MHD using a patient's body mass index and single-slice CT parameters to identify patients who may not require DIBH. Machine learning models were built and tested using a dataset containing 207 patients with left-sided breast cancer who were treated with field-in-field radiotherapy with free breathing. The average MHD was 251 cGy. Stratified repeated four-fold cross-validation was used to build models using 165 training data. The models were compared internally using their average performance metrics: F2 score, AUC, recall, accuracy, Cohen's kappa, and Matthews correlation coefficient. The final performance evaluation for each model was further externally analyzed using 42 unseen test data. The performance of each model was evaluated as a binary classifier by setting the cut-off value of MHD ≥ 300 cGy. The deep neural network (DNN) achieved the highest F2 score (78.9%). Most models successfully classified all patients with high MHD as true positive. This study indicates that the ten models, especially the DNN, might have the potential to identify patients who may not require DIBH.

Usefulness of Simple Diffusion Kurtosis Imaging for Head and Neck Tumors: An Early Clinical Study.

Diffusion kurtosis (DK) imaging (DKI), a type of restricted diffusion-weighted imaging, has been reported to be useful for tumor diagnoses in clinical studies. We developed a software program to simultaneously create DK images with apparent diffusion coefficient (ADC) maps and conducted an initial clinical study. Multi-shot echo-planar diffusion-weighted images were obtained at b-values of 0, 400, and 800 sec/mm2 for simple DKI, and DK images were created simultaneously with the ADC map. The usefulness of the DK image and ADC map was evaluated using a pixel analysis of all pixels and a median analysis of the pixels of each case. Tumor and normal tissues differed significantly in both pixel and median analyses. In the pixel analysis, the area under the curve was 0.64 for the mean kurtosis (MK) value and 0.77 for the ADC value. In the median analysis, the MK value was 0.74, and the ADC value was 0.75. The MK and ADC values correlated moderately in the pixel analysis and strongly in the median analysis. Our simple DKI system created DK images simultaneously with ADC maps, and the obtained MK and ADC values were useful for differentiating head and neck tumors from normal tissue.

Evaluation of calculation processes of apparent diffusion coefficient subtraction method (ASM) imaging.

A number of restricted diffusion (RD) imaging techniques, such as diffusion kurtosis (DK) imaging and Q space imaging, have been developed and proven to be useful for the diagnosis of diseases, including cerebral gliomas and cerebrovascular infarction. In particular, apparent diffusion coefficient (ADC) subtraction method (ASM) imaging has become available recently as a novel RD imaging technique. ASM is based on the difference between the ADC values in an image pair of two ADC maps, ADC basic (ADCb) and ADC modify (ADCm), which are created from diffusion-weighted images taken using short and long effective diffusion times, respectively. The present study aimed to assess the potential of different types of ASM imaging by comparing them with DK imaging which is the gold-standard RD imaging technique. In the present basic study using both polyethylene glycol phantom and cell-containing bio-phantom, three different types of ASM images were created using different calculation processes. ASM/A is an image calculated by dividing the absolute difference between ADCb and ADCm by ADCb several times. By contrast, ASM/S is an image created by dividing the absolute difference between ADCb and ADCm by the standard deviation of ADCb several times. As for positive ASM/A image (PASM/A), the positive image, which was resultant after subtracting ADCb from ADCm, was divided by ADCb several times. A comparison was made between the types of ASM and DK images. The results showed the same tendency between ASM/A in addition to both ASM/S and PASM/A. By increasing the number of divisions by ADCb from three to five times, ASM/A images transformed from DK-mimicking to more RD-sensitive images compared with DK images. These observations suggest that ASM/A images may prove useful for future clinical applications in RD imaging protocols for the diagnosis of diseases.

Quantitative evaluation of the reduction of distortion and metallic artifacts in magnetic resonance images using the multiacquisition variable­resonance image combination selective sequence.

Magnetic resonance imaging (MRI) is superior to computed tomography (CT) in determining changes in tissue structure, such as those observed following inflammation and infection. However, when metal implants or other metal objects are present, MRI exhibits more distortion and artifacts compared with CT, which hinders the accurate measurement of the implants. A limited number of reports have examined whether the novel MRI sequence, multiacquisition variable-resonance image combination selective (MAVRIC SL), can accurately measure metal implants without distortion. Therefore, the present study aimed to demonstrate whether MAVRIC SL could accurately measure metal implants without distortion and whether the area around the metal implants could be well delineated without artifacts. An agar phantom containing a titanium alloy lumbar implant was used for the present study and was imaged using a 3.0 T MRI machine. A total of three imaging sequences, namely MAVRIC SL, CUBE and magnetic image compilation (MAGiC), were applied and the results were compared. Distortion was evaluated by measuring the screw diameter and distance between the screws multiple times in the phase and frequency directions by two different investigators. The artifact region around the implant was examined using a quantitative method following standardization of the phantom signal values. It was revealed that MAVRIC SL was a superior sequence compared with CUBE and MAGiC, as there was significantly less distortion, a lack of bias between the two different investigators and significantly reduced artifact regions. These results suggested the possibility of utilizing MAVRIC SL for follow-up to observe metal implant insertions.

Evaluation of Fast Diffusion Kurtosis Imaging Using New Software Designed for Widespread Clinical Use.

Clinical research using restricted diffusion-weighted imaging, especially diffusion kurtosis (DK) imaging, has been progressing, with reports on its effectiveness in the diagnostic imaging of cerebral infarctions, neurodegenerative diseases, and tumors, among others. However, the application of DK imaging in daily clinical practice has not spread because of the long imaging time required and the use of specific software for image creation. Herein, with the aim of promoting clinical research using DK imaging at any medical facility, we evaluated fast DK imaging using a new software program. We developed a new macro program that produces DK images using general-purpose, inexpensive software (Microsoft Excel and ImageJ), and we evaluated fast DK imaging using bio-phantoms and a healthy volunteer in clinical trials. The DK images created by the new software with diffusion-weighted images captured with short-time imaging sequences were similar to the original DK images captured with long-time imaging sequences. The DK images using three b-values, which can reduce the imaging time by 43%, were equivalent to the DK images using five b-values. The DK imaging technique developed herein might allow any medical facility to increase its daily clinical use of DK imaging and easily conduct clinical research.

Collision tumor of small cell carcinoma and squamous cell carcinoma of the maxillary sinus: Case report.

A collision tumor refers to the coexistence of two diagnostically distinct tumors in a common anatomic space. Collision tumors are rare in the oral and maxillofacial region. The present study reported on the case of an 82-year-old female with a collision tumor in the maxillary sinus consisting of small cell carcinoma (SmCC) and squamous cell carcinoma (SCC). Computed tomography (CT) imaging revealed a mass in the right maxillary sinus. The lesion exhibited heterogeneous low signal intensity (SI) on T1-weighted imaging (T1WI), high SI on short T1 inversion recovery and heterogeneous solid enhancement on contrast-enhanced T1WI. The histopathology result of a biopsy specimen confirmed SmCC. After the patient received a course of chemoradiotherapy, follow-up CT revealed a residual tumor. In a second surgery, a remaining tumor and histopathology revealed SCC with no evidence of SmCC. The final diagnosis was a collision tumor made up of SCC and SmCC.

Evaluation of the Imaging Process for a Novel Subtraction Method Using Apparent Diffusion Coefficient Values.

Diffusion-weighted imaging may be used to obtain the apparent diffusion coefficient (ADC), which aids the diagnosis of cerebral infarction and tumors. An ADC reflects elements of free diffusion. Diffusion kurtosis imaging (DKI) has attracted attention as a restricted diffusion imaging technique. The ADC subtraction method (ASM) was developed to visualize restricted diffusion with high resolution by using two ADC maps taken with different diffusion times. We conducted the present study to provide a bridge between the reported basic ASM research and clinical research. We developed new imaging software for clinical use and evaluated its performance herein. This software performs the imaging process automatically and continuously at the pixel level, using ImageJ software. The new software uses a macro or a plugin which is compatible with various operating systems via a Java Virtual Machine. We tested the new imaging software's performance by using a Jurkat cell bio-phantom, and the statistical evaluation of the performance clarified that the ASM values of 99.98% of the pixels in the bio-phantom and physiological saline were calculated accurately (p<0.001). The new software may serve as a useful tool for future clinical applications and restricted diffusion imaging research.

Development of a novel phantom using polyethylene glycol for the visualization of restricted diffusion in diffusion kurtosis imaging and apparent diffusion coefficient subtraction method.

The present study aimed to investigate whether polyethylene glycol (PEG) phantoms have the potential to be used as standard phantoms for magnetic resonance imaging (MRI) in order to visualize restricted diffusion in diffusion kurtosis imaging (DKI), the ADC subtraction method (ASM) and the apparent diffusion coefficient (ADC). Diffusion-weighted images of 0-120 mM PEG phantoms were captured to create ADC, DKI and ASM images with post-processing. ASM is a recently developed method for restricted diffusion imaging using the readout segmentation of long variable echo-train sequences. As the PEG concentration increases, the ADC value decreases. Conversely, an increase in DKI and ASM values is associated with increasing PEG concentration. Formulae were constructed to represent the association between PEG concentrations and ADC, DKI and ASM values. These formulae can be used to determine the required PEG concentrations to mimic arbitrary ADC, DKI and ASM values of certain diseases, including tumors and infarctions. Validation experiments were conducted using bio-phantoms and clarified that the PEG phantoms cover the range of ADC and DKI values reported in previous clinical research using 3T MRI. PEG phantoms may be useful for future MRI research involving restricted diffusion.

Development of a novel method for visualizing restricted diffusion using subtraction of apparent diffusion coefficient values.

In order to visualize restricted diffusion, the present study developed a novel method called 'apparent diffusion coefficient (ADC) subtraction method (ASM)' and compared it with diffusion kurtosis imaging (DKI). The diffusion-weighted images of physiological saline, in addtion to bio-phatoms of low cell density and the highest cell density were obtained using two sequences with different effective diffusion times. Then, the calculated ADC values were subtracted. The mean values and standard deviations (SD) of the ADC values of physiological saline, low cell density and the highest cell density phantoms were 2.95±0.08x10­3, 1.90±0.35x10­3 and 0.79±0.05x10­3 mm2/sec, respectively. The mean kurtosis values and SD of DKI were 0.04±0.01, 0.44±0.13 and 1.27±0.03, respectively. The ASM and SD values were 0.25±0.20x104, 0.51±0.41x104 and 4.80±4.51x104 (sec/mm2)2, respectively. Using bio­phantoms, the present study demonstrated that DKI exhibits restricted diffusion in the extracellular space. Similarly, ASM may reflect the extent of restricted diffusion in the extracellular space.

Current status of oral and maxillofacial radiology in West Africa.

BACKGROUND: Oral and maxillofacial radiology became the ninth dental specialty recognized by the American Dental Association (ADA) in 1999. This came about following the discovery of X-rays by Wilhelm Conrad Roentgen in 1895 and, 14 days later, the application of X-rays to making dental radiographs by Otto Walkhoff. The purpose of this narrative study was to review the evolution of oral and maxillofacial radiology as a dental specialty in the USA and its recognition as a program of training by the West African College of Surgeons. METHODS: This study was conceptualized as a narrative review of the literature focusing on the history and development of oral and maxillofacial radiology in the USA. It builds a synthesis that describes the recognition of oral and maxillofacial radiology as a specialty of dentistry in West Africa, UK, Japan, and Australia. RESULTS: The main finding was that oral and maxillofacial radiology became the ninth specialty recognized by the American Dental Association, ADA, in October 13, 1999. On March 20, 2014, the West African College of Surgeons recognized this specialty and granted accreditation for postgraduate training. In the UK, Japan, and Australia, the postgraduate education in oral and maxillofacial radiology has two patterns, namely professional training and academic training. CONCLUSIONS: The primary goal of the postgraduate training curriculum is to train radiologists who are competent to deliver care to patients in any clinical setting, including a dental school, hospital radiology practice, or private practice.

Evaluation of Setup Errors at the Skin Surface Position for Whole Breast Radiotherapy of Breast Cancer Patients.

We used image-processing software to analyze the setup errors at the skin surface position of breast cancer patients (n=66) who underwent post-operative whole breast irradiation at our hospital in 2014-2015. The sixty-six digital reconstructed radiographs (DRR) were created at the treatment planning for each patient. The lineacgraphies (n=377) were taken after the patients' setup during radiotherapy. The lineacgraphies and DRR were superimposed at the skin surface position for each patient with the image-processing software. We measured the deviations of the isocenters for the nipple-lung (X) direction and craniocaudal (Y) direction and the deviation of the rotation angle of the XY axes between the lineacgraphy and DRR on the superimposed images. The systematic error (µ, Σ) and random error (σ) were calculated from the X and Y deviations and rotation angle deviation. The µ of X, Y, and rotation angle were 0.01 mm, -1.2 mm, and 0.05°, respectively. The Σ of X, Y, and rotation angle were 1.8 mm, 1.5 mm, and 0.9°, respectively. The σ of X, Y, and rotation angle were 2.0 mm, 1.5 mm, and 1.0°, respectively. Our analyses thus revealed that evaluations using image-processing software at the skin surface position in routine breast radiotherapy result in sufficiently small setup errors.

A Case of Schwannoma of the Submandibular Region.

BACKGROUND: We herein described a rare case of schwannoma of the hypoglossal nerve in the submandibular region with diagnostic imaging and histopathological findings. CASE REPORT: A 31-years-old woman has had a palpable firm, rubbery, freely mobile mass in the submandibular region. Of imaging, MR images showed homogeneous isointensity on T1-weighted imaging (T1-WI), heterogeneous hypointensity on T2-WI, heterogeneous hyperintensity on short T1 inversion recovery (STIR), and heterogeneous enhancement on contrast-enhanced T1-WI. A clear capsule was observed on the margin and showed hypointense on T2-WI. Dynamic MRI showed heterogeneous gradual increased enhancement. The uptake of contrast medium was regionally slow. Diagnostic imaging using CT and MRI was suspected of salivary gland tumor or neurogenic tumor. In consideration of imaging diagnosis, a pleomorphic adenoma or a schwannoma was suspected. Final diagnosis was confirmed on the basis of histopathological finding and intraoperative findings. CONCLUSION: 1. Histopathologic examination is inevitable, because MR findings are not specific.2. Schwannomas were said to have specific MRI properties, including specific signs (split-fat sign, fascicular sign, target sign). However, they are not always observed.3. This case confirmed the differential diagnosis on the basis of the intraoperative finding that the tumor was continuous with the hypoglossal nerve.

Incidental finding of papillary thyroid carcinoma on CT examination of mandibular lesion: Case report.

The number of significant incidental findings identified on radiographic examinations has increased. In total, 169 patients, 87 males and 82 females, with a mean age of 67.3 years (range, 17-92 years), as well as 65 patients (38.5%), 43 (66.2%) female and 22 (33.8%) male had abnormal findings in the thyroid for one year in our institution. Thyroid nodules are the most common incidental findings on oral and maxillofacial evaluations. Computed tomography (CT) and magnetic resonance imaging (MRI) examination are frequently used to detect thyroid abnormality. The present study reported a case of papillary thyroid carcinoma (PTC) detected following CT and MRI examination of a mandibular lesion. The CT examination of the oral and maxillofacial region included the thyroid, which must be examined carefully to detect various diseases, including PTC. Collaboration between radiologists and clinicians is important to manage these incidental findings.