August 2026
1. SFANOS KS, Morton R, Flores JN, Sosa RY, et al
   Subclonal Complete Loss of CDKN1B as a Common Genomic Alteration in Prostate Cancer: Associations With Race and Prostate Cancer Outcomes.
   Mod Pathol. 2026 Aug 12:101065. doi: 10.1016/j.modpat.2026.101065.
   

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   May 2026
2. SALGUERO-LOPEZ J, Medina S, Serafin R, Wang R, et al
   AI-Informed Architectural Insights of Three-Dimensional Glandular Networks Identify Prostate Cancer Patients at a Higher Risk of Biochemical Recurrence.
   Mod Pathol. 2026 May 25:101018. doi: 10.1016/j.modpat.2026.101018.
   

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   February 2026
3. SERAFIN RB, Lopez JS, Chow S, Wang R, et al
   Detection of prostate cancer in 3D pathology datasets via generative immunolabeling.
   Mod Pathol. 2026 Feb 13:100975. doi: 10.1016/j.modpat.2026.100975.
   

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   December 2025
4. NATEGHI R, Zhou R, Saft M, Schnauss M, et al
   Artificial Intelligence (AI)-Driven Screening of Equivocal Prostate Immunohistochemistry (IHC) Cases: Development and Validation of a Screening and Cancer Detection Framework.
   Mod Pathol. 2025;38:100904.
   

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   November 2025
5. ZABIHOLLAHY F, Shi K, Wangulu C, Prassas I, et al
   Clinical Grade Interpretable Artificial Intelligence Tool for Automated Detection of Lymph Node Metastasis in Prostate Cancer.
   Mod Pathol. 2025 Nov 10:100934. doi: 10.1016/j.modpat.2025.100934.
   

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   October 2025
6. JENNIFER NGUYEN NN, Liu K, Lajkosz K, Bernardino R, et al
   Corrigendum to "Magnetic Resonance Imaging (MRI)-Adapted Prostate Cancer Risk Tool Incorporating Cribriform and Intraductal Carcinoma" (Modern Pathology 2025 Dec;38(12):100852).
   Mod Pathol. 2025;38:100893.
   

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   July 2025
7. NGUYEN NJ, Liu K, Lajkosz K, Bernardino R, et al
   MRI-Adapted Prostate Cancer Risk Tool Incorporating Cribriform and Intraductal Carcinoma.
   Mod Pathol. 2025 Jul 25:100852. doi: 10.1016/j.modpat.2025.100852.
   

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   June 2025
8. CAI Q, Meng X, Sun J, Gagan J, et al
   Prostate Ductal Adenocarcinoma Revisited: Clinicopathological and Genomic Characterization Identifies Heterogenous Group of Diseases with Implications for Patient Management.
   Mod Pathol. 2025;38:100743.
   

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   May 2025
9. JI X, Salmon R, Mulliqi N, Khan U, et al
   Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence-Assisted Cancer Diagnosis.
   Mod Pathol. 2025;38:100715.
   

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   January 2025
10. SAMUELI B, Al-Ahmadie H, Chen YB, Gopalan A, et al
    Histopathologic and Molecular Characterization of IDH-Mutant Prostatic Adenocarcinoma.
    Mod Pathol. 2025;38:100616.
    

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    November 2024
11. FARYNA K, Tessier L, Retamero J, Bonthu S, et al
    Evaluation of Artificial Intelligence-Based Gleason Grading Algorithms "in the Wild".
    Mod Pathol. 2024;37:100563.
    

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    July 2024
12. WONG PF, McNeil C, Wang Y, Paparian J, et al
    Clinical-Grade Validation of an Autofluorescence Virtual Staining System with Human Experts and a Deep Learning System for Prostate Cancer.
    Mod Pathol. 2024 Jul 26:100573. doi: 10.1016/j.modpat.2024.100573.
    

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13. HARDER C, Pryalukhin A, Quaas A, Eich ML, et al
    Enhancing Prostate Cancer Diagnosis: AI-Driven Virtual Biopsy for Optimal MRI-Targeted Biopsy Approach and Gleason Grading Strategy.
    Mod Pathol. 2024 Jul 17:100564. doi: 10.1016/j.modpat.2024.100564.
    

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    April 2024
14. PRENDEVILLE S, Kaur H, Ansari S, Alqaqa S, et al
    Somatic Tumor Testing in Prostate Cancer: Experience of a Tertiary-Care Center Including Pathologist-Driven Reflex Testing of Localized Tumors at Diagnosis.
    Mod Pathol. 2024 Apr 6:100489. doi: 10.1016/j.modpat.2024.100489.
    

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15. FERRERO A, Ghelichkhan E, Manoochehri H, Ho MM, et al
    HistoEM: A Pathologist-Guided and Explainable Workflow Using Histogram Embedding for Gland Classification.
    Mod Pathol. 2024;37:100447.
    

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    March 2024
16. IRMAKCI I, Nateghi R, Zhou R, Vescovo M, et al
    Tissue Contamination Challenges the Credibility of Machine Learning Models in Real World Digital Pathology.
    Mod Pathol. 2024;37:100422.
    

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    January 2024
17. MIYAMOTO H, Teramoto Y, Numbere N, Wang Y, et al
    Prostate cancer risk stratification by simple scoring of the current pT3 lesions: A proposal for a new pathologic T-staging system.
    Mod Pathol. 2024 Jan 22:100429. doi: 10.1016/j.modpat.2024.100429.
    

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