Biopsy Reports Research Articles

Imaging, Patient, and Diagnostic Radiologist Factors Associated With Malignancy for Mammographic Asymmetries Undergoing Biopsy.

To identify imaging, patient, and radiologist factors associated with malignant pathology for mammographic asymmetries referred for image-guided biopsy. This is an IRB-approved study of consecutive image-guided core-needle biopsy reports from an academic center and affiliated imaging centers January 1, 2015 to June 30, 2022 with lesion type reported by biopsy radiologist as "asymmetry" on biopsy requisition form retrieved from the pathology database. Imaging features (asymmetry type, associated mammographic features, US correlate, lesion size) and patient demographics (age at biopsy, breast density, family or personal history of breast cancer) were extracted from imaging reports and electronic health record. Cases were excluded if the diagnostic or biopsy radiologist reported the lesion other than "asymmetry" or if imaging review identified the finding as predominantly mass or architectural distortion. Multiple logistic regression was performed to calculate the odds ratio (OR) of malignant outcome. Image-guided core-needle biopsy was requested of 326 asymmetries; 79 were excluded, yielding 247 asymmetries (9 asymmetry, 218 developing asymmetry, 20 focal asymmetry). Overall, 40/247 (16.2%) were malignant and 207/247 (83.8%) were benign. Presence of associated distortion (OR 14.78; 95% CI, 4.87-44.83; P <.001) or calcifications (OR 9.86; 95% CI, 2.74-35.53; P <.001), personal history of breast cancer (OR 2.65; 95% CI, 1.04-6.77; P = .041), and increasing patient age at biopsy (OR 1.08; 95% CI, 1.04-1.12; P <.001) were associated with likelihood of malignancy. Malignancy of mammographic asymmetries is more likely in the presence of associated distortion or calcifications, personal history of breast cancer, and increasing patient age. These results may be useful in diagnostic management of mammographic asymmetries.

Impact of an artificial intelligence decision support system among radiologists with different levels of experience in breast ultrasound: A prospective study in a tertiary center.

Impact of an artificial intelligence decision support system among radiologists with different levels of experience in breast ultrasound: A prospective study in a tertiary center.

Breast Lump Patterns Across Different Age Groups Among Female Patients Presenting to Surgical Outpatient Department of a Tertiary Care Hospital in District Malir Karachi

The number of patients presenting with different types of breast lumps has been on the rise in the Malir district. Many females are being diagnosed with breast cancer. Objectives: To determine the pattern of breast lumps in different age groups in the outpatient department of Al-Tibri Medical College hospital in District Malir, Karachi. Methods: It was a descriptive cross-sectional study conducted at the Department of General Surgery, Al-Tibri Medical College Hospital, Karachi, from 1st November 2022 to 31st October 2024. Patients presenting in the Surgical Outpatient Department with breast lumps were included in the study. Age at presentation, symptoms, clinical features, investigations, biopsy reports, and operation notes (if operated) were recorded and submitted for analysis. Results: The commonest lesions were fibro-adenoma (33.6%), inclusion cyst of the breast (19%), and breast abscess (18.5%), followed by Carcinoma breast (17.7%). 51.7 % of cases were associated with pain. Among carcinomas, 43% presented with pain. The highest peak of presenting with malignant lesions was from 39 to 43 years, and 2nd peak was from 49 to 58 years. Most benign lesions presented between 24 to 28 years. The chi-square test showed a strong association between age range and pain (p-value&lt;0.001), age range and type of lump (p-value &lt;0.001), and marital status and type of lump (p-value&lt;0.001). Conclusions: It was concluded that fibro-adenoma is the most common breast disease. Inflammatory lesions are also present frequently in the reproductive age group. Carcinoma breast presented in middle and later age groups, predominantly in married females in our district.

Positive Predictive Rate of Breast Imaging-Reporting and Data System (BI-RADS) Category 4 Lesions For Breast Cancer Taking Histopathology as Gold Standard

Objective: To determine positive predictive rate of Breast imaging-reporting and data system (BI-RADS) category 4 and its sub-categories for breast cancer taking histopathology as gold standard. Study Design: Cross sectional validation study. Place and Duration of Study: Department of Radiology, Pakistan Institute of Medical Sciences, Islamabad Pakistan, from Sep to Nov 2020. Methodology: 60 female patients who were diagnosed as Breast imaging-reporting and data system (BI-RADS) category 4 lesions on mammography were included in the study and afterwards followed for biopsy report. Data was collected and analyzed using SPSSv25. Results: Patient’s mean age was 50.6±9.7yrs. Among sixty patients with BIRADS 4, 13(21.7%) had BIRADS 4A, 22(36.7%) had BIRADS 4B and 25(41.7%) had 4C. Positive predictive value for BIRADS 4 was 68.33%, 4A was 15.3%, 4B was 72.7% and for 4C was 92%. Sensitivity &amp; Specificity of BIRADS 4A being benign and BIRADS 4B, &amp; 4C being malignant is 91.49% and 69.23% respectively. Overall, diagnostic accuracy of BIRADS 4B &amp; 4C classification was found to be 83.33%. Conclusion: Sub-categorization of Breast imaging-reporting and data system (BI-RADS) category 4 is not routinely practiced, however results of current study conclude that it helps to stratify the associated risk of malignancy and update the level of concern to referring physician and pathologist.

New interpretation of diabetic nephropathy or diabetic kidney disease from kidney biopsy: review article.

Many nephrologists considered that renal involvement in diabetes patients was seen as nodular glomerulosclerosis (i.e., Kimmelstiel-Wilson lesions). However, they diagnosed diabetic nephropathy or diabetic kidney disease (DKD) from clinical information on diabetes history, and reports of evaluation by kidney biopsy were scarce. Since the publication of the Tervaert classification of diabetic nephropathy in 2010, reports of kidney biopsy in these patients have increased. Analysis of biopsy specimens revealed not only the Tervaert classification (class I to IV) based on glomerular lesions, but also various other pathologies. Besides nodular lesions, findings included paratubular basement membrane insudative lesions (PTBMILs), polar vasculosis, and nephropathy associated with novel drugs (sodium-glucose transport protein 2 inhibitors and dipeptidyl peptidase-4 inhibitors). PTBMILs are unique to diabetic nephropathy. In patients with continuous hyperglycemia and excessive salt intake, elevated blood osmolality (calculated by serum Na × 2 + serum glucose/18 + serum urea nitrogen/2.8) leads to thirst and excessive drinking, which results in fluid overload and generalized edema. The increase in circulating blood volume is thought to induce PTBMILs because of the influx of serum components into the endothelium of glomerular vessels. This case series review presents diverse kidney biopsy findings in patients with diabetic nephropathy or diabetic kidney disease as well as the pathogenesis.

Cranial MRI in neurosarcoidosis: Imaging patterns and nationwide clinical correlations.

To investigate cranial MRIs of sarcoidosis pateints by defining typical and atypical findings and their relations with patient characteristics and other disease manifestations. A nationwide cohort was formed from patients with an entering ICD-10 code for sarcoidosis twice at least 1 month apart and any tissue biopsy result with the word "granuloma" defined in the biopsy report were considered to have sarcoidosis. Data regarding patients were obtained by using Turkish Ministry of Health National Electronic Data base. Patients of the formed cohort were investigated for the presence of a cranial imaging at any time. 4367 patients were defined as sarcoidosis and enrolled in the study. 1659 cranial imagings in 689 patients were investigated. 1175 imagings were deemed suitable and evaluated. 3.4% of the patients had findings suggestive of sarcoidosis. Most common lesions were leptomeningeal or dural thickening with/without contrast material enhancement and midbrain/brainstem lesions. Presence of pulmonary sarcoidosis was the only significant factor with a negative predictive effect for patients to have typical findings. Among sarcoidosis patients with MRI we detected 3.4% of them had findings suggestive of CNS sarcoidosis. Absence of pulmonary involvement was observed to be predictor for occurrence of typical manifestations.

Clinicopathological and management outcome in 70 patients with pityriasis rubra pilaris: A retrospective analysis

Background Pityriasis rubra pilaris (PRP) is a rare papulosquamous disease with a characteristic clinical appearance, including follicular salmon-coloured papules, which can sometimes progress into erythroderma. Both clinical and histopathological findings are important in diagnosing the disease and should be evaluated together. Objectives There are no guidelines for diagnosis and treatment of the disease. The aim of the present study was to contribute to the clinical diagnosis and treatment approach of this rare disease, which could serve as a clinical guide for dermatologists. Methods A total of 70 patients diagnosed with PRP in the last 20 years were included in this retrospective study. Clinical, demographic, and histopathologic profiles; and treatment strategies were analysed. Patients were divided into two groups with ‘definite’ or ‘probable’ diagnoses; those diagnosed to have PRP based on both clinical and histopathological findings were classified as having a ‘definite’ diagnosis; and those with histopathologically non-specific features but clinical findings compatible with PRP were classified as having a ‘probable’ diagnosis. Results Forty (57.1%) patients were females and 30 (42.9%) were males. Their age ranged from 8 to 79 years (mean age 39.57±18.80 years). The median duration of the disease (before patients received the diagnosis) was 7 months (IQR=24). According to biopsy reports, the most common epidermal changes were hyperkeratosis (78.6%) and focal parakeratosis (75.7%), while the ‘checkerboard pattern,’ which is considered specific for the disease, was detected in only 16 (22.9%) cases. Only 8 biopsy samples (11.4%) had an eosinophilic infiltrate. While 47 (67.1%) patients were classified under ‘definite diagnosis and 23 (32.9%) were classified under ‘probable diagnosis.’ The disease duration was longer in patients with definite diagnosis than in patients with probable diagnosis (p=0.045). A total of 33 (47.14%) patients needed systemic therapy in addition to topical treatment. While 4 of these 33 patients were classified as Type 3, the remaining patients were classified as Type 1, classical adult type. Only three Type 1 (classical adult PRP) patients had erythroderma. Oral retinoids, especially acitretin, were the most preferred and effective treatment. Five patients showed improvement with methotrexate and two needed biological agents. Limitation The present study is retrospective and includes a relatively limited number of patients. Conclusion PRP is still a rare, difficult-to-manage disease. More studies are required to standardise and improve the diagnosis and treatment approaches for the disease.

A case of anti-Ku myositis mimicking limb girdle muscular dystrophy

Anti-Ku is a myositis associated antibody. Histopathology of anti-Ku myositis shows significant muscle fibre necrosis imitating immune mediated necrotising myositis as well as muscular dystrophies. A presentation of isolated proximal muscle weakness with muscle biopsy evidence of muscular dystrophy could mislead the clinician. We present a case of anti-Ku myositis with lower limb predominant weakness, absent extra-muscular manifestations and with an equivocal Anti-Nuclear antibody titre, whose muscle biopsy report came as muscular dystrophy. We would like to highlight the importance of considering anti-Ku myositis as an important differential in biopsies showing significant muscle destruction.

Turnaround Time for Image-Guided Breast Core Biopsies: A College of American Pathologists Survey Q-Probes Study.

Timely breast core biopsy results help expedite appropriate treatment for patients. Many institutions track turnaround times from biopsy to report; however, there are no established benchmarks to evaluate performance and identify potential improvement opportunities. To determine benchmark turnaround times for breast core biopsy reports and identify key drivers impacting turnaround time. Participants enrolled in the College of American Pathologists Q-Probes study entitled Turnaround Time for Image-Guided Breast Needle Biopsy Specimens provided intervals for processing steps through report completion, and details regarding potential influencing variables. Nineteen participants submitted data for 876 cases. The median turnaround time from accession to report completion was 31.0 hours, with a median time of 19.2 hours from accessioning to slide delivery to pathologists. The median time from biopsy to accessioning (3.4 hours) and slide delivery to report completion (7.5 hours) was notably shorter. Cases with malignant diagnoses were associated with longer median turnaround times than those with benign/atypical/borderline diagnoses (44.1 versus 29.4 hours; P = .04). Cases requiring additional testing or consultation were associated with longer median turnaround times than straightforward cases (45.3 versus 27.4 hours; P < .001). Fixation time variability was noted between laboratories (median, 11.0 hours; 10th and 90th percentile times: 7.1 and 31.3 hours, respectively). Variability was seen in the total processing times among laboratories (mean, 9.1 hours; range, 4.5-12.5 hours). Participating laboratories provided timely breast core biopsy results. Benchmark data presented may be useful for laboratories to assess performance and develop strategies for improvement.

A natural language processing algorithm to extract MRI and biopsy-related phenotypes for prostate cancer patients.

356 Background: Extraction of data from unstructured medical records is a powerful but challenging tool for deriving novel information to drive research, improve clinical care and better inform guidelines. Here, we describe the creation and validation of a novel natural language processing (NLP) algorithm for extracting components of interest from biopsy and MRI reports for prostate cancer patients. Our algorithm specifically extracts the Gleason score from biopsy reports and maximum Prostate Imaging-Reporting and Data System (PI-RADS) score, Prostate-specific androgen (PSA) density, prostate volume, and prostate dimensions from MRI reports. Methods: MRI and biopsy pathology reports were extracted for a cohort of 155,570 patients diagnosed with prostate cancer between 1999 and 2024 either in the VA Cancer Registry System (VACRS) with prostate as their primary site of tumor or in the VA Corporate Data Warehouse with a relevant procedure or diagnosis code. These were annotated by a physician and a trained research scientist to generate data for the development and validation of our algorithm. Disagreements between annotators were adjudicated by a urologist. Our rule-based NLP algorithm was iteratively developed on 600 annotated and unannotated notes. The algorithm was validated on a manually annotated set of 250 MRI reports and 250 biopsy pathology notes from 378 patients at 78 VA centers for procedures between 2004 and 2024. Precision (true positives / (true positives + false positives)), recall (true positives / (true positives + false negatives)), and F1 score (2 * (precision * recall) / (precision + recall)) were computed to evaluate algorithm performance, with higher scores indicating better performance. Results: Our algorithm successfully extracted all five components from text reports with high precision and sensitivity. Item-level performance metrics for our algorithm on unseen data are reported in the table below. Post-hoc spot checking of algorithm performance on an additional sample of notes selected by procedure year revealed consistency of results across time for all components except prostate dimensions, for which a greater proportion of recent negative notes were false negatives. Further error analysis showed that many Gleason scores that our algorithm did not extract were repetitions of scores successfully extracted elsewhere in the note. Conclusions: Our NLP algorithm is able to derive structured data from medical reports with highly diverse formats with excellent accuracy and reliability. This approach has great potential to facilitate data extraction in a range of settings and to drive future research and clinical questions. Component Precision % Recall % F1 score % Gleason grade group 99.1 94.7 96.9 PI-RADS 95.5 92.7 94.1 PSA density 100.0 99.0 99.5 Prostate volume 96.9 94.5 95.7 Prostate dimensions 98.4 90.2 94.1

Automated risk stratification in localized prostate cancer using an AI-assisted framework.

341 Background: Specialist clinicians (oncologists, urologists, radiation oncologists) read through free text reports of prostate MRI and biopsy reports to risk stratify patients during initial consultation of localized PCa. This laborious and time-consuming process is repeated for each day during the clinic. Herein, we propose a hybrid stratification framework utilizing a combination of large language model (LLM) and rule-based programming to automate this process. Methods: This retrospective study included patients with localized PCa (2004-2024) presenting to care at Mayo Clinic with at least one positive prostate biopsy and MRI report available. The state-of-the-art LLM – GPT4 – was utilized using a structured zeroshot prompt to extract relevant phenotypic variables (clinical T stage, Gleason patterns, grade group, extent of specimen/cores involved, prostate size/volume) from unstructured MRI and biopsy reports. Using a rule-based algorithm, the extracted variables and PSA at PCa diagnosis were used to categorize each patient into one of the six NCCN risk categories (very low [VL], low [L], favorable intermediate [FInt], unfavorable intermediate [UFInt], high risk (HR), very high risk [VHR]). Prompts were iteratively developed using ~5% of the total dataset and validated on ~10% of the dataset. Final performance was assessed against a held-out expert annotated test dataset using evaluation metrics (accuracy, F1-score, precision, recall). Additionally, manual annotation was conducted by two independent novice reviewers to compare machine annotated and novice-human annotated risk categorization. Results: A total of 397 patients were included in the evaluation. The median age at diagnosis was 64.8 (IQR: 59.7-68.5); majority of the men were White (n: 366; 92%) and non-Hispanic (n: 371; 94%). The most prevalent risk category was UFint (n: 151; 38%) followed by FInt (n: 80; 20.2%), HR (n: 76; 19.1%), VHR (n: 64; 16.1%), L (21: 5.3%), and VL (n: 5; 1.3%). Novice reviewers achieved an accuracy of 79%, precision of 80%, recall of 82% and a F1-score of 0.81. The hybrid stratification framework using GPT4 achieved an accuracy of 89%, precision of 89%, recall of 88% and a F1-score of 0.88. Among 43 errors by GPT4 risk stratification, majority of the errors were due to miscategorization of clinical T-stage (n: 21; 49%) followed by erroneous number of positive cores (n: 13; 30%). However, additional evaluation showed that GPT4 achieved numerically higher performance (accuracy: 90%; precision: 91%; recall: 90%; F1: 0.90) compared to novice reviewers (accuracy: 77%; precision: 89%; recall: 77%; F1: 0.82) for ascertaining clinical T-stage. Conclusions: Large language models exhibited superior performance than novice clinicians for risk stratification in patients with localized PCa. As the next step, we intend to validate our framework for automated risk classification in a prospective manner.

ADAM: automated digital phenotyping and morphological texture analysis of bone biopsy images using deep learning.

Histomorphometric analysis of undecalcified bone biopsy images provides quantitative assessment of bone turnover, volume, and mineralization using static and dynamic parameters. Traditionally, quantification has relied on manual annotation and tracing of relevant tissue structures, a process that is time-intensive and subject to inter-operator variability. We developed ADAM, an automated pipeline for digital phenotyping, to quantify tissue and cellular components pertinent to static histomorphometric parameters such as bone and osteoid area, osteoclast and osteoblast count, and bone marrow adipose tissue (BMAT) area. The pipeline allowed rapid generation of delineated tissue and cell maps for up to 20 images in less than a minute. Comparing deep learning-generated annotation pixels with manual annotations, we observed Spearman correlation coefficients of ρ = 0.99 for both mineralized bone and osteoid, and ρ = 0.94 for BMAT. For osteoclast and osteoblast cell counts, which are subject to morphologic heterogeneity, using only brightfield microscopic images and without additional staining, we noted ρ = 0.60 and 0.69, respectively (inter-operator correlation was ρ = 0.62 for osteoclast and 0.84 for osteoblast count). The study also explored the application of morphological texture analysis (MTA), measuring relative pixel patterns that potentially vary with diverse tissue conditions. Notably, MTA from mineralized bone, osteoid, and BMAT showed differentiating potential to identify common pixel characteristics between images labeled as low or high bone turnover based upon the final diagnostic report of the bone biopsy. The Area Under the Receiver Operating Characteristic Curve (AUC-ROC) obtained for BMAT MTA features as a classifier for bone turnover, was 0.87, suggesting that computer-extracted features, not discernable to the human eye, hold potential in classifying tissue states. With additional evaluation, ADAM could be potentially integrated into existing clinical routines to improve pathology workflows and contribute to diagnostic insights into bone biopsy evaluation and reporting.

Analytical software for visual and quantitative comparison of real mammography and phantom breast cancer imaging

Computer-aided diagnostic schemes have been developed with the primary aim of improving the diagnostic accuracy of the detection of cancer in mammography. A robust mammographic image database is a priority requirement to assist in testing the effectiveness of techniques associated with these schemes. However, such datasets—with information on radiological and biopsy reports, different types of findings and good quality images—are difficult to find, mainly due to privacy concerns of different radiology centers and hospitals, and are often limited to the research team involved. Aiming to overcome these issues, we are developing an alternative based on images of a structured breast phantom previously developed in our group. Although having been validated in terms of their physical characteristics, investigating the images produced from this phantom exposure on a digital mammography system is an important task. Therefore, this work’s primary objective is to conduct a comparative analysis between digital images derived from this phantom and real-breast images to assess the degree of visual perception confusion between these two image types. This investigation will help determine the viability of using images from these phantom exposures in creating a database for evaluating the performance of techniques used in CAD schemes in digital mammography. For this purpose, a software was developed for managing comparative tests between images of actual breasts and images from this phantom, considering internal regions of interest. The results were promising, showing a variation of 55–65% in the rate of correct answers among observers, indicating a reasonable level of confusion between the two types of images.

A Case of Rapidly Progressive Renal Failure with Unearthed Amyloidosis

Amyloidosis-associated kidney disease commonly manifests with chronic glomerular symptoms including heavy proteinuria predominantly albuminuria. Clinical presentation ranges from full-blown nephrotic syndrome, hematuria, and hypertension to renal failure. In India patients with chronic kidney disease are mainly attributed to hypertension and diabetes but an underlying etiology such as amyloidosis needs to be unearthed and shouldn’t be ignored as an etiology. We report a case of a 60-year-old man with hypertension and hypothyroidism who presented with frothy urine for several years, b/l pedal edema for 15 days. Over the past 3 months, there was a serial increase in creatinine. As per CKD-EPI equation, the patient was CKD-4. As the patient was suspected to be rapidly progressive renal failure; a renal biopsy was planned. Biopsy reports were suggestive of Amyloidosis. Glomerular, vascular, and tubulointerstitial deposition of amyloid was seen. Based on renal biopsy and IHC staining; the patient’s diagnosis was AA-associated secondary renal amyloidosis. Thus in this case renal amyloidosis was an unearthed etiology.

Myocardial Inflammation in Cardiac Transthyretin Amyloidosis: Prevalence and Potential Prognostic Implications.

Despite previous histopathologic evidence for its presence, the role of myocardial inflammation in the development and progression of cardiac transthyretin amyloidosis (ATTR-CA) remains insufficiently understood. Thus, this study sought to characterize the prevalence and potential prognostic implications of myocardial inflammation in ATTR-CA. A retrospective observational study including patients with ATTR-CA diagnosed by endomyocardial biopsy was conducted. Myocardial inflammation was diagnosed through a review of routine endomyocardial biopsy reports. Baseline characteristics were compared using the Mann-Whitney U test and the Pearson χ2 test. Clinical outcomes were monitored via follow-up visits or telephone calls. Primary outcomes were all-cause death and a composite end point of all-cause death or heart failure hospitalization. Kaplan-Meier analyses, as well as univariable and age- and sex-adjusted multivariable Cox regression analyses, were used to assess differences in overall and composite end point-free survival between patients with ATTR-CA with and without myocardial inflammation. A total of 103 patients with ATTR-CA (100 wild type; 3 variant) were enrolled. Median follow-up was 18.2 (8.0-31.1) months. Myocardial inflammation was prevalent in 32% (n=33/103) of patients with ATTR-CA. Among evaluable patients with myocardial inflammation, 96% (n=26/27) and 31% (n=9/29) had elevated CD68 (clusters of differentiation 68)-positive macrophage and CD3 (clusters of differentiation 3)-positive T-cell counts, respectively. Overall survival (P=0.017) and composite end point-free survival (P=0.014) were significantly impaired in patients with ATTR-CA with myocardial inflammation (n=33) compared with those without (n=70). Statistical significance for both associations was sustained after adjustment for age and sex, yielding adjusted hazard ratios of 4.72 (95% CI, 1.33-16.71; P=0.016) and 2.30 (95% CI, 1.04-5.11; P=0.041) for all-cause death and the composite end point, respectively. Our findings affirm previous evidence that myocardial inflammation is present in approximately one-third of all patients with ATTR-CA. Moreover, we provide first data indicating that myocardial inflammation may be associated with a higher risk of death and heart failure hospitalizations in ATTR-CA.

P0543 Impact of disease clearance on the disease course in Ulcerative Colitis patients in clinical remission over a ten-year follow-up

Abstract Background Despite being in clinical remission, ulcerative colitis (UC) patients continue to have a risk of disease flare-ups. Although endoscopic and histological evaluations are considered the gold standard for follow-up, the value of histological inflammation in predicting disease flare-ups in clinically remitted patients is not clearly known. This study aimed to investigate the relationship between histological inflammation and disease flare-ups in UC patients in clinical remission. Methods Adult patients with UC, no history of colectomy, followed up in our outpatient clinic, and in clinical remission were included in the study (total Mayo score &amp;lt; 2). Biopsy reports from colonoscopies performed during clinical remission were examined for histological activity. The follow-up period was defined as 10 years, based on the last clinical remission recorded in the outpatient clinic records. The Nancy histological index (NHI) was used as the histological activity score. Patients with NHI &amp;lt; 2 were considered to be in histological remission. The temporal relationship between histological inflammation and the first clinical flare-up was evaluated using Spearman correlation analysis. Results A total of 53 patients, including 26 women and 27 men, with a diagnosis of UC in clinical remission were included in the study. The mean age of the patients was 51.5 years. While 28 patients were in endoscopic remission, 25 were followed up as endoscopically active. Among the 28 patients in endoscopic remission, 15 were in histological remission, and 13 were histologically active. Flare-ups were observed after a median of 18.0 months in patients with endoscopic remission and 10.0 months in those with endoscopic activity (p=0.07). Flare-ups were observed after a median of 96.0 months in patients with histological remission and 10.5 months in those with histological activity (p&amp;lt;0.05). A negative correlation was found between histological inflammation and disease flare-up (r=-0.381, p&amp;lt;0.05). Conclusion The risk of disease flare-ups is higher in patients who do not achieve disease clearance (i.e., those who are histologically active even in endoscopic remission).

Bridging the gap: Evaluating ChatGPT-generated, personalized, patient-centered prostate biopsy reports.

The highly specialized language used in prostate biopsy pathology reports coupled with low rates of health literacy leave some patients unable to comprehend their medical information. Patients' use of online search engines can lead to misinterpretation of results and emotional distress. Artificial intelligence (AI) tools such as ChatGPT (OpenAI) could simplify complex texts and help patients. This study evaluates patient-centered prostate biopsy reports generated by ChatGPT. Thirty-five self-generated prostate biopsy reports were synthesized using National Comprehensive Cancer Network guidelines. Each report was entered into ChatGPT, version 4, with the same instructions, and the explanations were evaluated by 5 urologists and 5 pathologists. Respondents rated the AI-generated reports as mostly accurate and complete. All but 1 report was rated complete and grammatically correct by the majority of physicians. Pathologists did not rate any reports as having severe potential for harm, but 1 or more urologists rated severe concern in 20% of the reports. For 80% of the reports, all 5 pathologists felt comfortable sharing them with a patient or another clinician, but all 5 urologists reached the same consensus for only 40% of reports. Although every report required edits, all physicians agreed that they could modify the ChatGPT report faster than they could write an original report. ChatGPT can save physicians substantial time by generating patient-centered reports appropriate for patient and physician audiences with low potential to cause harm. Surveyed physicians have confidence in the overall utility of ChatGPT, supporting further investigation of how AI could be integrated into physicians' workflows.

HCV and HBV genotypes: vital in the progression of HCV/ HBV co-infection

BackgroundViral hepatitis is the major contributor to liver cirrhosis and hepatocellular carcinoma (HCC). Studies indicated that the co-infection of hepatitis C and hepatitis B virus also prompts liver damage progression. Therefore, in the present study, the prevalence of HCV-HBV co-infection and the impact of HCV-HBV co-infection on the progression of liver damage was evaluated amongst the HCV-infected patients in Pakistan.MethodsIn this study 2500 HCV-positive patients were recruited from Pakistan. The presence and prevalence of HCV and HBV was confirmed through ELISA and nested PCR. To determine the liver damage due to viral infection levels of ALT, ALP, and total bilirubin were also determined. Diagnostic history of patients was thoroughly documented through serological tests and liver biopsy reports. Viral genotypes and viral loads were determined through multiplex polymerase chain reaction (PCR) and time PCR, respectively.ResultsThe study outcomes showed that 12.5% of the HCV-infected patients were co-infected with HBV. Co-infection development was more common in females than in males, and females were at a higher risk of developing the infection (p-value = < 0.0001, OR = 2.437). Despite the variation among different age groups, there was no significant difference in co-infection prevalence. HCV genotype 3a was found to be most prevalent while in HBV genotype D was found to be prevalent among the patients. The HCV patients frequently developed co-infection with HBV genotype D. It was also determined that viral load for HBV genotype D was higher compared to non-D genotypes while for HCV viral load was higher in non-3a genotypes.ConclusionsThis study evaluated the prevalence of HCV and HBV co-infection among HCV-positive patients, revealing that 12.5% patients were co-infected with HBV. Co-infection was more common in females, who had a higher risk of developing it. The study also revealed that HBV genotype D was the most prevalent in co-infected patients, with no significant age-related differences in co-infection rates.

Knowledge and Worry Following Review of Standard vs Patient-Centered Pathology Reports

This study compares knowledge of diagnosis and worry among adults presented with prostate biopsy reports in a patient-centered format, which present important clinical data in plain language, vs standard report format.

Disease Resolution after Cessation of Treatment in Patients with Eosinophilic Esophagitis

Background and aims: Eosinophilic esophagitis (EoE) is a chronic inflammatory condition of the esophagus. EoE is triggered in most patients by dietary allergens and mediated by type 2 immune responses. Over the past 3 decades, substantial progresses have been made in understanding EoE pathogenesis, management, and natural history. EoE affects children and adults, and the incidence and prevalence have increased over time. Untreated EoE can lead to severe complications including food impaction, small caliber esophagus, esophageal stricture, and esophageal perforation. EoE can be managed by dietary elimination, swallowed steroids, proton pump inhibitor, and biologics to achieve both clinical and tissue remission. Patients’ quality of life is significantly improved with effective EoE management. Thus far, reports on treatment-free remission in EoE patients without any treatment is rather scattered. Methods: We identified 7 EoE patients at our Massachusetts General Hospital Food Allergy Center via routine clinical care with treatment-free remission. Clinical charts and EGD biopsy reports were reviewed and analyzed. Results: We report 7 EoE patients who achieved treatment-free remission over time. In all 7 patients, their active EoEs were responsive to either diet elimination treatment or swallowed steroid treatment in both clinical symptoms and tissue eosinophilia of the esophagus for a variable period. The treatment-free status was achieved after their treatment was stopped for longer than 12 months in 4 of the 7 patients. Conclusions: We have reported 7 EoE cases, in whom all achieved treatment-free disease resolution after cessation of previous management and the treatment-free disease resolution lasted 12 months or longer. The precise mechanism and rate of the treatment-free remission need further investigation.