The characteristics and prognosis of different disease patterns of multiple primary lung cancers categorized according to the 8th edition lung cancer staging system.

INTRODUCTION: The 8th edition lung cancer staging system was the first to describe the detailed diagnosis and staging of multiple primary lung cancers (MPLC). However, the characteristics and prognosis of MPLC categorized according to the new system have not been evaluated. METHOD: We retrospectively analyzed data from surgically treated MPLC patients in a single center from 2011 to 2013 and explored the characteristics and outcomes of different MPLC disease patterns. RESULTS: In total, 202 surgically treated MPLC patients were identified and classified into different groups according to disease categories and diagnostic time (multifocal ground glass/lepidic (GG/L) nodules: n = 139, second primary lung cancer (SPLC): n = 63, simultaneous MPLC (sMPLC): n = 171, and metachronous MPLC (mMPLC): n = 31). There were significant differences in clinical characteristics between SPLC and GG/L nodule patients and simultaneous and metachronous MPLC patients. The overall 1-, 3-, and 5-year lung cancer-specific survival rates of MPLC were 97.98%, 90.18%, and 82.81%, respectively. Five-year survival was better in patients with multiple GG/L nodules than in those with SPLC (87.94% vs. 71.29%, P < 0.05). Sex was an independent prognostic factor for sMPLC (5-year survival, female vs. male, 88.0% vs. 69.5%, P < 0.05), and in multiple tumors, the highest tumor stage was an independent prognostic factor for all categories of MPLC. CONCLUSIONS: The different disease patterns of MPLC have significantly different characteristics and prognoses. Clinicians should place treatment emphasis on the tumor with the highest stage as it is the main contributor to the prognosis of all categories of MPLC patients.

Patterns of Discordance Between Clinical and Pathologic Stage in Head and Neck Cancer.

OBJECTIVE: To enhance understanding in patterns of discordance between clinical and pathological T and N staging in multiple sites of head and neck squamous cell cancer. METHODS: A retrospective cohort of 580 newly diagnosed and surgically treated head and neck squamous cell carcinoma patients from a single institution over a 10-year period are presented. Clinical and pathologic staging are compared. RESULTS: Notably, 33% of cases had staging discordance. Overall Cohen's kappa agreement was κ = 0.55 (moderate agreement). Highly discordant site stages with κ < 0.45 included: T2 oral cavity, T2 oropharynx, T3 larynx, and N1 lymph node. T2-4 oral cavity cancers were often overstaged, and more than one-third of T3 larynx cancers were understaged. Highly concordant site stages with κ>0.65 included: T1 larynx, T4 oropharynx, N0 lymph node, and N3 lymph node. CONCLUSION: There exists a quantifiable and, in certain sites, clinically relevant pattern of discordance between clinical and pathologic staging. Tumor board multidisciplinary evaluation can highlight these discrepancies and aide in limiting effects on treatment decisions. However, discordant staging can affect the interpretation and application of prognostication, treatment, and data accuracy. Further investigation is warranted to improve clinical staging accuracy in areas of highest discordance. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

Causes and impact of delays during the COVID-19 pandemic on head and neck cancer diagnosis.

BACKGROUND: The causes for delays during the COVID19 pandemic and their impact on head and neck cancer (HNC) diagnosis and staging are not well described. METHODS: Two cohorts were defined a priori for review and analysis-a Pre-Pandemic cohort (June 1 to December 31, 2019) and a Pandemic cohort (June 1 to December 31, 2020). Delays were categorized as COVID-19 related or not, and as clinician, patient, or policy related. RESULTS: A total of 638 HNC patients were identified including 327 in the Pre-Pandemic Cohort and 311 in the Pandemic Cohort. Patients in the Pandemic cohort had more N2-N3 category (41% vs. 33%, p = 0.03), T3-T4 category (63% vs. 50%, p = 0.002), and stage III-IV (71% vs. 58%, p < 0.001) disease. Several intervals in the diagnosis to treatment pathway were significantly longer in the pandemic cohort as compared to the Pre-Pandemic cohort. Among the pandemic cohort, 146 (47%) experienced a delay, with 112 related to the COVID-19 pandemic; 80 (71%) were clinician related, 15 (13%) were patient related, and 17 (15%) were policy related. CONCLUSIONS: Patients in the Pandemic cohort had higher stage disease at diagnosis and longer intervals along the diagnostic pathway, with COVID-19 related clinician factors being the most common cause of delay.

PsiOvi Staging Model for Schizophrenia (PsiOvi SMS): A New Internet Tool for Staging Patients with Schizophrenia.

BACKGROUND: One of the challenges of psychiatry is the staging of patients, especially those with severe mental disorders. Therefore, we aim to develop an empirical staging model for schizophrenia. METHODS: Data were obtained from 212 stable outpatients with schizophrenia: demographic, clinical, psychometric (PANSS, CAINS, CDSS, OSQ, CGI-S, PSP, MATRICS), inflammatory peripheral blood markers (C-reactive protein, interleukins-1RA and 6, and platelet/lymphocyte [PLR], neutrophil/lymphocyte [NLR], and monocyte/lymphocyte [MLR] ratios). We used machine learning techniques to develop the model (genetic algorithms, support vector machines) and applied a fitness function to measure the model's accuracy (% agreement between patient classification of our model and the CGI-S). RESULTS: Our model includes 12 variables from 5 dimensions: 1) psychopathology: positive, negative, depressive, general psychopathology symptoms; 2) clinical features: number of hospitalizations; 3) cognition: processing speed, visual learning, social cognition; 4) biomarkers: PLR, NLR, MLR; and 5) functioning: PSP total score. Accuracy was 62% (SD = 5.3), and sensitivity values were appropriate for mild, moderate, and marked severity (from 0.62106 to 0.6728). DISCUSSION: We present a multidimensional, accessible, and easy-to-apply model that goes beyond simply categorizing patients according to CGI-S score. It provides clinicians with a multifaceted patient profile that facilitates the design of personalized intervention plans.

Nodal staging in high and high-intermediate risk endometrial cancer surgery: Which role in the molecular classification era?

OBJECTIVES: Nodal staging contributes to risk group definition and the indication to adjuvant treatment in endometrial cancer (EC) patients. However, the role of nodal assessment evolved and requires redefinition. Primary outcome of the study was to assess the impact of surgical nodal staging in defining high-risk (HR) EC. Secondary outcome was to evaluate the contribution of nodal assessment to the decision for adjuvant treatment in both high-risk and high-intermediate risk (HIR) patients submitted to surgery. METHODS: Clinical stage I-II EC patients with postoperative diagnosis of HR and HIR disease were included. The contribution of nodal staging in prognostic groups allocation was assessed by reviewing HR patients to identify those without any other feature of such class (non-endometrioid histology, p53abn immunohistochemistry, post-operative T3-T4 disease) and HIR cases to assess how nodal staging affected adjuvant treatment indication. Descriptive statistics were conducted to describe the two populations. RESULTS: Fifty-seven patients were included, 46 with HR and 11 with HIR disease. Chemotherapy and external-beam radiotherapy (EBRT) were proposed in 40 HR patients. Considering histology, immunohistochemical profile and FIGO stage, high risk classification was exclusively relied on nodal involvement in 2/46 cases (4.3 %). Omitting retroperitoneal staging, one of them would have been classified in the intermediate risk group and the other as HIR: without nodal staging, chemotherapy and EBRT would have been omitted in 1/40 (2.5 %) case. Among HIR patients, chemotherapy was proposed in 7/11 cases and EBRT in all cases. Adjuvant chemotherapy was indicated in 5/6 (83.3 %) and omitted in 1/6 (16.7 %) pN0 patient (stage Ib G2, substantial LVSI). In HIRpN0 patients, omitting nodal staging could have changed adjuvant treatment indication in 1/6 (16.7 %) case. In HIRpNx patients, adjuvant chemotherapy was omitted in one patient (stage II, grade 2 and LVSI negative): nodal staging unavailability might have changed indication to chemotherapy in 1/5 (20 %) case, without changing indication to EBRT. Unavailable nodal staging could globally be related to omission of chemotherapy in 2/57 (3.5 %) patients and of EBRT in 1/57 (1.8 %) patient. CONCLUSIONS: In this series, nodal staging had limited impact on definition of HR class and on the choice of adjuvant treatment in HR and HIR EC patients.

Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma.

BACKGROUND: One of the primary reasons for the dismal survival rates in pancreatic ductal adenocarcinoma (PDAC) is that most patients are usually diagnosed at late stages. There is an urgent unmet clinical need to identify and develop diagnostic methods that could precisely detect PDAC at its earliest stages. AIM: To evaluate the potential value of radiomics analysis in the differentiation of early-stage PDAC from late-stage PDAC. METHODS: A total of 71 patients with pathologically proved PDAC based on surgical resection who underwent contrast-enhanced computed tomography (CT) within 30 d prior to surgery were included in the study. Tumor staging was performed in accordance with the 8th edition of the American Joint Committee on Cancer staging system. Radiomics features were extracted from the region of interest (ROI) for each patient using Analysis Kit software. The most important and predictive radiomics features were selected using Mann-Whitney U test, univariate logistic regression analysis, and minimum redundancy maximum relevance (MRMR) method. Random forest (RF) method was used to construct the radiomics model, and 10-times leave group out cross-validation (LGOCV) method was used to validate the robustness and reproducibility of the model. RESULTS: A total of 792 radiomics features (396 from late arterial phase and 396 from portal venous phase) were extracted from the ROI for each patient using Analysis Kit software. Nine most important and predictive features were selected using Mann-Whitney U test, univariate logistic regression analysis, and MRMR method. RF method was used to construct the radiomics model with the nine most predictive radiomics features, which showed a high discriminative ability with 97.7% accuracy, 97.6% sensitivity, 97.8% specificity, 98.4% positive predictive value, and 96.8% negative predictive value. The radiomics model was proved to be robust and reproducible using 10-times LGOCV method with an average area under the curve of 0.75 by the average performance of the 10 newly built models. CONCLUSION: The radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC.

Feasibility Study of Computed Tomographic Radiomics Model for the Prediction of Early and Intermediate Stage Hepatocellular Carcinoma Using BCLC Staging.

BACKGROUND: Hepatocellular carcinoma (HCC) is a serious health concern because of its high morbidity and mortality. The prognosis of HCC largely depends on the disease stage at diagnosis. Computed tomography (CT) image textural analysis is an image analysis technique that has emerged in recent years. OBJECTIVE: To probe the feasibility of a CT radiomic model for predicting early (stages 0, A) and intermediate (stage B) HCC using Barcelona Clinic Liver Cancer (BCLC) staging. METHODS: A total of 190 patients with stages 0, A, or B HCC according to CT-enhanced arterial and portal vein phase images were retrospectively assessed. The lesions were delineated manually to construct a region of interest (ROI) consisting of the entire tumor mass. Consequently, the textural profiles of the ROIs were extracted by specific software. Least absolute shrinkage and selection operator dimensionality reduction was used to screen the textural profiles and obtain the area under the receiver operating characteristic curve values. RESULTS: Within the test cohort, the area under the curve (AUC) values associated with arterial-phase images and BCLC stages 0, A, and B disease were 0.99, 0.98, and 0.99, respectively. The overall accuracy rate was 92.7%. The AUC values associated with portal vein phase images and BCLC stages 0, A, and B disease were 0.98, 0.95, and 0.99, respectively, with an overall accuracy of 90.9%. CONCLUSION: The CT radiomic model can be used to predict the BCLC stage of early-stage and intermediate-stage HCC.

Early rectal cancer: The diagnostic performance of MRI supplemented with a rectal micro-enema and a modified staging system to identify tumors eligible for local excision.

Background: In staging early rectal cancers (ERC), submucosal tumor depth is one of the most important features determining the possibility of local excision (LE). The micro-enema (Bisacodyl) induces submucosal edema and may hypothetically improve the visualization of tumor depth. Purpose: To test the diagnostic performance of MRI to identify ERC suitable for LE when adding a pre-procedural micro-enema and concurrent use of a modified classification system. Material and Methods: In this prospective study, we consecutively included 73 patients with newly diagnosed rectal tumors. Two experienced radiologists independently interpreted the MRI examinations, and diagnostic performance was calculated for local tumors eligible for LE (Tis-T1sm2, n = 43) and non-local tumors too advanced for LE (T1sm3-T3b, n = 30). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were registered for each reader. Inter- and intra-reader agreements were assessed by kappa statistics. Lymph node status was derived from the clinical MRI reports. Results: Reader1/reader2 achieved sensitivities of 93%/86%, specificities of 90%/83%, PPV of 93%/88%, and NPV of 90%/81%, respectively, for identifying tumors eligible for LE. Rates of overstaging of local tumors were 7% and 14% for the two readers, and kappa values for the inter- and intra-reader agreement were 0.69 and 0.80, respectively. For tumors ≤T2, all metastatic lymph nodes were smaller than 3 mm on histopathology. Conclusion: MRI after a rectal micro-enema and concurrent use of a modified staging system achieved good diagnostic performance to identify tumors suitable for LE. The rate of overstaging of local tumors was comparable to results reported in previous endorectal ultrasound (ERUS) studies.

Development of an Artificial Intelligence Model for the Classification of Gastric Carcinoma Stages Using Pathology Slides.

This study showcases a novel AI-driven approach to accurately differentiate between stage one and stage two gastric carcinoma based on pathology slide analysis. Gastric carcinoma, a significant contributor to cancer-related mortality globally, necessitates precise staging for optimal treatment planning and patient management. Leveraging a comprehensive dataset of 3540 high-resolution pathology images sourced from Kaggle.com, comprising an equal distribution of stage one and stage two tumors, the developed AI model demonstrates remarkable performance in tumor staging. Through the application of state-of-the-art deep learning techniques on Google's Collaboration platform, the model achieves outstanding accuracy and precision rates of 100%, accompanied by notable sensitivity (97.09%), specificity (100%), and F1-score (98.31%). Additionally, the model exhibits an impressive area under the receiver operating characteristic curve (AUC) of 0.999, indicating superior discriminatory power and robustness. By providing clinicians with an efficient and reliable tool for gastric carcinoma staging, this AI-driven approach has the potential to significantly enhance diagnostic accuracy, inform treatment decisions, and ultimately improve patient outcomes in the management of gastric carcinoma. This research contributes to the ongoing advancement of cancer diagnosis and underscores the transformative potential of artificial intelligence in clinical practice.

Symptom-based staging for logopenic variant primary progressive aphasia.

BACKGROUND AND PURPOSE: Logopenic variant primary progressive aphasia (lvPPA) is a major variant presentation of Alzheimer's disease (AD) that signals the importance of communication dysfunction across AD phenotypes. A clinical staging system is lacking for the evolution of AD-associated communication difficulties that could guide diagnosis and care planning. Our aim was to create a symptom-based staging scheme for lvPPA, identifying functional milestones relevant to the broader AD spectrum. METHODS: An international lvPPA caregiver cohort was surveyed on symptom development under an 'exploratory' survey (34 UK caregivers). Feedback from this survey informed the development of a 'consolidation' survey (27 UK, 10 Australian caregivers) in which caregivers were presented with six provisional clinical stages and feedback was analysed using a mixed-methods approach. RESULTS: Six clinical stages were endorsed. Early symptoms included word-finding difficulty, with loss of message comprehension and speech intelligibility signalling later-stage progression. Additionally, problems with hearing in noise, memory and route-finding were prominent early non-verbal symptoms. 'Milestone' symptoms were identified that anticipate daily-life functional transitions and care needs. CONCLUSIONS: This work introduces a new symptom-based staging scheme for lvPPA, and highlights milestone symptoms that could inform future clinical scales for anticipating and managing communication dysfunction across the AD spectrum.

Determining the Need for Metastatic Staging in Patients with Bilateral Breast Cancers.

Introduction: Bilateral breast cancers (BBC) diagnosed at an interval apart are uncommon. While metastatic staging guidelines are established in patients with unilateral breast cancer, its role in BBC diagnosed at an interval apart is unclear. We aim to identify the subgroup who would benefit from metastatic staging at contralateral cancer diagnosis. Methods: Eligible patients were divided into three categories: (A) ipsilateral invasive cancer and contralateral ductal carcinoma in situ (DCIS), (B) bilateral invasive cancers and (C) ipsilateral DCIS and contralateral invasive cancer and reviewed retrospectively. We excluded patients with bilateral DCIS, synchronous BBC diagnosed within 6 months from first cancer, patients who were stage IV at first cancer diagnosis and patients with recurrence prior to contralateral cancer. Results: Of 4516 newly diagnosed breast cancer patients, 79 patients were included. Systemic metastasis occurred in 15.6% of patients in Group B. Having nodal positivity of either cancer which were diagnosed ≤30 months apart and nodal positivity of only the contralateral cancer when diagnosed >30 months apart was significantly associated with systemic metastasis (p = 0.0322). Conclusions: Both the nodal status and a 30 months cut-off time interval between the two cancers can be used to identify patients who will benefit from metastatic staging. This finding requires validation in larger studies.

Depth of invasion analysis to predict acral melanoma outcomes.

BACKGROUND: Acral melanoma is a subtype with worse outcomes. The Breslow micrometric measurement is the most critical parameter in planning treatment and predicting outcomes. However, for acral lentiginous melanoma, the value of the Breslow thickness is a matter of debate. Depth of Invasion (DOI) is a well-established measure for staging oral squamous cell carcinoma. OBJECTIVE: This study compared DOI and Breslow thickness for predicting acral melanoma outcomes. METHODS: We performed a retrospective cross-sectional study of 71 acral melanoma lesions subjected to sentinel lymph node biopsy at one Brazilian referral center. RESULTS: Cox model univariate analysis showed that both DOI and Breslow thickness predicted melanoma specific survival (HR 1.12; p = 0.0255 and HR 1.144; p = 0.0006, respectively), although Kaplan Meier curve was only significant for Breslow (χ2 = 5.792; p = 0.0161) and not for DOI (χ2 = 0.2556; p = 0.6132). Sentinel lymph node status and presence or absence of ulceration also predicted specific survival in patients with acral melanoma (χ2 = 6.3514; p = 0.0117 and χ2 = 4.2793; p = 0.0386, respectively). Multivariate analysis, however, demonstrated that Breslow depth was the only independent parameter for predicting acral melanoma specific survival (HR 1.144; p = 0.0006). CONCLUSION: Even though Breslow thickness remains the main predictor for survival in acral melanoma, it is not a perfect parameter. The introduction of DOI in this context opens new perspectives for predicting acral melanoma outcomes.

Evaluation of multi-parameter MRI in preoperative staging of endometrial carcinoma.

Background: Endometrial carcinoma (EC) is a prevalent gynecological malignancy, necessitating accurate preoperative staging for effective treatment planning. This study explores the application value of multi-parameter MRI in diagnosing and staging endometrial cancer. Methods: Seventy-six patients diagnosed with endometrial cancer underwent 3.0 T pelvic MRI within two weeks before surgery. Imaging data were analyzed based on FIGO clinical staging criteria. The study assessed the sensitivity, specificity, positive predictive value, and negative predictive value of MRI for each stage. Results: Postoperative pathology confirmed 71 cases of endometrial adenocarcinoma, 3 serous adenocarcinoma, and 2 clear cell carcinomas. MRI staging showed a high consistency (Kappa value = 0.786) with postoperative pathology. The overall accuracy of MRI diagnosis was 86.8%. Sensitivity and specificity varied for each stage: IA (91.3%, 96.2%), IB (88.6%, 93.8%), II (97.4%, 89.2%), and III (84.2%, 100%). Conclusion: While there was a slight misdiagnosis rate, the overall accuracy of preoperative MRI for endometrial cancer was high, aiding in precise diagnosis and clinical staging. MRI effectively identified myometrial infiltration, cervical involvement, paracentral extension, and lymph node metastasis. Further research with larger sample sizes is recommended for enhanced reliability.

Histopathological staging of atrophic lesions of gastric mucosa.

Objective: To study the histopathological staging of atrophic lesions of the gastric mucosa. Methods: Histology and immunohistochemistry were used to closely examine 2144 specimens of atrophic gastric mucosa that were taken from endoscopic biopsies. Results: When the gastric mucosa epithelium is affected by infection, chemical stimulation, immune factors, genetic factors, and other factors, it may cause an atrophy of gastric mucosa epithelium and a decrease in the number of glands, intestinal metaplasia, hyperplasia of smooth muscle fibers, and atrophy of stem cells in the proliferative zone. In this study, we characterized the above lesions as atrophic lesions of the gastric mucosa. Based on the morphological and histological characteristics of the lesion, as well as the law of cell proliferation and transformation during its occurrence and development, we propose five stages. We also noted the onset age, gender correlation, and histopathological characteristics of each stage of gastric mucosal atrophies. Conclusion: Understanding the pathological staging of gastric mucosal atrophy is essential for treating patients correctly and keeping track of changes in malignant cells. It is also very important in preventing the initiation of gastric cancer or from getting worse.

Prognostic significance of ß2-microglobulin decline index in multiple myeloma.

Purpose: To assess the prognostic significance of ß2-microglobulin decline index (ß2M DI) in multiple myeloma (MM). Methods: 150 MM patients diagnosed with MM were enrolled in this study. Cox proportional hazards model was used to analyze the uni- and multivariate prognosis in training cohort (n=105). A new combined prognostic model containing ß2M DI was built up based on the data in training cohort. The validation group was used to verify the model. Results: ß2M DI showed significant correlation with prognosis in both uni- and multivariate analyses and had a good correlation with complete response (CR) rate and deep remission rate. The ROC and calibration curves in validation cohort (n=45) indicated a good predictive performance of the new model. Based on the median risk score of the training group, we classified patients into high- and low- risk groups. In both training and validation groups, patients in the low-risk group had longer overall survival (OS) time than that in the high-risk group (p<0.05). Conclusion: ß2M DI is a good predictive index for predicting treatment response and survival time in MM patients. The prognostic model added with ß2M DI showed a better correlation with OS.

Postembryonic development and male paedomorphosis in Osedax (Siboglinidae, Annelida).

Most species of the bone-devouring marine annelid, Osedax, display distinct sexual dimorphism with macroscopic sedentary females rooted in bones and free-living microscopic dwarf males. The paedomorphic male resembles the non-feeding metatrochophore larva in size, presence of eight pairs of chaetae, and a head ciliation potentially representing a residual prototroch. The male development may thus uniquely reiterate and validate the theoretical heterochrony process "progenesis", which suggests that an accelerated sexual maturation and early arrest of somatic growth can lead to a miniaturized and paedomorphic adult. In this study, we describe the postembryonic larval and juvenile organogenesis of Osedax japonicus to test for a potential synchronous arrest of somatic growth during male development. Five postembryonic stages could be distinguished, resembling day one to five in the larval development at 10°C: (0D) first cleavage of fertilized eggs (embryos undergo unequal spiral cleavage), (1D) pre-trochophore, with apical organ, (2D) early trochophore, + prototroch, brain, circumesophageal connectives and subesophageal commissure, (3D) trochophore, + telotroch, four ventral nerves, (4D) early metatrochophore, + protonephridia, dorsal and terminal sensory organs, (5D) metatrochophore, + two ventral paratrochs, mid-ventral nerve, posterior trunk commissure, two dorsal nerves; competent for metamorphosis. The larval development largely mirrors that of other lecithotrophic annelid larvae but does not show continuous chaetogenesis or full gut development. Additionally, O. japonicus larvae exhibit an unpaired, mid-dorsal, sensory organ. Female individuals shed their larval traits during metamorphosis and continue organogenesis (including circulatory system) and extensive growth for 2-3 weeks before developing oocytes. In contrast, males develop sperm within a day of metamorphosis and display a synchronous metamorphic arrest in neural and muscular development, retaining a large portion of larval features post metamorphosis. Our findings hereby substantiate male miniaturization in Osedax to be the outcome of an early and synchronous offset of somatic development, fitting the theoretical process "progenesis". This may be the first compelling morpho-developmental exemplification of a progenetic origin of a microscopic body plan. The presented morphological staging system will further serve as a framework for future examination of molecular patterns and pathways determining Osedax development.

A comparison study of 68gallium-prostate-specific membrane antigen positron emission tomography-computed tomography and multiparametric magnetic resonance imaging for locoregional staging of prostate cancer.

Purpose: Prostate cancer (PCa) is the most common malignancy in men aged 50 years and older and the second cause of cancer death among men. Accurate staging of PCa preoperatively is of high importance for treatment decisions and patient management. Conventional imaging modalities (ultrasound, computed tomography [CT], and magnetic resonance imaging) are inaccurate for the staging of PCa. Newer modality multiparametric magnetic resonance imaging (mpMRI) and prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scan show promising results for the staging of PCa. Only fewer studies are available for comparison of these modalities with histopathology as reference. The objective of our study is to evaluate the diagnostic accuracy of independent 68gallium PSMA (68Ga-PSMA) PET-CT compared with mpMRI for preoperative staging of PCa, using histopathology as the reference standard. Materials and methods: From August 2021 to December 2022, 30 patients of biopsy-proven PCa were prospectively enrolled as per eligibility criteria. Preoperatively, 68Ga-PSMA PET scan and mpMRI were done in all the patients. Extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph node metastasis (LNM) were investigated separately. Subsequently, the patients underwent robotic-assisted radical prostatectomy with bilateral pelvic lymph node dissection. Results: mpMRI prostate was more sensitive (66.66%) but less specific than PSMA PET-CT (55.55%) for ECE. mpMRI and PSMA PET-CT both had similar sensitivity (83.3%) and specificity (87.5%) for SVI. PSMA PET-CT was more sensitive (85.71%) and specific (95.6%) than mpMRI prostate (62.5% and 91.30%, respectively) for LNM. Conclusion: PSMA PET-CT is more specific for the detection of ECE and more sensitive and specific for the detection of LNM than mpMRI, and similar for the detection of SVI. mpMRI provides only local staging, while PSMA PET-CT provides information about local, regional, and distal staging. Overall, PSMA PET-CT is superior to mpMRI for locoregional staging of PCa.

Potential of photon counting computed tomography derived spectral reconstructions to reduce beam-hardening artifacts in chest CT.

PURPOSE: Aim of the recent study is to point out a method to optimize quality of CT scans in oncological patients with port systems. This study investigates the potential of photon counting computed tomography (PCCT) for reduction of beam hardening artifacts caused by port-implants in chest imaging by means of spectral reconstructions. METHOD: In this retrospective single-center study, 8 ROIs for 19 spectral reconstructions (polyenergetic imaging, monoenergetic reconstructions from 40 to 190 keV as well as iodine maps and virtual non contrast (VNC)) of 49 patients with pectoral port systems undergoing PCCT of the chest for staging of oncologic disease were measured. Mean values and standard deviation (SD) Hounsfield unit measurements of port-chamber associated hypo- and hyperdense artifacts, bilateral muscles and vessels has been carried out. Also, a structured assessment of artifacts and imaging findings was performed by two radiologists. RESULTS: A significant association of keV with iodine contrast as well as artifact intensity was noted (all p < 0.001). In qualitative assessment, utilization of 120 keV monoenergetic reconstructions could reduce severe and pronounced artifacts completely, as compared to lower keV reconstructions (p < 0.001). Regarding imaging findings, no significant difference between monoenergetic reconstructions was noted (all p > 0.05). In cases with very high iodine concentrations in the subclavian vein, image distortions were noted at 40 keV images (p < 0.01). CONCLUSIONS: The present study demonstrates that PCCT derived spectral reconstructions can be used in oncological imaging of the thorax to reduce port-derived beam-hardening artefacts. When evaluating image data sets within a staging, it can be particularly helpful to consider the 120 keV VMIs, in which the artefacts are comparatively low.

Advances in the Imaging of Esophageal and Gastroesophageal Junction Malignancies.

Accurate imaging is key for the diagnosis and treatment of esophageal and gastroesophageal junction cancers . Current imaging modalities, such as computed tomography (CT) and 18F-FDG (2-deoxy-2-[18F]fluoro-D-glucose) positron emission tomography (PET)/CT, have limitations in accurately staging these cancers. MRI shows promise for T staging and residual disease assessment. Novel PET tracers, like FAPI, FLT, and hypoxia markers, offer potential improvements in diagnostic accuracy. 18F-FDG PET/MRI combines metabolic and anatomic information, enhancing disease evaluation. Radiomics and artificial intelligence hold promise for early detection, treatment planning, and response assessment. Theranostic nanoparticles and personalized medicine approaches offer new avenues for cancer therapy.