Automatic diagnosis of melanoma using machine learning methods on a spectroscopic systemBMC Medical Imaging - Tập 14 - Trang 1-12 - 2014
Lin Li, Qizhi Zhang, Yihua Ding, Huabei Jiang, Bruce H Thiers, James Z Wang
Early and accurate diagnosis of melanoma, the deadliest type of skin cancer, has the potential to reduce morbidity and mortality rate. However, early diagnosis of melanoma is not trivial even for experienced dermatologists, as it needs sampling and laboratory tests which can be extremely complex and subjective. The accuracy of clinical diagnosis of melanoma is also an issue especially in distinguishing between melanoma and mole. To solve these problems, this paper presents an approach that makes non-subjective judgements based on quantitative measures for automatic diagnosis of melanoma. Our approach involves image acquisition, image processing, feature extraction, and classification. 187 images (19 malignant melanoma and 168 benign lesions) were collected in a clinic by a spectroscopic device that combines single-scattered, polarized light spectroscopy with multiple-scattered, un-polarized light spectroscopy. After noise reduction and image normalization, features were extracted based on statistical measurements (i.e. mean, standard deviation, mean absolute deviation, L
1
norm, and L
2
norm) of image pixel intensities to characterize the pattern of melanoma. Finally, these features were fed into certain classifiers to train learning models for classification. We adopted three classifiers – artificial neural network, naïve bayes, and k-nearest neighbour to evaluate our approach separately. The naive bayes classifier achieved the best performance - 89% accuracy, 89% sensitivity and 89% specificity, which was integrated with our approach in a desktop application running on the spectroscopic system for diagnosis of melanoma. Our work has two strengths. (1) We have used single scattered polarized light spectroscopy and multiple scattered unpolarized light spectroscopy to decipher the multilayered characteristics of human skin. (2) Our approach does not need image segmentation, as we directly probe tiny spots in the lesion skin and the image scans do not involve background skin. The desktop application for automatic diagnosis of melanoma can help dermatologists get a non-subjective second opinion for their diagnosis decision.
Lung nodule pre-diagnosis and insertion path planning for chest CT imagesBMC Medical Imaging - Tập 23 - Trang 1-16 - 2023
Rong-Li Xie, Yao Wang, Yan-Na Zhao, Jun Zhang, Guang-Biao Chen, Jian Fei, Zhuang Fu
Medical image processing has proven to be effective and feasible for assisting oncologists in diagnosing lung, thyroid, and other cancers, especially at early stage. However, there is no reliable method for the recognition, screening, classification, and detection of nodules, and even deep learning-based methods have limitations. In this study, we mainly explored the automatic pre-diagnosis of lung nodules with the aim of accurately identifying nodules in chest CT images, regardless of the benign and malignant nodules, and the insertion path planning of suspected malignant nodules, used for further diagnosis by robotic-based biopsy puncture. The overall process included lung parenchyma segmentation, classification and pre-diagnosis, 3-D reconstruction and path planning, and experimental verification. First, accurate lung parenchyma segmentation in chest CT images was achieved using digital image processing technologies, such as adaptive gray threshold, connected area labeling, and mathematical morphological boundary repair. Multi-feature weight assignment was then adopted to establish a multi-level classification criterion to complete the classification and pre-diagnosis of pulmonary nodules. Next, 3-D reconstruction of lung regions was performed using voxelization, and on its basis, a feasible local optimal insertion path with an insertion point could be found by avoiding sternums and/or key tissues in terms of the needle-inserting path. Finally, CT images of 900 patients from Lung Image Database Consortium and Image Database Resource Initiative were chosen to verify the validity of pulmonary nodule diagnosis. Our previously designed surgical robotic system and a custom thoracic model were used to validate the effectiveness of the insertion path. This work can not only assist doctors in completing the pre-diagnosis of pulmonary nodules but also provide a reference for clinical biopsy puncture of suspected malignant nodules considered by doctors.
Incidence of maxillary sinus septa in the saudi populationBMC Medical Imaging - Tập 23 - Trang 1-9 - 2023
Amani Mirdad, Razan Alaqeely, Sumaiah Ajlan, Mazen A. Aldosimani, Nahid Ashri
The variability in the maxillary sinus anatomy makes dental implant planning challenging. One of the anatomical landmarks that could affect the decision for implant placement around the maxillary sinus is the sinus septa. This study aimed to retrospectively determine the prevalence, anatomical distribution, and morphology of the maxillary sinus septa. This study included 309 CBCT images that were analyzed to determine the prevalence, height, location, and orientation of the maxillary sinus septa. Descriptive statistics, Mann‒Whitney U tests, and Kruskal‒Wallis tests were used for data analysis. A total of 618 maxillary sinuses were analyzed. Maxillary septa were present in 30% (n = 188) of the sinuses and in approximately 45% of the analyzed images. The mean height of the septa was 5.09 mm. The presence of bilateral septa was evident in 49 subjects (35.25%). Female subjects were significantly more likely to have only one septum (n = 67, 53.6%, p < 0.05). The presence of septa is very common, found in one-third to approximately half of the evaluated cases, which warrants careful examination before any surgical interventions to avoid possible complications.
A practical biphasic contrast media injection protocol strongly enhances the aorta and pulmonary artery simultaneously using a single CT angiography scanBMC Medical Imaging - - 2021
Cheng‐Chih Hsieh, An-Bang Zeng, Chia-Hung Chen, Zong-Yi Jhou, Chih-Hsin Wang, Yongjian Yang, Feng-Chuan Hsieh, Jingkai Lin, Ju-Yen Yeh, Chun-Chao Huang
Abstract
Background
Enhancement profiles of the pulmonary artery (PA) and aorta differ when using computed tomography (CT) angiography. Our aim was to determine the optimal CT protocol for a one-time CT scan that assesses both blood vessels.
Methods
We prospectively enrolled 101 cases of CT angiography in patients with suspected pulmonary embolism or aortic dissection from our center between 2018 and 2020. We also retrospectively collected the data of 40 patients who underwent traditional two-time CT scans between 2015 and 2018. Patients were divided into four groups: test bolus (TB) I, TB II, bolus-tracking (BT) I, and BT II. The enhancement of the PA and aorta, and the radiation doses used in the four groups were collected. Those who underwent two-time scans were classified into the traditional PA or aorta scan groups. Data were compared between the BT and traditional groups.
Results
The aortic enhancement was highest in BT II (294.78 ± 64.48 HU) followed BT I (285.18 ± 64.99 HU), TB II (186.58 ± 57.53 HU), and TB I (173.62 ± 69.70 HU). The radiation dose used was lowest in BT I (11.85 ± 5.55 mSv) and BT II (9.07 ± 3.44 mSv) compared with that used in the traditional groups (20.07 ± 7.78 mSv) and accounted for half of the traditional group (45.17–59.02%). The aortic enhancement was also highest in BT II (294.78 ± 64.48 HU) followed by BT I (285.18 ± 64.99 HU) when compared with that in the traditional aorta scan group (234.95 ± 94.18 HU).
Conclusion
Our CT protocol with a BT technique allows for a lower radiation dose and better image quality of the PA and aorta than those obtained using traditional CT scans.
Trial registration: NCT04832633, retrospectively registered in April 2021 to the clinical trial registry.
Prediction of lymph node status in patients with early-stage cervical cancer based on radiomic features of magnetic resonance imaging (MRI) imagesBMC Medical Imaging -
Shuyu Liu, Yu Zhou, Caizhi Wang, Junjie Shen, Yi Zheng
Abstract
Background
Lymph node metastasis is an important factor affecting the treatment and prognosis of patients with cervical cancer. However, the comparison of different algorithms and features to predict lymph node metastasis is not well understood. This study aimed to construct a non-invasive model for predicting lymph node metastasis in patients with cervical cancer based on clinical features combined with the radiomic features of magnetic resonance imaging (MRI) images.
Methods
A total of 180 cervical cancer patients were divided into the training set (n = 126) and testing set (n = 54). In this cross-sectional study, radiomic features of MRI images and clinical features of patients were collected. The least absolute shrinkage and selection operator (LASSO) regression was used to filter the features. Seven machine learning methods, including eXtreme Gradient Boosting (XGBoost), Logistic Regression, Multinomial Naive Bayes (MNB), Support Vector Machine (SVM), Decision Tree, Random Forest, and Gradient Boosting Decision Tree (GBDT) are used to build the models. Receiver operating characteristics (ROC) curve and area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the performance of the models.
Results
Of these 180 patients, 49 (27.22%) patients had lymph node metastases. Five of the 122 radiomic features and 3 clinical features were used to build predictive models. Compared with other models, the MNB model was the most robust, with its AUC, specificity, and accuracy on the testing set of 0.745 (95%CI: 0.740–0.750), 0.900 (95%CI: 0.807–0.993), and 0.778 (95%CI: 0.667–0.889), respectively. Furthermore, the AUCs of the MNB models with clinical features only, radiomic features only, and combined features were 0.698 (95%CI: 0.692–0.704), 0.632 (95%CI: 0.627–0.637), and 0.745 (95%CI: 0.740–0.750), respectively.
Conclusion
The MNB model, which combines the radiomic features of MRI images with the clinical features of the patient, can be used as a non-invasive tool for the preoperative assessment of lymph node metastasis.
A diagnosis model in nasopharyngeal carcinoma based on PET/MRI radiomics and semiquantitative parametersBMC Medical Imaging - Tập 22 - Trang 1-9 - 2022
Qi Feng, Jiangtao Liang, Luoyu Wang, Xiuhong Ge, Zhongxiang Ding, Haihong Wu
The staging of nasopharyngeal carcinoma (NPC) is of great value in treatment and prognosis. We explored whether a positron emission tomography/ magnetic resonance imaging (PET/MRI) based comprehensive model of radiomics features and semiquantitative parameters was useful for clinical evaluation of NPC staging. A total of 100 NPC patients diagnosed with non-keratinized undifferentiated carcinoma were divided into early-stage group (I—II) and advanced-stage group (III—IV) and divided into the training set (n = 70) and the testing set (n = 30). Radiomics features (n = 396 × 2) of the primary site of NPC were extracted from MRI and PET images, respectively. Three major semiquantitative parameters of primary sites including maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) in all NPC patients were measured. After feature selection, three diagnostic models including the radiomics model, the metabolic parameter model, and the combined model were established using logistic regression model. Finally, internal validation was performed, and a nomogram for NPC comprehensive diagnosis has been made. The radiomics model and metabolic parameter model showed an area under the curve (AUC) of 0.83 and 0.80 in the testing set, respectively. The combined model based on radiomics and semiquantitative parameters showed an AUC of 0.90 in the testing set, with the best performance among the three models. The combined model based on PET/MRI radiomics and semiquantitative parameters is of great value in the evaluation of clinical stage (early-stage group and advanced-stage group) of NPC.
Three-dimensional ultrashort echo time magnetic resonance imaging in pediatric patients with pneumonia: a comparative studyBMC Medical Imaging - Tập 23 - Trang 1-9 - 2023
Yan Sun, Yujie Chen, Xuesheng Li, Yi Liao, Xijian Chen, Yu Song, Xinyue Liang, Yongming Dai, Dapeng Chen, Gang Ning
UTE has been used to depict lung parenchyma. However, the insufficient discussion of its performance in pediatric pneumonia compared with conventional sequences is a gap in the existing literature. The objective of this study was to compare the diagnostic value of 3D-UTE with that of 3D T1-GRE and T2-FSE sequences in young children diagnosed with pneumonia. Seventy-seven eligible pediatric patients diagnosed with pneumonia at our hospital, ranging in age from one day to thirty-five months, were enrolled in this study from March 2021 to August 2021. All patients underwent imaging using a 3 T pediatric MR scanner, which included three sequences: 3D-UTE, 3D-T1 GRE, and T2-FSE. Subjective analyses were performed by two experienced pediatric radiologists based on a 5-point scale according to six pathological findings (patchy shadows/ground-glass opacity (GGO), consolidation, nodule, bulla/cyst, linear opacity, and pleural effusion/thickening). Additionally, they assessed image quality, including the presence of artifacts, and evaluated the lung parenchyma. Interrater agreement was assessed using intraclass correlation coefficients (ICCs). Differences among the three sequences were evaluated using the Wilcoxon signed-rank test. The visualization of pathologies in most parameters (patchy shadows/GGO, consolidation, nodule, and bulla/cyst) was superior with UTE compared to T2-FSE and T1 GRE. The visualization scores for linear opacity were similar between UTE and T2-FSE, and both were better than T1-GRE. In the case of pleural effusion/thickening, T2-FSE outperformed the other sequences. However, statistically significant differences between UTE and other sequences were only observed for patchy shadows/GGO and consolidation. The overall image quality was superior or at least comparable with UTE compared to T2-FSE and T1-GRE. Interobserver agreements for all visual assessments were significant and rated “substantial” or “excellent.” In conclusion, UTE MRI is a useful and promising method for evaluating pediatric pneumonia, as it provided better or similar visualization of most imaging findings compared with T2-FSE and T1-GRE. We suggest that the UTE MRI is well-suited for pediatric population, especially in younger children with pneumonia who require longitudinal and repeated imaging for clinical care or research and are susceptible to ionizing radiation.
Assessment of postpartum haemorrhage for placenta accreta: Is measurement of myometrium thickness and dark intraplacental bands using MRI helpful?BMC Medical Imaging - Tập 22 Số 1
Xinyi Chen, Mingsheng Ying, Xu Han, Yinghui Xin, Lin Yang, Zhiling Liu, Yaling Han, Zhaoqin Huang, Renjie Li, Jie Zhang
Abstract
Background
This study aimed to investigate the predictive values of magnetic resonance imaging (MRI) myometrial thickness grading and dark intraplacental band (DIB) volumetry for blood loss in patients with placenta accreta spectrum (PAS).
Methods
Images and clinical data were acquired from patients who underwent placenta MRI examinations and were diagnosed with PAS from March 2015 to January 2021. Two radiologists jointly diagnosed, processed, and analysed the MR images of each patient. The analysis included MRI-based determination of placental attachment, as well as myometrial thickness grading and DIB volumetry. The patients included in the study were divided into three groups according to the estimated blood loss volume: in the general blood loss (GBL) group, the estimated blood loss volume was < 1000 ml; in the massive blood loss (MBL) group, the estimated blood loss volume was ≥ 1000 ml and < 2000 ml; and in the extremely massive blood loss (ex-MBL) group, the estimated blood loss volume was ≥ 2000 ml. The categorical, normally distributed, and non-normally distributed data were respectively analysed by the Chi-square, single-factor analysis of variance, and Kruskal–Wallis tests, respectively. The verification of correlation was completed by Spearman correlation analysis. The evaluation capabilities of indicators were assessed using receiver operating characteristic curves.
Results
Among 75 patients, 25 were included in the GBL group, 26 in the MBL group, and 24 in the ex-MBL group. A significant negative correlation was observed between the grade of myometrial thickness and the estimated blood loss (P < 0.001, ρ = − 0.604). There was a significant positive correlation between the volume of the DIB and the estimated blood loss (P < 0.001, ρ = 0.653). The areas under the receiver operating characteristic curve of the two MRI features for predicting blood loss ≥ 2000 ml were 0.776 and 0.897, respectively.
Conclusions
The grading and volumetric MRI features, myometrial thickness, and volume of DIB, can be used as good prediction indicators of the risk of postpartum haemorrhage in patients with PAS.
Comparison of 18F-sodium fluoride PET/CT, 18F-fluorocholine PET/CT and diffusion-weighted MRI for the detection of bone metastases in recurrent prostate cancer: a cost-effectiveness analysis in FranceBMC Medical Imaging - - 2020
Mathieu Gauthé, Kevin Zarca, Cyrielle Aveline, Frédéric Lecouvet, Sona Balogova, Olivier Cussenot, Jean-Noël Talbot, Isabelle Durand-Zaleski
The diagnostic performance of 18F-sodium fluoride positron emission tomography/computed tomography (PET/CT) (NaF), 18F-fluorocholine PET/CT (FCH) and diffusion-weighted whole-body magnetic resonance imaging (DW-MRI) in detecting bone metastases in prostate cancer (PCa) patients with first biochemical recurrence (BCR) has already been published, but their cost-effectiveness in this indication have never been compared. We performed trial-based and model-based economic evaluations. In the trial, PCa patients with first BCR after previous definitive treatment were prospectively included. Imaging readings were performed both on-site by local specialists and centrally by experts. The economic evaluation extrapolated the diagnostic performances of the imaging techniques using a combination of a decision tree and Markov model based on the natural history of PCa. The health states were non-metastatic and metastatic BCR, non-metastatic and metastatic castration-resistant prostate cancer and death. The state-transition probabilities and utilities associated with each health state were derived from the literature. Real costs were extracted from the National Cost Study of hospital costs and the social health insurance cost schedule. There was no significant difference in diagnostic performance among the 3 imaging modalities in detecting bone metastases. FCH was the most cost-effective imaging modality above a threshold incremental cost-effectiveness ratio of 3000€/QALY when imaging was interpreted by local specialists and 9000€/QALY when imaging was interpreted by experts. FCH had a better incremental effect on QALY, independent of imaging reading and should be preferred for detecting bone metastases in patients with biochemical recurrence of prostate cancer. NCT01501630. Registered 29 December 2011.
