Lesion Shape Research Articles

Prevalence and Pattern of Mandibular Condensing Osteitis Lesions in Saudi Population at Qassim Region

ABSTRACT Background: Condensing osteitis (CO) is a common radiopaque lesion observed in the jaws, often detected incidentally on panoramic radiographs. Understanding the prevalence and characteristics of CO is essential for early detection and appropriate management. Objective: To determine the prevalence and characteristics of condensing osteitis among the Saudi population in the Qassim region. Methods: A retrospective study was conducted using 876 digital panoramic radiographs. The presence of CO was identified based on specific radiographic features, and data were collected regarding gender, age, lesion localization, lesion shape, and associated dental status. Results: The prevalence of CO was found to be 2.3% (n = 20) in the study population, with a higher predilection in females (1.4%) compared to males (0.9%). The most commonly affected age group was 30–39 years for males and 10–19 and 30–39 years for females. The mandibular molar region was predominantly affected (90%), with a ‘U’ shape observed in 55% of the lesions. Root canal treatment was the most commonly associated dental status (75%), followed by deep caries (20%) and large restorations (5%). Conclusion: The study highlights a 2.3% prevalence of CO in the Saudi population of the Qassim region, with a higher predilection in females and a predominant localization in the mandibular molar region. Dental practitioners should be vigilant in identifying CO, especially in at-risk populations, to facilitate timely diagnosis and appropriate management.

Prediction of ovarian cancer prognosis using statistical radiomic features of ultrasound images

Objective. Ovarian cancer is the deadliest gynecologic malignancy worldwide. Ultrasound is the most useful non-invasive test for preoperative diagnosis of ovarian cancer. In this study, by leveraging multiple ultrasound images from the same patient to generate personalized, informative statistical radiomic features, we aimed to develop improved ultrasound image-based prognostic models for ovarian cancer. Approach. A total of 2057 ultrasound images from 514 ovarian cancer patients, including 355 patients with epithelial ovarian cancer, from two hospitals in China were collected for this study. The models were constructed using our recently developed Frequency Appearance in Multiple Univariate pre-Screening feature selection algorithm and Cox proportional hazards model. Main results. The models showed high predictive performance for overall survival (OS) and recurrence-free survival (RFS) in both epithelial and nonepithelial ovarian cancer, with concordance indices ranging from 0.773 to 0.794. Radiomic scores predicted 2 year OS and RFS risk groups with significant survival differences (log-rank test, P < 1.0 × 10−4 for both validation cohorts). OS and RFS hazard ratios between low- and high-risk groups were 15.994 and 30.692 (internal cohort) and 19.339 and 19.760 (external cohort), respectively. The improved performance of these newly developed prognostic models was mainly attributed to the use of multiple preoperative ultrasound images from the same patient to generate statistical radiomic features, rather than simply using the largest tumor region of interest among them. The models also revealed that the roundness of tumor lesion shape was positively correlated with prognosis for ovarian cancer. Significance. The newly developed prognostic models based on statistical radiomic features from ultrasound images were highly predictive of the risk of cancer-related death and possible recurrence not only for patients with epithelial ovarian cancer but also for those with nonepithelial ovarian cancer. They thereby provide reliable, non-invasive markers for individualized prognosis evaluation and clinical decision-making for patients with ovarian cancer.

Early re-emerging tremor after MRgFUS thalamotomy: case-control analysis of procedural and imaging features.

This study aimed to identify possible prognostic factors determining early tremor relapse after Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS) thalamotomy in patients with essential tremor (ET) and Parkinson's disease (PD). Nine patients (six ET and three PD) who underwent Vim MRgFUS thalamotomy in a single institution and developed early re-emergent tremor were analyzed. A control group of patients matched pairwise for sex, pathology, age, disease duration, and skull density ratio (SDR) was selected to compare the technical-procedural data and MR imaging evidence. MR imaging findings compared between groups included lesion shape and volume in multiparametric sequences, as well as Fractiona Anisotropy (FA) and Apparent Diffusion Coefficient (ADC) values derived from Diffusion Tensor Imaging Diffusion Weighted Imaging (DTI) and Diffusion Weighted Imaging (DWI) sequences. We did not find statistically significant differences in gender and age between the two groups. Technical and procedural parameters were also similar in both treatment groups. In MRI analysis, we found lesions of similar size but with greater caudal extension in the control group with stable outcomes compared to patients with tremor relapse. In our analysis of early recurrences after thalamotomy with focused ultrasound, there were neither technical and procedural differences nor prognostic factors related to lesion size or ablation temperatures. Greater caudal extension of the lesion in patients without recurrence might suggest the importance of spatial consolidation during treatment.

MRI of Soft-Tissue Tumors: What to Include in the Report.

MRI serves as a critical step in the workup, local staging, and treatment planning of extremity soft-tissue masses. For the radiologist to meaningfully contribute to the management of soft-tissue masses, they need to provide a detailed list of descriptors of the lesion outlined in an organized report. While it is occasionally possible to use MRI to provide a diagnosis for patients with a mass, it is more often used to help with determining the differential diagnosis and planning of biopsies, surgery, radiation treatment, and chemotherapy (when provided). Each descriptor on the list outlined in this article is specifically aimed to assist in one or more facets of the overall approach to soft-tissue masses. This applies to all masses, but in particular sarcomas. Those descriptors are useful to help narrow the differential diagnosis and ensure concordance with a pathologic diagnosis and its accompanying grade assignment of soft-tissue sarcomas. These include a lesion's borders and shape, signal characteristics, and contrast enhancement pattern; the presence of peritumoral edema and peritumoral enhancement; and the presence of lymph nodes. The items most helpful in assisting surgical planning include a lesion's anatomic location, site of origin, size, location relative to a landmark, relationship to adjacent structures, and vascularity including feeding and draining vessels. The authors provide some background information on soft-tissue sarcomas, including their diagnosis and treatment, for the general radiologist and as a refresher for radiologists who are more experienced in tumor imaging. ©RSNA, 2024 See the invited commentary by Murphey in this issue.

Classification of cervical lesions based on multimodal features fusion

Cervical cancer is a severe threat to women's health worldwide with a long cancerous cycle and a clear etiology, making early screening vital for the prevention and treatment. Based on the dataset provided by the Obstetrics and Gynecology Hospital of Fudan University, a four-category classification model for cervical lesions including Normal, low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL) and cancer (Ca) is developed. Considering the dataset characteristics, to fully utilize the research data and ensure the dataset size, the model inputs include original and acetic colposcopy images, lesion segmentation masks, human papillomavirus (HPV), thinprep cytologic test (TCT) and age, but exclude iodine images that have a significant overlap with lesions under acetic images. Firstly, the change information between original and acetic images is introduced by calculating the acetowhite opacity to mine the correlation between the acetowhite thickness and lesion grades. Secondly, the lesion segmentation masks are utilized to introduce prior knowledge of lesion location and shape into the classification model. Lastly, a cross-modal feature fusion module based on the self-attention mechanism is utilized to fuse image information with clinical text information, revealing the features correlation. Based on the dataset used in this study, the proposed model is comprehensively compared with five excellent models over the past three years, demonstrating that the proposed model has superior classification performance and a better balance between performance and complexity. The modules ablation experiments further prove that each proposed improved module can independently improve the model performance.

Domain base dynamic convolution and distance map guidance for anterior mediastinal lesion segmentation

The automatic segmentation of anterior mediastinal lesions in the enhanced CT image plays a significant role in clinical diagnosis. Due to the low incidence rate of anterior mediastinal disease, the data for training segmentation network may come from different hospitals, different equipment, and different operators, which leads to lower generalization and robustness of the trained network. This paper proposes an anterior mediastinal lesion segmentation method based on domain-adaptive dynamic convolution and distance map guidance. Considering the diversity of clinical data sources and equipment differences, the domain prior knowledge is added to the global average-pooling layer of the network, and the dynamic convolution forms specific network parameters for specific domains to enhance domain-specific information. Meanwhile, the Singed Distance Map (SDM) head is involved in the network according to the shape, size and position of the anterior mediastinal lesions to constraint the boundary and assist in localization. Ablation experiments demonstrate that the distance map can effectively constrain the segmentation target and reduce false positives. Both qualitative and quantitative experimental results indicate that our method can achieve more accurate anterior mediastinal lesion segmentation with greater generalization ability. Our approach achieves an overall Dice coefficient of 88.33%, which is 2.31% higher than existing state-of-the-art methods, and has achieved good performance in terms of ASSD evaluation for segmentation edges.

Follow-up results of BI-RADS 3 lesions on magnetic resonance imaging: a retrospective study

The categorization of Breast Imaging Reporting and Data System (BI-RADS) 3 lesions is not as clear in magnetic resonance imaging (MRI) as it is in mammography (MG). With the increasing number of MRI scans currently being conducted globally, incidentally detected lesions falling into the probably benign category are frequently being observed. In this study, our aim was to investigate the imaging characteristics and follow-up results of BI-RADS 3 lesions detected by MRI and to determine their malignancy rates. Breast MRI scans performed between January 2010 and January 2020 and classified as BI-RADS 3 lesions were retrospectively analyzed. The study included 216 lesions with known biopsy or surgical excision results or with at least one year of radiological follow-up. We assessed the patients' age, the presence of breast cancer, the follow-up interval, and the imaging findings at the beginning and during the follow-up. Lesions that remained stable, disappeared, or decreased in size and had a benign histopathological diagnosis were classified as benign. Lesions with the histopathological diagnosis of malignancy, identified by either biopsy or surgical excision, were classified as malignant. We determined the malignancy rate based on the histopathology and follow-up results. Considering the follow-up results of all cases, 8% of lesions were excised, 0.5% decreased in size, 1.4% became enlarged, 17.1% disappeared, and 73% remained stable. The malignancy rate was 2.8%. A significant relationship was found between lesion shape and malignancy, as progression to malignancy was more likely in round lesions than in other types. An irregular margin, heterogeneous enhancement, and kinetic curve (type 2) features were significant for lesion upgrade to malignancy. The malignancy rate in BI-RADS 3 lesions detected by MRI is low and falls within the accepted cancer rate for MG and sonography. Changes in size, morphology, and enhancement pattern should be considered in terms of malignancy development during follow-up. The follow-up intervals should be determined on a case-by-case basis.

A non-invasive approach to skin cancer diagnosis via graphene electrical tattoos and electrical impedance tomography

Objective. Making up one of the largest shares of diagnosed cancers worldwide, skin cancer is also one of the most treatable. However, this is contingent upon early diagnosis and correct skin cancer-type differentiation. Currently, methods for early detection that are accurate, rapid, and non-invasive are limited. However, literature demonstrating the impedance differences between benign and malignant skin cancers, as well as between different types of skin cancer, show that methods based on impedance differentiation may be promising. Approach. In this work, we propose a novel approach to rapid and non-invasive skin cancer diagnosis that leverages the technologies of difference-based electrical impedance tomography (EIT) and graphene electronic tattoos (GETs). Main results. We demonstrate the feasibility of this first-of-its-kind system using both computational numerical and experimental skin phantom models. We considered variations in skin cancer lesion impedance, size, shape, and position relative to the electrodes and evaluated the impact of using individual and multi-electrode GET (mGET) arrays. The results demonstrate that this approach has the potential to differentiate based on lesion impedance, size, and position, but additional techniques are needed to determine shape. Significance. In this way, the system proposed in this work, which combines both EIT and GET technology, exhibits potential as an entirely non-invasive and rapid approach to skin cancer diagnosis.

Ultrasound features using MUSA terms and definitions in uterine sarcoma and leiomyoma: cohort study.

Timely and accurate preoperative diagnosis of uterine sarcoma will increase patient survival. The primary aim of this study was to describe the ultrasound features of uterine sarcoma compared with those of uterine leiomyoma based on the terms and definitions of the Morphological Uterus Sonographic Assessment (MUSA) group. A secondary aim was to assess the interobserver agreement for reporting on ultrasound features according to MUSA terminology. This was a retrospective cohort study of patients with uterine sarcoma or uterine leiomyoma treated in a single tertiary center during the periods 1997-2019 and 2016-2019, respectively. Demographic characteristics, presenting symptoms and surgical outcomes were extracted from patients' files. Ultrasound images were re-evaluated independently by two sonologists using MUSA terms and definitions. Descriptive statistics were calculated and interobserver agreement was assessed using Cohen's κ (with squared weights) or intraclass correlation coefficient, as appropriate. A total of 107 patients were included, of whom 16 had a uterine sarcoma and 91 had a uterine leiomyoma. Abnormal uterine bleeding was the most frequent presenting symptom (69/107 (64%)). Compared with leiomyoma cases, patients with uterine sarcoma were older (median age, 65 (interquartile range (IQR), 60-70) years vs 48 (IQR, 43-52) years) and more likely to be postmenopausal (13/16 (81%) vs 15/91 (16%)). In the uterine sarcoma cohort, leiomyosarcoma was the most frequent histological type (6/16 (38%)), followed by adenosarcoma (4/16 (25%)). On ultrasound evaluation, according to Observers 1 and 2, the tumor border was irregular in most sarcomas (11/16 (69%) and 13/16 (81%) cases, respectively), but regular in most leiomyomas (65/91 (71%) and 82/91 (90%) cases, respectively). Lesion echogenicity was classified as non-uniform in 68/91 (75%) and 51/91 (56%) leiomyomas by Observers 1 and 2, respectively, and 15/16 (94%) uterine sarcomas by both observers. More than 60% of the uterine sarcomas showed acoustic shadows (11/16 (69%) and 10/16 (63%) cases by Observers 1 and 2, respectively), whereas calcifications were reported in a small minority (0/16 (0%) and 2/16 (13%) cases by Observers 1 and 2, respectively). In uterine sarcomas, intralesional vascularity was reported as moderate to abundant in 13/16 (81%) cases by Observer 1 and 15/16 (94%) cases by Observer 2, while circumferential vascularity was scored as moderate to abundant in 6/16 (38%) by both observers. Interobserver agreement for the presence of cystic areas, calcifications, acoustic shadow, central necrosis, color score (overall, intralesional and circumferential) and maximum diameter of the lesion was moderate. The agreement for shape of lesion, tumor border and echogenicity was fair. A postmenopausal patient presenting with abnormal uterine bleeding and a new or growing mesenchymal mass with irregular tumor borders, moderate-to-abundant intralesional vascularity, cystic areas and an absence of calcifications on ultrasonography is at a higher risk of having a uterine sarcoma. Interobserver agreement for most MUSA terms and definitions is moderate. Future studies should validate the abovementioned clinical and ultrasound findings on uterine mesenchymal tumors in a prospective multicenter fashion. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

An automated methodology for whole-body, multimodality tracking of individual cancer lesions.

Objective. Manual analysis of individual cancer lesions to assess disease response is clinically impractical and requires automated lesion tracking methodologies. However, no methodology has been developed for whole-body individual lesion tracking, across an arbitrary number of scans, and acquired with various imaging modalities.Approach. This study introduces a lesion tracking methodology and benchmarked it using 2368Ga-DOTATATE PET/CT and PET/MR images of eight neuroendocrine tumor patients. The methodology consists of six steps: (1) alignment of multiple scans via image registration, (2) body-part labeling, (3) automatic lesion-wise dilation, (4) clustering of lesions based on local lesion shape metrics, (5) assignment of lesion tracks, and (6) output of a lesion graph. Registration performance was evaluated via landmark distance, lesion matching accuracy was evaluated between each image pair, and lesion tracking accuracy was evaluated via identical track ratio. Sensitivity studies were performed to evaluate the impact of lesion dilation (fixed versus automatic dilation), anatomic location, image modalities (inter- versus intra-modality), registration mode (direct versus indirect registration), and track size (number of time-points and lesions) on lesion matching and tracking performance.Main results. Manual contouring yielded 956 lesions, 1570 lesion-matching decisions, and 493 lesion tracks. The median residual registration error was 2.5 mm. The automatic lesion dilation led to 0.90 overall lesion matching accuracy, and an 88% identical track ratio. The methodology is robust regarding anatomic locations, image modalities, and registration modes. The number of scans had a moderate negative impact on the identical track ratio (94% for 2 scans, 91% for 3 scans, and 81% for 4 scans). The number of lesions substantially impacted the identical track ratio (93% for 2 nodes versus 54% for ≥5 nodes).Significance. The developed methodology resulted in high lesion-matching accuracy and enables automated lesion tracking in PET/CT and PET/MR.

Long-term follow-up demonstrates change in conformation shape of the focal choroidal excavation lesions

PurposeThis study aims to present long-term observation of 5 eyes with focal choroidal excavation (FCE), focusing on morphological changes in conformity of the lesion.MethodsA retrospective case series was conducted, including 5 eyes of 5 patients with FCE. The study utilized multimodal imaging including color fundus photography, optical coherence tomography (OCT), enhanced depth imaging OCT (EDI-OCT), fundus fluorescein angiography (FFA), fundus autofluorescence (FAF), red free imaging, and OCT angiography.ResultsThe mean age at diagnosis was 51 ± 10.65 years, with a mean follow-up period 37 ± 13.59 months. All cases were unilateral, with 1 presenting FCE as an isolated lesion, and one patient exhibiting 2 FCEs in one eye. The mean choroidal thickness measured by EDI-OCT was 268.2 ± 63.39 μm in the affected eye. One patient displayed choroidal thickening and pachyvessels. Of the 5 eyes, one had conforming and 4 non-conforming FCE. We observed a conversion in conformity in all patients, with 4 cases transitioning from non-conforming FCE to conforming type (3 spontaneously, 1 treatment-induced). In conforming FCE, a hyporeflective space appeared twice between neuroretina and retinal pigment epithelium with spontaneous regression.ConclusionWe observed change in shape from the conforming to non-conforming FCE and vice versa in all patients. We consider this small change in the hyporeflective space as non-pathologic and clinically insignificant.

Analysis of the treatment planning metrics and their correlation with morphology of intracranial lesions in Gamma Knife stereotactic radiosurgery.

Gamma Knife Radiosurgery (GKRS) has established a role in treating various benign brain pathologies. The radiosurgery planning necessitates a proper understanding of radiation dose distribution in relation to the target lesion and surrounding eloquent area. The quality of a radiosurgery plan is determined by various planning parameters. Here, we have reviewed various GKRS planning parameters and analyzed their correlation with the morphology of treated brain lesions. A total of 430 treatment plans (71 meningioma, 133 vestibular schwannoma/VS, 150 arteriovenous malformation/AVM, 76 pituitary adenoma/PA treated with GKRS between December 2013 and May 2023) were analyzed for target coverage (TC), conformity index (CI), homogeneity index (HI), and gradient index (GI). The values of CIPaddick and CILomax for PA were lower and differed significantly from meningioma, VS, and AVM. The value of HI for PA was higher and differed significantly when compared with meningioma, VS, and AVM. The values of HI for AVM were also significantly higher than VS and meningioma. The mean GI was 3.02, 2.92, 3.03, and 2.88 for meningioma, VS, AVM, and PA, respectively. The value of GI for meningioma and AVM was significantly higher when compared with the values for VS and PA. The mean TC was 0.94 for meningioma, 0.96 for VS, 0.95 for AVM, and 0.90 for PA. The value TC of PA was lower and differed significantly when compared with VS, AVM, and meningioma. Lesions with a volume of ≤1 cc had poor planning metrics as the spillage of radiation may be higher. The GKRS planning parameters depend on the size, shape, nature, and location of intracranial lesions. Therefore, each treatment plan needs to be evaluated thoroughly and a long-term follow-up is needed to establish their relation with clinical outcome.

Accuracy of Panoramic Radiography in Comparison With Cone-Beam Computed Tomography for the Detection of Idiopathic Osteosclerosis: An Original Cross-sectional Study

Background: The accuracy of radiography for the detection of bone lesions is a critical issue. This study aimed to assess the accuracy of panoramic radiography in comparison with cone-beam computed tomography (CBCT) for the detection of idiopathic osteosclerosis (IO). Methods: This cross-sectional study was conducted on imaging records of 201 patients who had both panoramic radiographs and CBCT scans. Panoramic radiographs of patients were evaluated for lesions suspected of IO. After two weeks, the accuracy of diagnoses was investigated by assessing the patients’ CBCT scans. The location, number, shape, internal structure, and size of lesions and their relationship with teeth were also assessed on CBCT scans using Romexis Viewer software, version 3.8.0. Data were analyzed by the chi-square test (alpha=0.05). Results: Of all, 73.4% of IO lesions were correctly diagnosed on panoramic radiographs, yielding an accuracy of 0.85 for this modality. IO lesions were detected in 51 patients (n=64 lesions, 25.73%), mainly located in the mandibular molar (45.3%) and premolar (29.7%) regions. All lesions were well-defined, and most of them were spherical (42.1%). The majority of them had a cortical internal structure (73.4%) and did not correlate with teeth (78.1%). The mean size of large and small diameters of lesions was 5.4 and 3.1 mm, respectively. Conclusions: Identifying the radiographic characteristics of common lesions such as IO can be a guide for dentists to avoid incorrect treatments and unnecessary biopsies. In this way, panoramic radiography with 0.85 accuracy helps in diagnosing these lesions.

MF-Net: Multiple-feature extraction network for breast lesion segmentation in ultrasound images

Objective:Breast lesion segmentation in ultrasound images is of great significance for qualitative breast lesions. However, blurred lesion boundaries, irregular lesion shapes, and similar intensity distributions between lesion and background bring challenges to accurately segmenting breast lesions. Recently, several U-Net-based variants and transformer-based networks have been applied in breast lesion segmentation. Nevertheless, these methods have three limitations: (1) Introducing mass attention mechanisms and complex operations, (2) Ignoring the capability of extracting local detail features, and (3) Ignoring fusing different global semantic information. Approach:To alleviate these challenges, we propose a novel multiple-feature extraction network named MF-Net. The core designs are as follows: (1) A transformer-based auxiliary bi-encoder models long-range dependencies, (2) A multiple-feature extraction module excavates the robust local features, and (3) A global feature enhancement module integrates different global context information. Main results:We conducted extensive experiments on three public breast lesion datasets and compared our method with twelve state-of-the-art methods. The results of comparison experiments indicate that our model achieves a 3.16% improvement in boundary accuracy with a slight lead in segmentation accuracy. Similarly, when the boundary accuracy is close, our model also gets a 3.92% improvement in segmentation accuracy. In the generalization experiments, our network also demonstrates varying degrees of superiority in segmentation accuracy and boundary precision. Significance:Our network mainly has three advantages: (1) It achieves outstanding performance in the precise segmentation of the breast lesions, (2) It focuses on exploring details such as irregular morphology and blurred boundaries of breast lesions, providing valuable insights for further clinical research, and (3) It improves performance without decreasing inference speed through the introduction of critical components.

A new height contouring method for severity prediction in cam-type hip joints: 20 subject-specific cases

Cam-type femoroacetabular impingement syndrome (FAIS) is characterised by a non-spherical continuation of the femoral head into the femoral head-neck junction and is associated with damage to the acetabular cartilage. Diagnostic methods based on cam shape are progressing from 2D radiographic measurements to 3D CT measures, providing greater insight. There is currently no consensus on how to describe the 3D cam lesion shape and subject-specific impingement mechanisms are difficult to determine.A novel 3D ‘contour’ method was used to describe the proximal femur of 20 cam-type hips. Five contours, analogous to height contours on a terrain map, were used to describe the femoral head-neck junction, capturing the progressive height of the cam lesion. From that description, the cam apex (a subject's largest alpha angle), cam extent (spread around the femoral head), cam location (position around the femoral head) and average acetabular coverage, were recorded. A previously developed hip impingement model was used to apply 126 activity-based motions to each subject-specific hip shape and predict impingement occurrence and depth of incursion past the acetabular rim. Correlations between shape measures and impingement occurrence were investigated.The two contours representing the lowest heights (close to the head best fit sphere and 1 mm greater than that) generated cam alpha angle and cam extent measurements which contained the typical clinical measures (Alpha: close to best fit 47°-98°, at 1 mm 45°–77°; Extent: close to best fit 0°–129°, at 1 mm 0°–100°). The remaining contours described the progressive height of the cam lesion up to 4 mm greater than the head radius. Impingement was predicted predominantly from the first 1 mm height of the cam, with only two subjects impinging at a cam height greater than 2 mm. Therefore, it is possible that adequate resection of the first 1 mm of cam height is the most critical in reducing a subject's impingement severity.Impingement occurrence was positively correlated with the cam apex (ρ = 0.84 close to best fit, ρ = 0.70 at 1 mm height), the cam extent (ρ = 0.68 close to best fit, ρ = 0.80 at 1 mm height) and the acetabular coverage (ρ = 0.50, at 1 mm height). However, in line with other work on cam impingement, correlations between any single shape measure and the risk of impingement were not strong enough to be used with confidence as predictive tools. This supports the further development of modelling tools which sufficiently capture the complex shape and can generate an impingement risk metric which accounts for joint motion.

Diagnosis of benign and malignant peripheral lung lesions based on a feature model constructed by the random forest algorithm for grayscale and contrast-enhanced ultrasound.

To construct a predictive model for benign and malignant peripheral pulmonary lesions (PPLs) using a random forest algorithm based on grayscale ultrasound and ultrasound contrast, and to evaluate its diagnostic value. We selected 254 patients with PPLs detected using chest lung computed tomography between October 2021 and July 2023, including 161 malignant and 93 benign lesions. Relevant variables for judging benign and malignant PPLs were screened using logistic regression analysis. A model was constructed using the random forest algorithm, and the test set was verified. Correlations between these relevant variables and the diagnosis of benign and malignant PPLs were evaluated. Age, lesion shape, size, angle between the lesion border and chest wall, boundary clarity, edge regularity, air bronchogram, vascular signs, enhancement patterns, enhancement intensity, homogeneity of enhancement, number of non-enhancing regions, non-enhancing region type, arrival time (AT) of the lesion, lesion-lung AT difference, AT difference ratio, and time to peak were the relevant variables for judging benign and malignant PPLs. Consequently, a model and receiver operating characteristic curve were constructed with an AUC of 0.92 and an accuracy of 88.2%. The test set results showed that the model had good predictive ability. The index with the highest correlation for judging benign and malignant PPLs was the AT difference ratio. Other important factors were lesion size, patient age, and lesion morphology. The random forest algorithm model constructed based on clinical data and ultrasound imaging features has clinical application value for predicting benign and malignant PPLs.

Successful magnetic resonance-guided focused ultrasound treatment of tremor in patients with a skull density ratio of 0.4 or less.

The use of magnetic resonance-guided focused ultrasound (MRgFUS) for the treatment of tremor-related disorders and other novel indications has been limited by guidelines advocating treatment of patients with a skull density ratio (SDR) above 0.45 ± 0.05 despite reports of successful outcomes in patients with a low SDR (LSDR). The authors' goal was to retrospectively analyze the sonication strategies, adverse effects, and clinical and imaging outcomes in patients with SDR ≤ 0.4 treated for tremor using MRgFUS. Clinical outcomes and adverse effects were assessed at 3 and 12 months after MRgFUS. Outcomes and lesion location, volume, and shape characteristics (elongation and eccentricity) were compared between the SDR groups. A total of 102 consecutive patients were included in the analysis, of whom 39 had SDRs ≤ 0.4. No patient was excluded from treatment because of an LSDR, with the lowest being 0.22. Lesioning temperatures (> 52°C) and therapeutic ablations were achieved in all patients. There were no significant differences in clinical outcome, adverse effects, lesion location, and volume between the high SDR group and the LSDR group. SDR was significantly associated with total energy (rho = -0.459, p < 0.001), heating efficiency (rho = 0.605, p < 0.001), and peak temperature (rho = 0.222, p = 0.025). The authors' results show that treatment of tremor in patients with an LSDR using MRgFUS is technically possible, leading to a safe and lasting therapeutic effect. Limiting the number of sonications and adjusting the energy and duration to achieve the required temperature early during the treatment are suitable strategies in LSDR patients.

Unveiling denture-induced oral lesions: A comprehensive study on classification and pain assessment.

Denture-induced oral Lesions (DIOLs) often manifests shortly after the placement or adjustment of new or realigned dentures, frequently resulting in severe pain and discomfort. This study aimed to classify DIOLs placing a particular emphasis on assessing the associated pain. A prospective case study was conducted involving 126 patients who were fitted with a total of 193 dentures of various types at the Hadassah School of Dental Medicine. All patients underwent comprehensive intra-oral examinations within 1-8 weeks following denture delivery, completed symptom questionnaires and had their medical records reviewed. Key variables documented included age, gender, overall health status, denture type, and a detailed description of the DIOLs. The description encompassed factors such as lesion location, shape, colour, size, border characteristics, ulcerative appearance, membrane coverage, 3D morphology (elevated, immersed and flat) and patient-reported Verbal Pain Score (VPS) when touching the DIOLs, when wearing the denture, and when not wearing the denture. Notably, 25.4% of denture wearers required no adjustments, while 14.4% necessitated more than three revisions. A majority (71.8%) of DIOLs cases were associated with mandibular complete dentures, primarily situated on the alveolar ridge. The mean VPS indicated a pain intensity of 7 ± 2.1, with temporary dentures in both jaws causing the most discomfort. Implant-supported overdentures were particularly painful when placed in the mandible. Additionally, VPS scores were higher among older individuals and those with prior prosthetic experiences. A significant correlation was observed between pain intensity and presence of chronic health condition (0.036). This study revealed distinct characteristics of DIOLs and highlighted the multifactorial nature of pain experienced following the development of DIOLs. Insights into the influence of patient and denture characteristics on DIOLs and pain intensity can guide healthcare professionals in optimising patient comfort and satisfaction.

Predictive value and potential association of PET/CT radiomics on lymph node metastasis of cervical cancer

Objective: Due to the information-rich nature of positron emission tomography/computed tomography (PET/CT) images, the authors hope to explore radiomics features that could distinguish metastatic lymph nodes (LNs) from hypermetabolic benign LNs, in addition to conventional indicators. Methods: PET/CT images of 106 patients with early-stage cervical cancer from 2019 to 2021 were retrospectively analyzed. The tumor lesions and LN regions of PET/CT images were outlined with SeeIt, and then radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) was used to select features. The final selected radiomics features of LNs were used as predictors to construct a machine learning model to predict LN metastasis. Results: The authors determined two morphological coefficient characteristics of cervical lesions (shape – major axis length and shape – mesh volume), one first order characteristics of LNs (first order – 10 percentile) and two gray-level co-occurrence matrix (GLCM) characteristics of LNs (GLCM – id and GLCM – inverse variance) were closely related to LN metastasis. Finally, a neural network was constructed based on the radiomic features of the LNs. The area under the curve of receiver operating characteristic (AUC-ROC) of the model was 0.983 in the training set and 0.860 in the test set. Conclusion: The authors constructed and demonstrated a neural network based on radiomics features of PET/CT to evaluate the risk of single LN metastasis in early-stage cervical cancer.

Progressive lesion necrosis is related to increasing aphasia severity in chronic stroke

BackgroundVolumetric investigations of cortical damage resulting from stroke indicate that lesion size and shape continue to change even in the chronic stage of recovery. However, the potential clinical relevance of continued lesion growth has yet to be examined. In the present study, we investigated the prevalence of lesion expansion and the relationship between expansion and changes in aphasia severity in a large sample of individuals in the chronic stage of aphasia recovery. MethodsRetrospective structural MRI scans from 104 S survivors with at least 2 observations (k = 301 observations; mean time between scans = 31 months) were included. Lesion demarcation was performed using an automated lesion segmentation software and lesion volumes at each timepoint were subsequently calculated. A linear mixed effects model was conducted to investigate the effect of days between scan on lesion expansion.Finally, we investigated the association between lesion expansion and changes on the Western Aphasia Battery (WAB) in a group of participants assessed and scanned at 2 timepoints (N = 54) using a GLM. ResultsMost participants (81 %) showed evidence of lesion expansion. The mixed effects model revealed lesion volumes significantly increase, on average, by 0.02 cc each day (7.3 cc per year) following a scan (p < 0.0001).Change on language performance was significantly associated with change in lesion volume (p = 0.025) and age at stroke (p = 0.031). The results suggest that with every 10 cc increase in lesion size, language performance decreases by 0.9 points, and for every 10-year increase in age at stroke, language performance decreases by 1.9 points. ConclusionsThe present study confirms and extends prior reports that lesion expansion occurs well into the chronic stage of stroke. For the first time, we present evidence that expansion is predictive of longitudinal changes in language performance in individuals with aphasia. Future research should focus on the potential mechanisms that may lead to necrosis in areas surrounding the chronic stroke lesion.