Association Between Body Composition and Survival in Patients With Gastroesophageal Adenocarcinoma: An Automated Deep Learning Approach.

PURPOSE: Body composition (BC) may play a role in outcome prognostication in patients with gastroesophageal adenocarcinoma (GEAC). Artificial intelligence provides new possibilities to opportunistically quantify BC from computed tomography (CT) scans. We developed a deep learning (DL) model for fully automatic BC quantification on routine staging CTs and determined its prognostic role in a clinical cohort of patients with GEAC. MATERIALS AND METHODS: We developed and tested a DL model to quantify BC measures defined as subcutaneous and visceral adipose tissue (VAT) and skeletal muscle on routine CT and investigated their prognostic value in a cohort of patients with GEAC using baseline, 3-6-month, and 6-12-month postoperative CTs. Primary outcome was all-cause mortality, and secondary outcome was disease-free survival (DFS). Cox regression assessed the association between (1) BC at baseline and mortality and (2) the decrease in BC between baseline and follow-up scans and mortality/DFS. RESULTS: Model performance was high with Dice coefficients ≥0.94 ± 0.06. Among 299 patients with GEAC (age 63.0 ± 10.7 years; 19.4% female), 140 deaths (47%) occurred over a median follow-up of 31.3 months. At baseline, no BC measure was associated with DFS. Only a substantial decrease in VAT >70% after a 6- to 12-month follow-up was associated with mortality (hazard ratio [HR], 1.99 [95% CI, 1.18 to 3.34]; P = .009) and DFS (HR, 1.73 [95% CI, 1.01 to 2.95]; P = .045) independent of age, sex, BMI, Union for International Cancer Control stage, histologic grading, resection status, neoadjuvant therapy, and time between surgery and follow-up CT. CONCLUSION: DL enables opportunistic estimation of BC from routine staging CT to quantify prognostic information. In patients with GEAC, only a substantial decrease of VAT 6-12 months postsurgery was an independent predictor for DFS beyond traditional risk factors, which may help to identify individuals at high risk who go otherwise unnoticed.

Krukenburg tumour: Role of 18F-FDG PET/CT in identifying the primary site.

Krukenberg tumours are a rare form of metastatic tumours of the ovary. They primary site is usually the gastro-intestinal system with the most common being gastric cancer. We present the case of a 35-year-old female coming in with a large pelvi-abdominal mass for investigation. This pelvic mass showed mild to moderate metabolic activity. 18F-FDG PET-CT was able to identify the primary gastric carcinoma. Subsequent histopathology confirmed this to be gastric adenocarcinoma with metastases to the ovary.

Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.

Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcinoma at CT informs clinical management decisions but may be challenging for classifying pure ground-glass nodules (pGGNs). Deep learning (DL) may improve ternary classification. Purpose To determine whether a strategy that includes an adjudication approach can enhance the performance of DL ternary classification models in predicting the invasiveness of adenocarcinoma at chest CT and maintain performance in classifying pGGNs. Materials and Methods In this retrospective study, six ternary models for classifying preinvasive, minimally invasive, and invasive adenocarcinoma were developed using a multicenter data set of lung nodules. The DL-based models were progressively modified through framework optimization, joint learning, and an adjudication strategy (simulating a multireader approach to resolving discordant nodule classifications), integrating two binary classification models with a ternary classification model to resolve discordant classifications sequentially. The six ternary models were then tested on an external data set of pGGNs imaged between December 2019 and January 2021. Diagnostic performance including accuracy, specificity, and sensitivity was assessed. The χ2 test was used to compare model performance in different subgroups stratified by clinical confounders. Results A total of 4929 nodules from 4483 patients (mean age, 50.1 years ± 9.5 [SD]; 2806 female) were divided into training (n = 3384), validation (n = 579), and internal (n = 966) test sets. A total of 361 pGGNs from 281 patients (mean age, 55.2 years ± 11.1 [SD]; 186 female) formed the external test set. The proposed strategy improved DL model performance in external testing (P < .001). For classifying minimally invasive adenocarcinoma, the accuracy was 85% and 79%, sensitivity was 75% and 63%, and specificity was 89% and 85% for the model with adjudication (model 6) and the model without (model 3), respectively. Model 6 showed a relatively narrow range (maximum minus minimum) across diagnostic indexes (accuracy, 1.7%; sensitivity, 7.3%; specificity, 0.9%) compared with the other models (accuracy, 0.6%-10.8%; sensitivity, 14%-39.1%; specificity, 5.5%-17.9%). Conclusion Combining framework optimization, joint learning, and an adjudication approach improved DL classification of adenocarcinoma invasiveness at chest CT. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Sohn and Fields in this issue.

[Ascending colon cancer with submucosal tumor-like morphology arising near ileal valve lipohyperplasia:a case report].

An 89-year-old man was diagnosed with a submucosal tumor suspected to be a lipoma and was followed up for 6 years. The patient was admitted to the hospital because of increased tumor size and morphological changes despite negative bioptic findings. The lesion was diagnosed as an advanced adenocarcinoma of the ascending colon (cT3N0M0, cStage IIa). Laparoscopic-assisted right hemicolectomy with D3 lymph node dissection was performed. Pathological diagnosis of a surgically resected specimen revealed adenocarcinoma with lipohyperplasia (pT3N2aM0, pStage IIIb). Reports of colon cancer accompanied by colonic lipomas or lipohyperplasia are limited. This case showed an interesting submucosal tumor-like morphology because the cancer developed at the base of the lipohyperplasia and grew and spread below it.

Machine learning for differentiating lung squamous cell cancer from adenocarcinoma using Clinical-Metabolic characteristics and 18F-FDG PET/CT radiomics.

Noninvasive differentiation between the squamous cell carcinoma (SCC) and adenocarcinoma (ADC) subtypes of non-small cell lung cancer (NSCLC) could benefit patients who are unsuitable for invasive diagnostic procedures. Therefore, this study evaluates the predictive performance of a PET/CT-based radiomics model. It aims to distinguish between the histological subtypes of lung adenocarcinoma and squamous cell carcinoma, employing four different machine learning techniques. A total of 255 Non-Small Cell Lung Cancer (NSCLC) patients were retrospectively analyzed and randomly divided into the training (n = 177) and validation (n = 78) sets, respectively. Radiomics features were extracted, and the Least Absolute Shrinkage and Selection Operator (LASSO) method was employed for feature selection. Subsequently, models were constructed using four distinct machine learning techniques, with the top-performing algorithm determined by evaluating metrics such as accuracy, sensitivity, specificity, and the area under the curve (AUC). The efficacy of the various models was appraised and compared using the DeLong test. A nomogram was developed based on the model with the best predictive efficiency and clinical utility, and it was validated using calibration curves. Results indicated that the logistic regression classifier had better predictive power in the validation cohort of the radiomic model. The combined model (AUC 0.870) exhibited superior predictive power compared to the clinical model (AUC 0.848) and the radiomics model (AUC 0.774). In this study, we discovered that the combined model, refined by the logistic regression classifier, exhibited the most effective performance in classifying the histological subtypes of NSCLC.

Adenocarcinoma originating in the anterior mediastinum diagnosed by endobronchial ultrasound-guided transbronchial cryobiopsy: a case report.

BACKGROUND: Endobronchial ultrasound-guided transbronchial cryobiopsy (EBUS-cryobiopsy) is advantageous for collecting larger specimens with minimal crushing; however, it has not been widely used for mediastinal tumors. CASE PRESENTATION: A 73-year-old woman with a history of left breast cancer underwent surgery followed by radiotherapy. Computed tomography showed a mass in the anterior mediastinum that was in extensive contact with the sternum on the ventral side and partly with the trachea on the dorsal side. Two computed tomography-guided needle biopsies (CTNBs) were performed on the mass; however, a definitive diagnosis was not made because of severe crush artifacts. Subsequently, we performed EBUS-cryobiopsy and safely obtained sufficient specimen volume with minimal crushing. The histopathological diagnosis was adenocarcinoma, with immunobiological features distinct from those of previous breast cancers. Her overall diagnosis was a rare tumor originating in the anterior mediastinum. CONCLUSIONS: EBUS-cryobiopsy can be safely performed in narrow areas surrounded by major blood vessels, and the obtained specimens may be superior to CTNBs for histopathological diagnosis.

Short- and long-term outcomes after distal pancreatectomy with radiologic infiltration of splenic vessels for pancreatic ductal adenocarcinoma.

BACKGROUND: The effect of radiologic splenic vessels involvement (RSVI) on the survival of patients with pancreatic adenocarcinoma (PAC) located in the body and tail of the pancreas is controversial, and its influence on postoperative morbidity after distal pancreatectomy (DP) is unknown. This study aimed to determine the influence of RSVI on postoperative complications, overall survival (OS), and disease-free survival (DFS) in patients undergoing DP for PAC. METHODS: A multicenter retrospective study of DP was conducted at 7 hepatopancreatobiliary units between January 2008 and December 2018. Patients were classified according to the presence of RSVI. A Clavien-Dindo grade of >II was considered to represent a major complication. RESULTS: A total of 95 patients were included in the analysis. Moreover, 47 patients had vascular infiltration: 4 had arterial involvement, 10 had venous involvement, and 33 had both arterial and venous involvements. The rates of major complications were 20.8% in patients without RSVI, 40.0% in those with venous RSVI, 25.0% in those with arterial RSVI, and 30.3% in those with both arterial and venous RSVIs (P = .024). The DFS rates at 3 years were 56% in the group without RSVI, 50% in the group with arterial RSVI, and 16% in the group with both arterial and venous RSVIs (P = .003). The OS rates at 3 years were 66% in the group without RSVI, 50% in the group with arterial RSVI, and 29% in the group with both arterial and venous RSVIs (P < .0001). CONCLUSION: RSVI increased the major complication rates after DP and reduced the OS and DFS. Therefore, it may be a useful prognostic marker in patients with PAC scheduled to undergo DP and may help to select patients likely to benefit from neoadjuvant treatment.

[Resected Right Upper Lobe Lung Cancer with Displaced Bronchus and Anomalous Pulmonary Vein].

The patient is a 77-year-old man. He was referred to our hospital after a chest computed tomography (CT) scan revealed a 6.5 cm-sized mass in the right lung apex. Bronchoscopy revealed adenocarcinoma, clinical stageⅡB, and the patient was referred for surgery. Preoperative 3D-CT revealed the presence of a displaced bronchus, probably B1a, branching from the right main bronchus centrally from the upper lobe bronchus, and an abnormal vessel (V2) running dorsal to the upper lobe bronchus and the right main bronchus, and returning directly to the left atrium. Surgery was performed by resectioning the right upper lobe through a posterolateral incision, combined resection of the wall pleura, and lymph node dissection (ND2a-2). Because lung cancer surgery is sometimes accompanied by abnormal bronchial and pulmonary vascular branches, it is essential to thoroughly examine the patient before surgery for checking abnormal branches by bronchoscopy and 3D-CT.

Preoperative ultrasound-guided dual localization with titanium clips and carbon nanoparticles for predicting the surgical approach and guiding the resection of Siewert type II esophagogastric junction adenocarcinoma.

OBJECTIVE: To investigate the superiority of preoperative ultrasound-guided titanium clip and nanocarbon dual localization over traditional methods for determining the surgical approach and guiding resection of Siewert type II adenocarcinoma of the esophagogastric junction (AEG). METHOD: This study included 66 patients with Siewert type II AEG who were treated at the PLA Joint Logistics Support Force 900th Hospital between September 1, 2021, and September 1, 2023. They were randomly divided into an experimental group (n = 33), in which resection was guided by the dual localization technique, and the routine group (n = 33), in which the localization technique was not used. Surgical approach predictions, proximal esophageal resection lengths, pathological features, and the occurrence of complications were compared between the groups. RESULT: The use of the dual localization technique resulted in higher accuracy in predicting the surgical approach (96.8% vs. 75.9%, P = 0.02) and shorter proximal esophageal resection lengths (2.39 ± 0.28 cm vs. 2.86 ± 0.39 cm, P < 0.001) in the experimental group as compared to the routine group, while there was no significant difference in the incidence of postoperative complications (22.59% vs. 24.14%, P = 0.88). CONCLUSION: Preoperative dual localization with titanium clips and carbon nanoparticles is significantly superior to traditional methods and can reliably delineate the actual infiltration boundaries of Siewert type II AEG, guide the surgical approach, and avoid excessive esophageal resection.

Correlation of CT parameters and PD-L1 expression status in gastric cancer.

OBJECTIVE: We aimed to explore the correlation between routine computed tomography (CT) imaging features and programmed cell death ligand-1(PD-L1) expression status in gastric cancer and evaluate the predictive value of imaging parameters for this immunotherapy biomarker. MATERIALS AND METHODS: Patients with gastric adenocarcinoma who underwent abdominal CT three-stage enhanced scan and PD-L1 immunohistochemical testing before treatment were retrospectively examined. All diagnoses were confirmed through pathology. According to the expression status of PD-L1, they were divided into the positive (CPS ≥ 5) or negative group (CPS < 5). Baseline CT imaging features were collected. Diagnostic performances of the different variables were evaluated using receiver operating characteristic (ROC) curve. RESULTS: In total, 67 patients (17 women and 50 men; mean age: 59.55 ± 10.22 years) with gastric adenocarcinoma were included in the study. The overall stages, probability of maximum lymph node short diameter > 1 cm and peak of lesion enhancement occurring in the arterial phase were statistically significant between the two groups (p < 0.05). Moreover, the arterial enhancement fraction (AEF) was significantly higher in the positive group than that in the negative group (p < 0.05), and ROC curve analysis showed that the AEF exhibited a high evaluation efficacy (area under the curve [AUC] = 0.724 [95% confidence interval (CI): 0.602-0.826]). The combined parameters had the best diagnostic efficacy (AUC = 0.825 [95%CI: 0.716-0.933]), sensitivity (75.00%), and specificity (81.40%). CONCLUSIONS: These findings confirm a correlation between CT imaging features and PD-L1 expression status in gastric cancer, and AEF may help evaluate high PD-L1 expression and select patients suitable for immunotherapy.

ENDOSONOGRAPHY-GUIDED RESCUE PROCEDURES AFTER FAILED ERCP IN A PATIENT WITH PANCREATIC DUCTAL ADENOCARCINOMA.

BACKGROUND: • The ERCP even when done by experienced professionals, fails in 10% of cases. BACKGROUND: • Until the development of the EUS-BD, PTBD had a role as a rescue therapy, despite a high rate of adverse events. BACKGROUND: • The EUS-BD is safe and has similar efficacy, when compared to PTBD and should be performed immediately after ERCP failure. BACKGROUND: • A doctor with skills in both methods (ERCP/EUS) is needed to determine the best EUS-guided therapeutic option.

[Intravascular Large B-cell Lymphoma Presenting with Lung Adenocarcinoma:
A Case Report and Literature Review].

Intravascular large B-cell lymphoma (IVLBCL) is an aggressive extranodal large B-cell lymphoma, cocurrence in the same organ with other malignancies is very rare, especially in the lung. Here, we report a rare case of lung adenocarcinoma with IVLBCL. The patient was admitted to the hospital due to diarrhea associated with fever and cough. A computed tomography (CT) scan of the chest showed an irregular patchy high-density shadow in the upper lobe of the right lung with ground-glass opacity at the margin. After admission, the patient was given anti-infection treatment, but still had intermittent low fever (up to 37.5 °C). The pathological diagnosis of percutaneous lung biopsy (PLB) was lepidic-predominant adenocarcinoma with local infiltration, which was proved to be invasive nonmucinous adenocarcinoma of the lung with IVLBCL after surgery. This paper analyzed the clinicopathological characteristics and reviewed the relevant literature to improve the knowledge of clinicians and pathologists and avoid missed diagnosis or misdiagnosis.
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Sinonasal adenocarcinoma presented as a giant anterior cranial fossa mass: a case report and review of the literature.

BACKGROUND: Intestinal adenocarcinoma accounts for less than 0.1-4% of all malignancies in the region. It is common among woodworkers and leather workers. Sinonasal adenocarcinoma usually arises from the ethmoid sinus (40%) or nasal cavity (25%). Extension to nearby structures is common, but intracranial spread is very rare. These tumors are usually treated with surgery, with a reported 5-year survival rate of 59% to 80%. CASE PRESENTATION: This is a 60-year-old Black African male patient who presented with globalized headache, nasal obstruction with snoring during sleep, anosmia, change in mentation, sometimes agitation and left-side visual loss of one-year duration with worsening his above symptoms over the last one month. He couldn't smell soap bilaterally; in his left eye he could see only hand movement at nearly 30 cm. On brain magnetic resonance imaging, there was a T1 hypo- and T2 hyper-intense anterior cranial fossa mass arising from the left ethmoid sinuses and sphenoid sinuses and compressing the left optic structures, and brain computed tomography demonstrated heterogeneous hypo- to isodense mass. Complete tumor excision achieved and discharged with significant improvement and linked to oncology unit for radiotherapy. CONCLUSION: The management of these patients is multidisciplinary, involving neurosurgeons, otolaryngologists, oncologists, and maxillofacial surgeons. Surgical resection is the main treatment strategy, followed by radiotherapy, particularly intensity-modulated therapy. Chemotherapy is used in highly advanced, metastatic, and unresectable tumors.

TDASD: Generating medically significant fine-grained lung adenocarcinoma nodule CT images based on stable diffusion models with limited sample size.

BACKGROUND AND OBJECTIVES: Spread through air spaces (STAS) is an emerging lung cancer infiltration pattern. Predicting its spread through CT scans is crucial. However, limited STAS data makes this prediction task highly challenging. Stable diffusion is capable of generating more diverse and higher-quality images compared to traditional GAN models, surpassing the dominating GAN family models in image synthesis over the past few years. To alleviate the issue of limited STAS data, we propose a method TDASD based on stable diffusion, which is able to generate high-resolution CT images of pulmonary nodules corresponding to specific nodular signs according to the medical professionals. METHODS: First, we apply the stable diffusion method for fine-tuning training on publicly available lung datasets. Subsequently, we extract nodules from our hospital's lung adenocarcinoma data and apply slight rotations to the original nodule CT slices within a reasonable range before undergoing another round of fine-tuning through stable diffusion. Finally, employing DDIM and Ksample sampling methods, we generate lung adenocarcinoma nodule CT images with signs based on prompts provided by doctors. The method we propose not only safeguards patient privacy but also enhances the diversity of medical images under limited data conditions. Furthermore, our approach to generating medical images incorporates medical knowledge, resulting in images that exhibit pertinent medical features, thus holding significant value in tumor discrimination diagnostics. RESULTS: Our TDASD method has the capability to generate medically meaningful images by optimizing input prompts based on medical descriptions provided by experts. The images generated by our method can improve the model's classification accuracy. Furthermore, Utilizing solely the data generated by our method for model training, the test results on the original real dataset reveal an accuracy rate that closely aligns with the testing accuracy achieved through training on real data. CONCLUSIONS: The method we propose not only safeguards patient privacy but also enhances the diversity of medical images under limited data conditions. Furthermore, our approach to generating medical images incorporates medical knowledge, resulting in images that exhibit pertinent medical features, thus holding significant value in tumor discrimination diagnostics.

Prevalence of DICER1 variants in large multinodular goiter: thyroid function, clinical and imaging characteristics.

Objective: Mutations in DICER1 are found in differentiated thyroid carcinoma (DTC) and in multinodular goiter (MNG) at a younger age with other tumors, which characterizes DICER1 syndrome. DICER1 is one driver to DTC; however, it is also found in benign nodules. We speculated that patients with mutations in DICER1 may present long-lasting MNG. Our aim was to investigate the frequency of DICER1 variants in patients with MNG. Subjects and methods: Patients who submitted to total thyroidectomy due to large MNG with symptoms were evaluated. DICER1 hotspots were sequenced from thyroid nodule samples. To confirm somatic mutation, DNA from peripheral blood was also analyzed. Results: Among 715 patients, 154 were evaluated with 56.2 ± 12.3 years old (28-79) and the thyroid volume was 115.7 ± 108 mL (16.2-730). We found 11% with six DICER1 variations in a homo or heterozygous state. Only rs12018992 was a somatic DICER1 variant. All remaining variants were synonymous and likely benign, according to the ClinVar database. The rs12018992 was previously described in an adolescent with DTC, measuring 13 mm. There were no significant differences according to gender, familial history of goiter, age, thyroid volume, TSH and TI-RADS classification between DICER1 carriers. Free T4 were lower in patients with DICER1 polymorphisms (13.77 ± 1.8 vs. 15.44 ± 2.4 pmol/L, p = 0.008), regardless of TSH levels. Conclusion: We conclude that germline DICER1 variants can be found in 11% of large goiters but no second-hit somatic mutation was found. DICER1 is one driver to thyroid lesion and a second-hit event seems unnecessary in the MNG development.

18F-FDG PET/CT Findings of Tibia Metastasis From Endometrial Adenocarcinoma.

ABSTRACT: Bone metastases from endometrial carcinoma are rare, especially when the bone is the sole metastatic site. A 55-year-old woman with a history of endometrial carcinoma was referred for FGD PET/CT scan due to pain in the left knee. The images showed that multiple lesions with intense activity were detected in the left tibia. Histopathological examination and immunohistochemistry of the left tibial lesion confirmed metastases from the endometrial adenocarcinoma.

PARP1-targeted fluorescence molecular endoscopy as novel tool for early detection of esophageal dysplasia and adenocarcinoma.

BACKGROUND: Esophageal cancer is one of the 10 most common cancers worldwide and its incidence is dramatically increasing. Despite some improvements, the current surveillance protocol with white light endoscopy and random untargeted biopsies collection (Seattle protocol) fails to diagnose dysplastic and cancerous lesions in up to 50% of patients. Therefore, new endoscopic imaging technologies in combination with tumor-specific molecular probes are needed to improve early detection. Herein, we investigated the use of the fluorescent Poly (ADP-ribose) Polymerase 1 (PARP1)-inhibitor PARPi-FL for early detection of dysplastic lesions in patient-derived organoids and transgenic mouse models, which closely mimic the transformation from non-malignant Barrett's Esophagus (BE) to invasive esophageal adenocarcinoma (EAC). METHODS: We determined PARP1 expression via immunohistochemistry (IHC) in human biospecimens and mouse tissues. We also assessed PARPi-FL uptake in patient- and mouse-derived organoids. Following intravenous injection of 75 nmol PARPi-FL/mouse in L2-IL1B (n = 4) and L2-IL1B/IL8Tg mice (n = 12), we conducted fluorescence molecular endoscopy (FME) and/or imaged whole excised stomachs to assess PARPi-FL accumulation in dysplastic lesions. L2-IL1B/IL8Tg mice (n = 3) and wild-type (WT) mice (n = 2) without PARPi-FL injection served as controls. The imaging results were validated by confocal microscopy and IHC of excised tissues. RESULTS: IHC on patient and murine tissue revealed similar patterns of increasing PARP1 expression in presence of dysplasia and cancer. In human and murine organoids, PARPi-FL localized to PARP1-expressing epithelial cell nuclei after 10 min of incubation. Injection of PARPi-FL in transgenic mouse models of BE resulted in the successful detection of lesions via FME, with a mean target-to-background ratio > 2 independently from the disease stage. The localization of PARPi-FL in the lesions was confirmed by imaging of the excised stomachs and confocal microscopy. Without PARPi-FL injection, identification of lesions via FME in transgenic mice was not possible. CONCLUSION: PARPi-FL imaging is a promising approach for clinically needed improved detection of dysplastic and malignant EAC lesions in patients with BE. Since PARPi-FL is currently evaluated in a phase 2 clinical trial for oral cancer detection after topical application, clinical translation for early detection of dysplasia and EAC in BE patients via FME screening appears feasible.

18 F-FDG PET/CT characteristics of IASLC grade 3 invasive adenocarcinoma and the value of 18 F-FDG PET/CT for preoperative prediction: a new prognostication model.

OBJECTIVE: This study is performed to investigate the imaging characteristics of the International Association for the Study of Lung Cancer grade 3 invasive adenocarcinoma (IAC) on PET/CT and the value of PET/CT for preoperative predicting this tumor. MATERIALS AND METHODS: We retrospectively enrolled patients with IAC from August 2015 to September 2022. The clinical characteristics, serum tumor markers, and PET/CT features were analyzed. T test, Mann-Whitney U test, χ 2 test, Logistic regression analysis, and receiver operating characteristic analysis were used to predict grade 3 tumor and evaluate the prediction effectiveness. RESULTS: Grade 3 tumors had a significantly higher maximum standardized uptake value (SUV max ) and consolidation-tumor-ratio (CTR) ( P  < 0.001), while Grade 1 - 2 tumors were prone to present with air bronchogram sign or vacuole sign ( P  < 0.001). A stepwise logistic regression analysis revealed that smoking history, CEA, SUV max , air bronchogram sign or vacuole sign and CTR were useful predictors for Grade 3 tumors. The established prediction model based on the above 5 parameters generated a high AUC (0.869) and negative predictive value (0.919), respectively. CONCLUSION: Our study demonstrates that grade 3 IAC has a unique PET/CT imaging feature. The prognostication model established with smoking history, CEA, SUV max , air bronchogram sign or vacuole sign and CTR can effectively predict grade 3 tumors before the operation.

Pancreatic cancer in photon-counting CT: Low keV virtual monoenergetic images improve tumor conspicuity.

PURPOSE OF THE STUDY: The aim of the study was to identify differences in the tumor conspicuity of pancreatic adenocarcinomas in different monoenergetic or polyenergetic reconstructions and contrast phases in photon-counting CT (PCCT). MATERIAL AND METHODS: 34 patients were retrospectively enrolled in this study. Quantitative image analysis was performed with region of interest (ROI) measurements in different monoenergetic levels ranging from 40 up to 70 keV (5-point steps) and polyenergetic series. Tumor-parenchyma attenuation differences and contrast-to-noise-ratio (CNR) were calculated. A qualitative image analysis was accomplished by 4 radiologists using a 5-point Likert scale (1 = "not recognizable" up to 5 = "easy recognizable"). Differences between groups were evaluated for statistical significance using the Friedman test and in case of significant differences pair-wise post-hoc testing with Bonferroni correction was applied. RESULTS: Tumor-parenchyma attenuation difference was significantly different between the different image reconstructions for both arterial- and portal-venous-phase-images (p < 0.001). Tumor-parenchyma attenuation difference was significantly higher on arterial-phase-images at mono40keV compared to polyenergetic images (p < 0.001) and mono55keV images or higher (p < 0.001). For portal-venous-phase-images tumor-parenchyma attenuation difference was significantly higher on mono40keV images compared to polyenergetic images (p < 0.001) and mono50keV images (p = 0.03) or higher (p < 0.001). The same trend was seen for CNR. Tumor conspicuity was rated best on mono40keV images with 4.3 ± 0.9 for arterial-phase-images and 4.3 ± 1.1 for portal-venous-phase-images. In contrast, overall image quality was rated best on polyenergetic-images with 4.8 ± 0.5 for arterial-phase-images and 4.7 ± 0.6 for portal-venous-phase-images. CONCLUSION: Low keV virtual monoenergetic images significantly improve the tumor conspicuity of pancreatic adenocarcinomas in PCCT based on quantitative and qualitative results. On the other hand, readers prefer polyenergetic images for overall image quality.