Myers, Jeffrey L.

Context.— A monthly pathology journal club has met for 24 years. It was established to help members stay apprised of the literature relevant to diagnostic pulmonary pathology. Objective.— To assess whether the journal club met its goal and to report on opportunities identified for improvement. Design.— To determine whether articles chosen for discussion as opposed to notation were more significant, Scopus citation indices for article types reviewed from January 2007 to November 2023 were compared. A survey of current faculty was undertaken to determine if the club was meeting expectations and to identify improvement opportunities. Results.— Articles from January 2007 to November 2023 included 858 discussed and 3385 noted. Mean (SD) citation count was 103.0 (409.80) for discussion and 64.9 (259.77) for notation articles ( P < .001). The citation count was noticeably right skewed, as articles with high citation counts inflated the mean. Members were mostly satisfied with the way the journal club was structured and managed. Members most valued the summary of the articles, followed by the live discussion. Opportunities for improvement included decreasing the number of journals scanned, decreasing detail in summaries, and using generative artificial intelligence (AI) to facilitate summary generation. A pilot using AI anecdotally reduced preparatory time, but the human-edited summary included more specific context, critical commentary, and enhanced take-home messages, providing a more nuanced analysis. Conclusions.— The journal club met its initial goal. Opportunities for improvement have been identified including the use of generative AI to facilitate article summarization.

Abstract Diagnosis of interstitial lung disease (ILD) requires a multidisciplinary discussion approach that includes clinicians, radiologists, and pathologists. Surgical lung biopsy (SLB) is currently the recommended standard in obtaining pathologic specimens for patients with ILD requiring a tissue diagnosis. The increased diagnostic confidence and accuracy provided by microscopic pathology assessment of SLB specimens must be balanced with the associated risks in patients with ILD. This document was developed by the SLB Working Group of the Pulmonary Fibrosis Foundation, composed of a multidisciplinary group of ILD physicians, including pulmonologists, radiologists, pathologists, and thoracic surgeons. In this document, we present an up-to-date literature review of the indications, contraindications, risks, and alternatives to SLB in the diagnosis of fibrotic ILD; outline an integrated approach to the decision-making around SLB in the diagnosis of fibrotic ILD; and provide practical information to maximize the yield and safety of SLB.

Abstract Context. —Diffuse pulmonary hemorrhage is an uncommon presenting manifestation of angiosarcoma. Objective. —To review the clinical, radiologic, and pathologic findings of patients with metastatic angiosarcoma who presented with diffuse pulmonary hemorrhage. Design. —Patients fulfilling inclusion criteria were identified from the consultation files. Clinical and radiologic data were obtained from referring pathologists. Histologic slides were reviewed in all patients. Results. —Our patients included 6 men and 1 woman, aged 31 to 73 years; 4 patients were younger than 40 years. Six patients presented with hemoptysis, and all had diffuse abnormalities on radiographic studies. Clinical considerations prior to biopsy included pulmonary hemorrhage syndrome (n = 2), acute respiratory failure (n = 1), and infection (n = 1). Metastatic disease was included in the differential diagnosis in only 1 patient. None had a diagnosis of malignancy prior to lung biopsy. All biopsies showed hemorrhage associated with atypical epithelioid and spindle cells, forming anastomosing vascular channels, distributed along and within lymphatics and arteries. Neoplastic cells were immunoreactive for factor VIII–related protein or CD31 in all cases for which special stains were available. Three patients with complete follow-up died of their disease. Primary sites were discovered in all 3 patients who underwent autopsy examination. Two tumors arose in the heart and 1 in the pelvic soft tissues. One additional patient had a likely primary site identified in the right atrium by cardiac ultrasound and was subsequently lost to follow-up. Conclusion. —Angiosarcoma should be included in the differential diagnosis of diffuse pulmonary hemorrhage, especially in young adults.

Abstract We describe a patient with self-induced inhalational pulmonary talcosis originally diagnosed as asthma. A 35-year-old female respiratory technologist developed severe asthma that was refractory to steroids and methotrexate. An open lung biopsy specimen showed scattered aggregates of refractile golden crystals within membranous and respiratory bronchioles. The particles ranged in size from 30 to 100 μm and were birefringent when viewed with polarized light. Following review of the lung biopsy specimen, the patient admitted to regularly inhaling large amounts of hospital baby powder. Analysis of the lung biopsy specimen and a sample of the hospital baby powder by x-ray energy dispersion showed identical spectroscopic peaks, including elemental peaks for magnesium silicate. Many patients with self-induced illness lack the picturesque symptomatology classically attributed to Munchausen syndrome. Awareness of these more subtle and varied patterns of presentation may aid in earlier recognition.

Abstract Rationale Usual interstitial pneumonia (UIP) is the defining morphology of idiopathic pulmonary fibrosis (IPF). Guidelines for IPF diagnosis conditionally recommend surgical lung biopsy for histopathology diagnosis of UIP when radiology and clinical context are not definitive. A “molecular diagnosis of UIP” in transbronchial lung biopsy, the Envisia Genomic Classifier, accurately predicted histopathologic UIP. Objectives We evaluated the combined accuracy of the Envisia Genomic Classifier and local radiology in the detection of UIP pattern. Methods Ninety-six patients who had diagnostic lung pathology as well as a transbronchial lung biopsy for molecular testing with Envisia Genomic Classifier were included in this analysis. The classifier results were scored against reference pathology. UIP identified on high-resolution computed tomography (HRCT) as documented by features in local radiologists’ reports was compared with histopathology. Measurements and Main Results In 96 patients, the Envisia Classifier achieved a specificity of 92.1% (confidence interval [CI],78.6–98.3%) and a sensitivity of 60.3% (CI, 46.6–73.0%) for histology-proven UIP pattern. Local radiologists identified UIP in 18 of 53 patients with UIP histopathology, with a sensitivity of 34.0% (CI, 21.5–48.3%) and a specificity of 96.9% (CI, 83.8–100%). In conjunction with HRCT patterns of UIP, the Envisia Classifier results identified 24 additional patients with UIP (sensitivity 79.2%; specificity 90.6%). Conclusions In 96 patients with suspected interstitial lung disease, the Envisia Genomic Classifier identified UIP regardless of HRCT pattern. These results suggest that recognition of a UIP pattern by the Envisia Genomic Classifier combined with HRCT and clinical factors in a multidisciplinary discussion may assist clinicians in making an interstitial lung disease (especially IPF) diagnosis without the need for a surgical lung biopsy.

Abstract Rationale Usual interstitial pneumonia (UIP) is the histopathologic hallmark of idiopathic pulmonary fibrosis. Although UIP can be detected by high-resolution computed tomography of the chest, the results are frequently inconclusive, and pathology from transbronchial biopsy (TBB) has poor sensitivity. Surgical lung biopsy may be necessary for a definitive diagnosis. Objectives To develop a genomic classifier in tissue obtained by TBB that distinguishes UIP from non-UIP, trained against central pathology as the reference standard. Methods Exome enriched RNA sequencing was performed on 283 TBBs from 84 subjects. Machine learning was used to train an algorithm with high rule-in (specificity) performance using specimens from 53 subjects. Performance was evaluated by cross-validation and on an independent test set of specimens from 31 subjects. We explored the feasibility of a single molecular test per subject by combining multiple TBBs from upper and lower lobes. To address whether classifier accuracy depends upon adequate alveolar sampling, we tested for correlation between classifier accuracy and expression of alveolar-specific genes. Results The top-performing algorithm distinguishes UIP from non-UIP conditions in single TBB samples with an area under the receiver operator characteristic curve (AUC) of 0.86, with specificity of 86% (confidence interval = 71–95%) and sensitivity of 63% (confidence interval = 51–74%) (31 test subjects). Performance improves to an AUC of 0.92 when three to five TBB samples per subject are combined at the RNA level for testing. Although we observed a wide range of type I and II alveolar–specific gene expression in TBBs, expression of these transcripts did not correlate with classifier accuracy. Conclusions We demonstrate proof of principle that genomic analysis and machine learning improves the utility of TBB for the diagnosis of UIP, with greater sensitivity and specificity than pathology in TBB alone. Combining multiple individual subject samples results in increased test accuracy over single sample testing. This approach requires validation in an independent cohort of subjects before application in the clinic.

PURPOSE: To estimate the efficacy of contralateral prophylactic mastectomy in women with a personal and family history of breast cancer. PATIENTS AND METHODS: We followed the course of 745 women with a first breast cancer and a family history of breast and/or ovarian cancer who underwent contralateral prophylactic mastectomy at the Mayo Clinic between 1960 and 1993. Family history information and cancer follow-up information were obtained from the medical record, a study-specific questionnaire, and telephone follow-up. Life-tables for contralateral breast cancers, which consider age at first breast cancer, current age, and type of family history, were used to calculate the number of breast cancers expected in our cohort had they not had a prophylactic mastectomy. RESULTS: Of the 745 women in our cohort, 388 were premenopausal (age < 50 years) and 357 were post- menopausal. Eight women developed a contralateral breast cancer. Six events were observed among the premenopausal women, compared with 106.2 predicted, resulting in a risk reduction of 94.4% (95% confidence interval [CI], 87.7% to 97.9%). For the 357 postmenopausal women, 50.3 contralateral breast cancers were predicted, whereas only two were observed, representing a 96.0% risk reduction (95% CI, 85.6% to 99.5%). CONCLUSION: The incidence of contralateral breast cancer seems to be reduced significantly after contralateral prophylactic mastectomy in women with a personal and family history of breast cancer.