Current Medical Imaging - Volume 20, Issue 1, 2024

The prognosis of postoperative tumor deposits (TDs) is worse than positive lymph node metastases alone.

To detect TDs by using multiplanar high-resolution T2-weighted imaging (HRT2WI).

This retrospective study enrolled 130 patients with locally advanced rectal cancer (LARC). Using pathology-proven tumor deposits (pTDs) as the gold standard, all patients were divided into the pTDs-negative and pTDs-positive groups, the correlation of clinicopathological factors and image features [such as MRI-detected tumor deposits (mTDs), MRI-detected metastatic lymph node (mLN), MRI-detected extramural vascular invasion (mEMVI), maximal extramural depth (EMD), etc.] with pTDs were analyzed by univariate analysis and multivariate binary logistic regression analysis, and the nomogram was established based on the latter. The diagnostic efficiency was evaluated by the receiver operating characteristic curve (ROC) analysis and area under curve (AUC).

mTDs, mLN, mEMVI, and EMD were significantly different between the pTDs-positive and pTDs-negative groups (P < 0.05), with the AUC of 0.767, 0.746, 0.664 and 0.644, respectively. mTDs and mLN were independent risk factors for pTDs (odds ratio: 5.74 and 3.90, P < 0.05). The AUC, sensitivity, specificity, negative predictive value, and accuracy of the nomogram were 0.814 (95% CI: 0.720 ~ 0.908), 73.9%, 79.4%, 93.4%, and 78.5%, respectively. Seventeen of 23 patients with pTDs were identified as mTDs, with a moderate agreement between pTDs and mTDs (Kappa=0.419).

Multiplanar HRT2WI can be used as a preoperative diagnostic tool to identify TDs in LARC. The combined model constructed by mTDs and mLN shows a good diagnostic performance for TDs.

The jaws can be affected by several lesions that manifest in the oral cavity, but little is known about non-odontogenic benign and malignant lesions and their radiological findings.

Our aim was to discuss the imaging findings of non-odontogenic jaw lesions to help the surgeon in the diagnosis and formulating a differential diagnosis for this vast spectrum of jaw lesions with overlapping clinical and imaging appearances.

CT and MR images of the mandible, maxillofacial region, and neck were retrieved from the archive of the Radiology Department of Pamukkale University for the duration between 2012-2023 and assessed.

A total of 8125 CT and MR images were retrospectively analyzed. The mean age of the patients was 39.5 years in females and 43.2 in males, with a range varying from 15 to 72 years. Histopathologically approved benign and malignant non-odontogenic lesions were detected in only 19 patients out of 8125 images (0.23%). Osteomyelitis and abscess were the most common (n=3; 0.03%), followed by two cases (n=2; 0.02%) of each fibrous dysplasia, hemangioma, osteosarcoma, squamous cell carcinoma, and multiple myeloma, and one case (n=1; 0.01%) of each ossifying fibroma, osteoma, lymphoma, metastasis, and solitary bone cyst.

Although non-odontogenic benign and malignant lesions of the jaw are rare, awareness of the radiological features of these lesions plays an important role in their diagnosis and management.

The present study aimed to analyze mammography and ultrasonography (US) manifestations of sclerosing lymphocytic lobulitis (SLL) of the breast.

A total of 8 pathologically confirmed SLL lesions from seven women (with one patient having bilateral breast lesions) were included in the study. All patients underwent preoperative mammography and US examinations. The findings from both modalities were classified and compared to their corresponding clinical data.

Four patients were diagnosed with diabetes mellitus. Mammography results revealed that seven lesions presented as focal asymmetry or asymmetry. Seven lesions were observed as non-mass lesions on US examination. The most commonly observed US lesion features were as follows: seven lesions had focal non-ductal hypoechoic areas (87.5%), seven lesions exhibited posterior shadowing (87.5%), all lesions showed no vascularity or vessels in the rim (100%), no lesion had calcifications (0%), five lesions had an elasticity score of 3 (100%), one lesion showed retraction on the coronal plane (20%), and one lesion displayed a skipping sign on the coronal plane (20%). Based on these US findings, seven lesions (87.5%) were classified as BI-RADS 4.

The mammography findings for SLL are often nonspecific. However, the US features of SLL typically present as non-mass lesions. The absence of calcification and vascularity and no retraction on the coronal plane inside the lesion may help to differentiate this disease from the conventional forms of breast carcinoma.

Ganglioglioma is a rare, slowly proliferating mixed glioneuronal tumor, with the highest incidence observed in children and young adults, but it can also occur in adults.

This study aimed to compare the imaging characteristics of ganglioglioma in children/adolescents and adults to facilitate radiographic diagnosis.

In this retrospective study, a total of 32 patients were included and divided into two groups: the child/adolescent group (age < 18 years, n=19) and the adult group (age ≥ 18 years, n=13). Various variables were analyzed, including maximum diameter, location, periphery, border, calcification, unenhanced CT attenuation, T1WI, T2WI/FLAIR, and DWI signal intensity, enhancement pattern, degree of enhancement, homogeneity of enhancement, solid/cystic component, peri-tumoral edema, intra-tumoral septa, peri-tumoral capsule, and intra-tumoral hemorrhage.

Most gangliogliomas were situated in the peripheral regions, particularly in the temporal lobe. The majority exhibited hypointense/isointense signals on T1WI and hyperintense signals on T2WI/FLAIR and DWI, with predominantly heterogeneous nodular enhancement. Peri-tumoral edema was significantly less frequent in the child/adolescent group, while marked enhancement was significantly more common in the adult group. There was no significant difference in maximum diameter between the child/adolescent group and the adult group.

Peri-tumoral edema was significantly less prevalent in the child/adolescent group, whereas marked enhancement was significantly more frequent in the adult group. To ensure accurate results, a larger case series should be conducted to validate our findings.

This study aimed to develop a method for predicting short-term outcomes of lung cancer patients treated with intensity-modulated radiotherapy (IMRT) using radiomic features detected through computed tomography images.

A prediction model was developed based on a dataset of radiomic features obtained from 132 patients with lung cancer receiving IMRT. Dimension reduction was performed for the features using the maximum-relevance and minimum-redundancy (mRMR) algorithm, and the least absolute shrinkage and selection operator (LASSO) regression model was utilized to optimize feature selection for the IMRT-sensitivity prediction model. The model was constructed using binary logistic regression analysis and was evaluated using the concordance index (C-index), calibration plots, receiver operating characteristic curve, and decision curve analysis.

Fifty features were selected from 1348 radiomic features using the mRMR method. Of these, three radiomic features were selected by LASSO logistic regression to construct the radiomics nomogram. The C-index of the model was 0.776 (95% confidence interval: 0.689–0.862) and 0.791 (95% confidence interval: 0.607–0.974) in the training and validation cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful.

Radiomic features have the potential to be applied to predict the short-term efficacy of IMRT in patients with inoperable lung cancer.

The objective of this study was to investigate the diagnostic power of apparent diffusion coefficient/coefficient of variance (ADCcV) as well as ADC parameters formed based on magnetic resonance images (MRI) in the distinction of molecular breast cancer subtypes.

The study involved 205 patients who had breast cancer at stages 1-3. Estrogen receptor (EsR), progesterone receptor (PrR), human epidermal growth factor receptor 2 (Her2), and proliferation index (Ki-67) were histologically analyzed in the tumor. The correlations between the immunohistochemistry and intrinsic subtypes were analyzed using ADC and ADCcV.

The maximum whole tumor (WTu) ADC (p=0.004), minimum WTu ADC (p<0.001), and mean WTu ADC (p<0.001) values were significantly smaller in the EsR-positive tumors than those in the EsR-negative tumors. Compared to the PrR-negative tumors, the PrR-positive tumors showed significantly smaller maximum, minimum, and mean WTu ADC values (p=0.005, p=0.001, and p<0.001, respectively). In the comparisons of the molecular subtypes in terms of ADCcV, the p-values indicated statistically significant differences between the luminal A (lumA) group and the triple negative (TN) group, between the luminal B (lumB) group and the TN group, and between the Her2-enriched and TN groups (p<0.001, p=0.011, and p=0.004, respectively). Considering the luminal and non-luminal groups, while a significant difference was observed between the groups considering their minimum, maximum, and mean WTu ADC values, their ADCcV values were similar (p<0.001, p=0.004, and p<0.001, respectively).

Using ADCcV in addition to ADC parameters increased the diagnostic power of diffusion weighted-MRI (DW-MRI) in the distinction of molecular subtypes of breast cancer.

Few studies have focused on the changes in human brain function activities caused by reading Chinese characters with different intelligibility and whether it can reflect the understanding and cognitive ability of the human brain.

Task-fMRI based on Chinese character reading tasks with different intelligibility was used to explore activated brain regions and their cognitive changes.

Volunteers were randomly recruited using advertisements. Forty volunteers were recruited based on strict inclusion and exclusion criteria, and 40 volunteers were recruited. Brain function data of 40 healthy right-handed volunteers in fuzzy/clear Chinese reading tasks were collected using a Siemens Skyra 3.0T magnetic resonance scanner. Data were preprocessed and statistically analyzed using the statistical software SPM12.0 to observe the activation of the cortex and analyze its characteristics and possible changes in cognitive function.

Task-fMRI analysis: (1) The main brain regions activated in fuzzy/clear reading tasks were located in the occipital visual cortex (P < 0.001); (2) a paired sample t-test suggested that there was a significant difference in BOLD signals in the brain regions activated by fuzzy/clear reading tasks (P < 0.001, equiv Z = 4.25). Compared with the fuzzy reading task, the brain regions more strongly activated in the clear reading task were mainly located in the right superior frontal gyrus and the bilateral temporal lobe. Compared with the clear reading task, the brain region that was more strongly activated in the fuzzy reading task was mainly located in the right fusiform gyrus.

Clear Chinese character information mainly activates the dorsal stream of the visual-spatial network. This reflects the information transmission of the brain after understanding the text content and is responsible for guiding and controlling attention. Fuzzy words that cannot provide clear text content activate the fusiform gyrus of the ventral stream of the visual-spatial network, strengthening the function of orthographic processing.

Among all cancer forms, gastrointestinal (GI) cancer is the most serious condition that spreads quickly and requires early detection. GI disorders claim the lives of up to nearly two million people worldwide. To lower the mortality rate from GI cancer, early detection is essential.

For the identification of GI illnesses, such as polyps, stomach ulcers, and bleeding, endoscopy is the gold standard in the medical imaging industry. The numerous images produced by endoscopy require an enormous amount of time for the specialist to diagnose the disease. It makes manual diagnosis difficult and has sparked research on automatic computer-based approaches to diagnose all the generated images quickly and accurately. AI-based algorithms have already been used in endoscopy images with promising outcomes and have enhanced disease identification and classification with precision. However, there are still a lot of issues to be solved, including figuring out potential biases in algorithms and improving interpretability and generalizability.

The proposed GastroNet model creates a system for classifying digestive problems for the Kvasir Version 1 dataset. The framework consists of different CNN layers with multiple filters, and average max-pooling is used to extract image features. The optimization of network parameters is done using the Stochastic Gradient Descent (SGD) algorithm.

Finally, the robustness of the proposed model is compared with other state-of-the-art models like VGG 19, ResNet 50, Inception, and Xception in terms of evaluation metrics.

To analyze the efficacy of microwave ablation (MWA) guided by computed tomography (CT) and 1.5T magnetic resonance (MR) in the treatment of VX2 para-vascular liver tumor model in rabbits.

Sixty para-vascular VX2 liver tumor models in rabbits were randomly divided into CT-guided microwave ablation group (CT group, n=35) and MR-guided microwave ablation group (MR group, n=35). The complete ablation rate, mean operation time, postoperative complication rate and mean survival time were compared between the two groups.

In the CT group, the rate of complete ablation was 68.6% (24/35), and the mean operation time was 42.1 ± 9.7 minutes. Three cases had ascites and one case had abdominal wall injury. In the MR group, the rate of complete ablation was 94.2% (33/35), and the mean operation time was 53.4 ± 10.9 minutes. One case was complicated with ascites. No serious complications such as pneumothorax, liver abscess, pleural effusion and diaphragm perforation were found in both groups. Between the two groups, the difference in complete ablation rate was statistically significant (P=0.006 < 0.05). A statistically significant difference can also be found in mean operation time (P < 0.01). The follow-up time was 21 days after the operation. As for the postoperative complication rate (11.4% in the CT group and 2.9% in the MR group, P=0.353) and mean survival time (16.9 ± 1.8 days in CT group, 18.3 ± 2.3 days in the MR group, P=0.925), the differences were not statistically significant.

Compared with CT guidance, although the microwave ablation time under MR guidance was longer, the complete ablation rate under MR guidance was high, which proved that MR guidance was a more effective way of microwave ablation guidance and was worth promoting in the clinic. In this experiment, the postoperative complication rate was lower in the MR group, although the difference was not statistically significant, which may be related to the small sample size, and the subsequent study on the postoperative complication rate can increase the sample content.

Extraprostatic extension (EPE) serves as a crucial marker of prostate cancer aggressiveness and independently predicts the likelihood of biochemical recurrence (BCR), exhibiting a strong correlation with the histologic severity of EPE. Therefore, this study aimed to investigate the probability of EPE along the zonal level of the prostate by measuring tumor contact length (TCL) using multiparametric magnetic resonance imaging (mpMRI).

Records of 308 patients who had undergone radical prostatectomy (RP) were identified. Tumor levels in the prostate were categorized as apex, mid-gland, and base, after which the correlation between TCL measured using MRI and microscopic EPE on pathologic specimens was evaluated. Univariable and multivariable logistic regression analyses were performed to assess the association among tumor origin, index tumor diameter, and TCL measured using MRI and microscopic EPE in RP specimens.

Among the 214 patients included, 45 apical cancers (21%), 87 mid-gland cancers (41%), and 82 base cancers (38%) were observed. Pathological reports revealed that 18 (40.0%) apex, 31 (35.6%) mid-gland, and 50 (61.0%) base tumors were pT3a. Multivariable analysis demonstrated that the zonal level of the tumor, especially the base level, was an independent predictive factor for EPE (P < 0.001), and the AUC value of the base tumor was 0.858.

Prostate cancers arising from the base were more likely to exhibit EPE than those arising from the mid-gland and apex of the prostate gland. Therefore, identifying the origin of the zonal level of prostate cancer may help guide treatment decisions and predict clinical prognosis.

The composition of kidney stones is related to the hardness of the stones. Knowing the composition of the stones before surgery can help plan the laser power and operation time of percutaneous nephroscopic surgery. Moreover, patients can be treated with medications if the kidney stone is compounded by uric acid before treatment, which can relieve the patients of the pain of surgery. However, although the literature generally reports the kidney stone composition analysis method base on dual-energy CT images, the accuracy of these methods is not enough; they need manual delineation of the kidney stone location, and these methods cannot analyze mixed composition kidney stones.

This study aimed to overcome the problem related to identifying kidney stone composition; we need an accurate method to analyze the composition of kidney stones.

In this paper, we proposed the automatic kidney stone composition analysis algorithm based on a dual-energy CT image. The algorithm first segmented the kidney stone mask by deep learning model, then analyzed the composition of each stone by machine learning model.

The experimental results indicate that the proposed algorithm can segment kidney stones accurately (AUC=0.96) and predict kidney stone composition accurately (mean Acc=0.86, mean Se=0.75, mean Sp=0.9, mean F1=0.75, mean AUC=0.83, MR (Exact match ratio)=0.6).

The proposed method can predict the composition and location of kidney stones, which can guide its treatment.

Experimental results show that the weighting strategy can improve kidney stone segmentation performance. In addition, the multi-label classification model can predict kidney stone composition precisely, including the mixed composition kidney stones.

Budd-Chari syndrome (BCS) is a rare condition defined by the obstruction of hepatic venous outflow. BCS is a relatively infrequent cause of acute liver failure (ALF), accounting for less than 1% of cases. Treatment for acute BCS consists of a stepwise approach, requiring anticoagulation, angioplasty, transjugular intrahepatic portosystemic shunt (TIPS), and liver transplantation.

We present the case of a 31-year-old female patient with BCS, which led to ALF and subsequent multiple organ failure, which was successfully treated with TIPS and endovascular coil placement. Initial diagnostic workup revealed the complete obstruction of the hepatic venous outflow, spleno-mesenteric confluent thrombosis, and biochemical criteria of ALF. Her condition rapidly deteriorated towards multiple organ failure. At one point, the MELD score was 42, while the SOFA score predicted a mortality rate of >95%. Following continuous venovenous hemodiafiltration with cytokine adsorbent filters, TIPS was inserted, resulting in a portal pressure gradient (PPG) of 14 mmHg. Following TIPS, the patient had persistent ascites and later presented an episode of gastric variceal bleeding with endoscopic and surgical treatment failure. TIPS revision with further dilation led to a final PPG of 6 mmHg. During the procedure, selective embolization by coil placement of the spleno-gastric collateral circulation ultimately resolved the variceal bleeding. In the aftermath, the patient had complete organ failure remission and was successfully discharged with no ascites, encephalopathy, or significant impairment regarding daily life activities.

In the rare setting of BCS complicated with ALF and portal hypertension-related complications, TIPS and endovascular embolization provide a unique, effective, and against-all-odd solution.

Compared thyroid volumes measured by 2-D and 3-D US with those of resected specimens and proposed new models to improve measurement accuracy.

This study included 80 patients who underwent total thyroidectomy. One 2D_model and one 3D_model were developed using piecewise linear regression analysis. The accuracy of these models was compared using an ellipsoid model (2-D_US value × 0.5), 3-D_US value, and Ying’s model [1.76 + (2-D_US value × 0.38)].

The new 2D_model was: V=2.66 + (0.71 * X1) - (1.51 * X2). In this model, if 2-D_US value <= 228.39, X1 = 2-D_US value and X2 = 0; otherwise, X1 = 2-D_US value and X2 = 2-D_US value - 228.39. The 3D_model was: V= 2.90 + (1.08 * X1) + (2.43 * X2). In this model, if 3-D_US value <= 102.06, X1 = 3-D_US value and X2 = 0; otherwise, X1 = 3-D_US value and X2 = 3-D_US value - 102.06. The accuracy of the new models was higher than that of the 3-D_US value, the ellipsoid model, and Ying’s model (P<0.05).

The models established are more accurate than the traditional ones and can accurately measure thyroid volume.

The study aimed to explore an approach for accurately assembling high-quality lymph node clinical target volumes (CTV) on CT images in cervical cancer radiotherapy with the encoder-decoder 3D network.

216 cases of CT images treated at our center between 2017 and 2020 were included as a sample, which were divided into two cohorts, including 152 cases and 64 cases, respectively. Para-aortic lymph node, common iliac, external iliac, internal iliac, obturator, presacral, and groin nodal regions were delineated as sub-CTV manually in the cohort including 152 cases. Then, the 152 cases were randomly divided into training (96 cases), validation (36 cases), and test (20 cases) groups for the training process. Each structure was individually trained and optimized through a deep learning model. An additional 64 cases with 6 different clinical conditions were taken as examples to verify the feasibility of CTV generation based on our model. Dice similarity coefficient (DSC) and Hausdorff distance (HD) metrics were both used for quantitative evaluation.

Comparing auto-segmentation results to ground truth, the mean DSC value/HD was 0.838/7.7mm, 0.853/4.7mm, 0.855/4.7mm, 0.844/4.7mm, 0.784/5.2mm, 0.826/4.8mm and 0.874/4.8mm for CTV_PAN, CTV_common iliac, CTV_internal iliac, CTV_external iliac, CTV_obturator, CTV_presacral, and CTV_groin, respectively. The similarity comparison results of six different clinical situations were 0.877/4.4mm, 0.879/4.6mm, 0.881/4.2mm, 0.882/4.3mm, 0.872/6.0mm, and 0.875/4.9mm for DSC value/HD, respectively.

We have developed a deep learning-based approach to segmenting lymph node sub-regions automatically and assembling high-quality CTVs according to clinical needs in cervical cancer radiotherapy. This work can increase the efficiency of the process of cervical cancer detection and treatment.