Congo Red Staining in Digital Pathology: The Streamlined Pipeline for Amyloid Detection Through Congo Red Fluorescence Digital Analysis

Cazzaniga, Giorgio; Bolognesi, Maddalena Maria; Stefania, Matteo Davide; Mascadri, Francesco; Eccher, Albino; Alberici, Federico; Mescia, Federica; Smith, Andrew; Fraggetta, Filippo; Rossi, Mattia; Gambaro, Giovanni; Pagni, Fabio; L’Imperio, Vincenzo

doi:10.1016/j.labinv.2023.100243

Cited by 6 publications

(4 citation statements)

References 38 publications

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“…The switch from microscope to digital pathology and WSI enabled the application of image analysis and computational tools, as demonstrated by the amyloid use case, where the conventional assessment of birefringence under polarised light can potentially hamper the digitisation of the Congo red stain. However, the application of CRF associated with SPADA computational pipeline 16 allows the automatic detection and quantification of amyloid deposits, detecting even…”

Section: Discussionmentioning

confidence: 99%

“…IF glomerular positivity and intensity (from 0 to 3+) were recorded, as well as the Amyloid Score. 16 The review results, along with the time required to render a complete diagnosis for each case, have been comprehensively collected and organised into an Excel file (Microsoft, Redmond, USA). The obtained dataset is publicly available in the Bicocca Open Archive Research Data repository.…”

Section: Pathology Reviewmentioning

confidence: 99%

“…A perfect concordance was recorded for the interpretation of Congo red positivity with both commercial and medical monitors as compared with the traditional microscope, with 4 out of 30 cases (13%) receiving a diagnosis of amyloidosis. The application of Congo red fluorescence (CRF) as a digital alternative to the birefringence under polarised light using the Streamlined Pipeline for Amyloid detection through congo red fluorescence Digital Analysis (SPADA) pipeline 16 allowed the quantification and extension assessment of amyloid deposits in the different compartments using the Amyloid Score with both monitors, with slightly higher average Amyloid Score as compared with the birefringence assessment (6 vs 7), detecting minimal interstitial deposits that were missed by polarised light in two cases.…”

Section: Congo Red Evaluationmentioning

confidence: 99%

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Benchmarking digital displays (monitors) for histological diagnoses: the nephropathology use case

Cazzaniga,

Mascadri,

Marletta

et al. 2024

J Clin Pathol

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AimThe digital transformation of the pathology laboratory is being continuously sustained by the introduction of innovative technologies promoting whole slide image (WSI)-based primary diagnosis. Here, we proposed a real-life benchmark of a pathology-dedicated medical monitor for the primary diagnosis of renal biopsies, evaluating the concordance between the ‘traditional’ microscope and commercial monitors using WSI from different scanners.MethodsThe College of American Pathologists WSI validation guidelines were used on 60 consecutive renal biopsies from three scanners (Aperio, 3DHISTECH and Hamamatsu) using pathology-dedicated medical grade (MG), professional grade (PG) and consumer-off-the-shelf (COTS) monitors, comparing results with the microscope diagnosis after a 2-week washout period.ResultsMG monitor was faster (1090 vs 1159 vs 1181 min, delta of 6–8%, p<0.01), with slightly better performances on the detection of concurrent diseases compared with COTS (κ=1 vs 0.96, 95% CI=0.87 to 1), but equal concordance to the commercial monitors on main diagnosis (κ=1). Minor discrepancies were noted on specific scores/classifications, with MG and PG monitors closer to the reference report (r=0.98, 95% CI=0.83 to 1 vs 0.98, 95% CI=0.83 to 1 vs 0.91, 95% CI=0.76 to 1, κ=0.93, 95% CI=077 to 1 vs 0.93, 95% CI=0.77 to 1 vs 0.86, 95% CI=0.64 to 1, κ=1 vs 0.50, 95% CI=0 to 1 vs 0.50, 95% CI=0 to 1, for IgA, antineutrophilic cytoplasmic antibody and lupus nephritis, respectively). Streamlined Pipeline for Amyloid detection through congo red fluorescence Digital Analysis detected amyloidosis on both monitors (4 of 30, 13% cases), allowing detection of minimal interstitial deposits with slight overestimation of the Amyloid Score (average 6 vs 7).ConclusionsThe digital transformation needs careful assessment of the hardware component to support a smart and safe diagnostic process. Choosing the display for WSI is critical in the process and requires adequate planning.

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Section: Discussionmentioning

confidence: 99%

Section: Pathology Reviewmentioning

confidence: 99%

Section: Congo Red Evaluationmentioning

confidence: 99%

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Benchmarking digital displays (monitors) for histological diagnoses: the nephropathology use case

Cazzaniga,

Mascadri,

Marletta

et al. 2024

J Clin Pathol

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“…However, the small sample size of this study was a significant limitation. In another recent study, Congo red fluorescence on virtual slides (CRFvs) from 154 renal biopsies was used to build an automated digital pipeline tool to identify the amyloid-containing areas in renal biopsies [81]. Optimum interobserver agreement was observed using this approach (k = 0.90; 95% CI, 0.81-0.98).…”

Section: Ai Applications To Pathology In Cardiac Amyloidosismentioning

confidence: 99%

How Artificial Intelligence Can Enhance the Diagnosis of Cardiac Amyloidosis: A Review of Recent Advances and Challenges

Kamel,

Abbas,

Kanaan

et al. 2024

JCDD

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Cardiac amyloidosis (CA) is an underdiagnosed form of infiltrative cardiomyopathy caused by abnormal amyloid fibrils deposited extracellularly in the myocardium and cardiac structures. There can be high variability in its clinical manifestations, and diagnosing CA requires expertise and often thorough evaluation; as such, the diagnosis of CA can be challenging and is often delayed. The application of artificial intelligence (AI) to different diagnostic modalities is rapidly expanding and transforming cardiovascular medicine. Advanced AI methods such as deep-learning convolutional neural networks (CNNs) may enhance the diagnostic process for CA by identifying patients at higher risk and potentially expediting the diagnosis of CA. In this review, we summarize the current state of AI applications to different diagnostic modalities used for the evaluation of CA, including their diagnostic and prognostic potential, and current challenges and limitations.

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Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline

L’Imperio,

Cazzaniga,

Mannino

et al. 2024

Virchows Arch

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The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, − 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.

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Congo Red Staining in Digital Pathology: The Streamlined Pipeline for Amyloid Detection Through Congo Red Fluorescence Digital Analysis

Cited by 6 publications

References 38 publications

Benchmarking digital displays (monitors) for histological diagnoses: the nephropathology use case

Benchmarking digital displays (monitors) for histological diagnoses: the nephropathology use case

How Artificial Intelligence Can Enhance the Diagnosis of Cardiac Amyloidosis: A Review of Recent Advances and Challenges

Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline

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