Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

Manual counting of mitotic tumor cells in tissue sections constitutes one of the strongest prognostic markers for breast cancer. This procedure, however, is time-consuming and error-prone. We developed a method to automatically detect mitotic figures in breast cancer tissue sections based on convolutional neural networks (CNNs). Application of CNNs to hematoxylin and eosin (H&E) stained histological tissue sections is hampered by: (1) noisy and expensive reference standards established by pathologists, (2) lack of generalization due to staining variation across laboratories, and (3) high computational requirements needed to process gigapixel whole-slide images (WSIs). In this paper, we present a method to train and evaluate CNNs to specifically solve these issues in the context of mitosis detection in breast cancer WSIs. First, by combining image analysis of mitotic activity in phosphohistone-H3 (PHH3) restained slides and registration, we built a reference standard for mitosis detection in entire H&E WSIs requiring minimal manual annotation effort. Second, we designed a data augmentation strategy that creates diverse and realistic H&E stain variations by modifying the hematoxylin and eosin color channels directly. Using it during training combined with network ensembling resulted in a stain invariant mitosis detector. Third, we applied knowledge distillation to reduce the computational requirements of the mitosis detection ensemble with a negligible loss of performance. The system was trained in a single-center cohort and evaluated in an independent multicenter cohort from The Cancer Genome Atlas on the three tasks of the Tumor Proliferation Assessment Challenge (TUPAC). We obtained a performance within the top-3 best methods for most of the tasks of the challenge.Comment: Accepted to appear in IEEE Transactions on Medical Imagin

Higher COVID-19 pneumonia risk associated with anti-IFN-α than with anti-IFN-ω auto-Abs in children

We found that 19 (10.4%) of 183 unvaccinated children hospitalized for COVID-19 pneumonia had autoantibodies (auto-Abs) neutralizing type I IFNs (IFN-alpha 2 in 10 patients: IFN-alpha 2 only in three, IFN-alpha 2 plus IFN-omega in five, and IFN-alpha 2, IFN-omega plus IFN-beta in two; IFN-omega only in nine patients). Seven children (3.8%) had Abs neutralizing at least 10 ng/ml of one IFN, whereas the other 12 (6.6%) had Abs neutralizing only 100 pg/ml. The auto-Abs neutralized both unglycosylated and glycosylated IFNs. We also detected auto-Abs neutralizing 100 pg/ml IFN-alpha 2 in 4 of 2,267 uninfected children (0.2%) and auto-Abs neutralizing IFN-omega in 45 children (2%). The odds ratios (ORs) for life-threatening COVID-19 pneumonia were, therefore, higher for auto-Abs neutralizing IFN-alpha 2 only (OR [95% CI] = 67.6 [5.7-9,196.6]) than for auto-Abs neutralizing IFN-. only (OR [95% CI] = 2.6 [1.2-5.3]). ORs were also higher for auto-Abs neutralizing high concentrations (OR [95% CI] = 12.9 [4.6-35.9]) than for those neutralizing low concentrations (OR [95% CI] = 5.5 [3.1-9.6]) of IFN-omega and/or IFN-alpha 2

Histological subtypes in triple negative breast cancer are associated with specific information on survival

Much research has focused on finding novel prognostic biomarkers for triple negative breast cancer (TNBC), whereas only scattered information about the relation between histopathological features and survival in TNBC is available. This study aims to explore the prognostic value of histological subtypes in TNBC. A multicenter retrospective TNBC cohort was established from five Dutch hospitals. All non-neoadjuvantly treated, stage I-III patients with estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 negative breast cancer diagnosed between 2006 and 2014 were included. Clinical and follow-up data (overall survival; OS, relapse free survival; RFS) were retrieved and a central histopathological review was performed. Of 597 patients included (median follow up 62.8 months, median age at diagnosis 56.0 years), 19.4% developed a recurrence. The most prevalent histological subtypes were carcinoma of no special type (NST) (88.4%), metaplastic carcinoma (4.4%) and lobular carcinoma (3.4%). Collectively, tumors of special type were associated with a worse RFS and OS compared to carcinoma NST (RFS HR 1.89; 95% CI 1.18-3.03; p = 0.008; OS HR 1.94; 95% CI 1.28-2.92; p = 0.002). Substantial differences in survival, however, were present between the different histological subtypes. In the presented TNBC cohort, special histological subtype was in general associated with less favorable survival. However, within the group of tumors of special type there were differences in survival between the different subtypes. Accurate histological examination can provide specific prognostic information that may potentially enable more personalized treatment and surveillance regimes for TNBC patients.Funding Agencies|Radboud University Medical Center Institute for Health Sciences (RIHS)</p

ESM_1.docx

Detailed description of the firms, solutions and clones used to examine the cases mentioned in the case report

ESM_3 (figures of immunohistochemical staining)

Figures associated with the performed immunohistochemical staining of the sections used in the case report

Invasive aspergillosis in patients admitted to the intensive care unit with severe influenza: a retrospective cohort study

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Blinded double reading yields a higher programme sensitivity than non-blinded double reading at digital screening mammography: A prospected population based study in the south of The Netherlands

Purpose: To prospectively determine the screening mammography outcome at blinded and non-blinded double reading in a;biennial population based screening programme in the south of the Netherlands. Methods: We included a consecutive series of 87,487 digital screening mammograms, obtained between July 2009 and July 2011. Screening mammograms were double read in either a blinded (2nd reader was not informed about the 1st reader's decision) or non-blinded fashion (2nd reader was informed about the 1st reader's decision). This reading strategy was alternated on a monthly basis. Women with discrepant readings between the two radiologists were always referred for further analysis. During 2 years follow-up, we collected the radiology reports, surgical correspondence and pathology reports of all referred women and interval breast cancers. Results: Respectively 44,491 and 42,996 screens had been read either in a blinded or non-blinded fashion. Referral rate (3.3% versus 2.8%, p <0.001) and false positive rate (2.6% versus 2.2%, p = 0.002) were significantly higher at blinded double reading whereas the cancer detection rate per 1000 screens (7.4 versus 6.5, p = 0.14) and positive predictive value of referral (22% versus 23%, p = 0.51) were comparable. Blinded double reading resulted in a significantly higher programme sensitivity (83% versus 76%, p = 0.01). Per 1000 screened women, blinded double reading would yield 0.9 more screen detected cancers and 0.6 less interval cancers than non-blinded double reading, at the expense of 4.4 more recalls. Conclusion: We advocate the use of blinded double reading in order to achieve a better programme sensitivity, at the expense of an increased referral rate and false positive referral rate. (C) 2014 Elsevier Ltd. All rights reserve

Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm

An increasing number of pathology laboratories are now fully digitised, using whole slide imaging (WSI) for routine diagnostics. WSI paves the road to use artificial intelligence (AI) that will play an increasing role in computer-aided diagnosis (CAD). In melanocytic skin lesions, the presence of a dermal mitosis may be an important clue for an intermediate or a malignant lesion and may indicate worse prognosis. In this study a mitosis algorithm primarily developed for breast carcinoma is applied to melanocytic skin lesions. This study aimed to assess whether the algorithm could be used in diagnosing melanocytic lesions, and to study the added value in diagnosing melanocytic lesions in a practical setting. WSIs of a set of hematoxylin and eosin (H&amp;E) stained slides of 99 melanocytic lesions (35 nevi, 4 intermediate melanocytic lesions, and 60 malignant melanomas, including 10 nevoid melanomas), for which a consensus diagnosis was reached by three academic pathologists, were subjected to a mitosis algorithm based on AI. Two academic and six general pathologists specialized in dermatopathology examined the WSI cases two times, first without mitosis annotations and after a washout period of at least 2 months with mitosis annotations based on the algorithm. The algorithm indicated true mitosis in lesional cells, i.e., melanocytes, and non-lesional cells, i.e., mainly keratinocytes and inflammatory cells. A high number of false positive mitosis was indicated as well, comprising melanin pigment, sebaceous glands nuclei, and spindle cell nuclei such as stromal cells and neuroid differentiated melanocytes. All but one pathologist reported more often a dermal mitosis with the mitosis algorithm, which on a regular basis, was incorrectly attributed to mitoses from mainly inflammatory cells. The overall concordance of the pathologists with the consensus diagnosis for all cases excluding nevoid melanoma (n = 89) appeared to be comparable with and without the use of AI (89% vs. 90%). However, the concordance increased by using AI in nevoid melanoma cases (n = 10) (75% vs. 68%). This study showed that in general cases, pathologists perform similarly with the aid of a mitosis algorithm developed primarily for breast cancer. In nevoid melanoma cases, pathologists perform better with the algorithm. From this study, it can be learned that pathologists need to be aware of potential pitfalls using CAD on H&amp;E slides, e.g., misinterpreting dermal mitoses in non-melanotic cells.Funding Agencies|Innovative Medicines Initiative 2 Joint Undertaking [945358]; European UnionEuropean Commission; EFPIA</p

Validation of whole-slide digitally imaged melanocytic lesions : does z-stack scanning improve diagnostic accuracy?

Background: Accurate diagnosis of melanocytic lesions is challenging, even for expert pathologists. Nowadays, whole-slide imaging (WSI) is used for routine clinical pathology diagnosis in several laboratories. One of the limitations of WSI, as it is most often used, is the lack of a multiplanar focusing option. In this study, we aim to establish the diagnostic accuracy of WSI for melanocytic lesions and investigate the potential accuracy increase of z-stack scanning. Z-stack enables pathologists to use a software focus adjustment, comparable to the fine-focus knob of a conventional light microscope. Materials and Methods: Melanocytic lesions (n = 102) were selected from our pathology archives: 35 nevi, 5 spitzoid tumors of unknown malignant potential, and 62 malignant melanomas, including 10 nevoid melanomas. All slides were scanned at a magnification comparable to use of a ×40 objective, in z-stack mode. A ground truth diagnosis was established on the glass slides by four academic dermatopathologists with a special interest in the diagnosis of melanoma. Six nonacademic surgical pathologists subspecialized in dermatopathology examined the cases by WSI. Results: An expert consensus diagnosis was achieved in 99 (97%) of cases. Concordance rates between surgical pathologists and the ground truth varied between 75% and 90%, excluding nevoid melanoma cases. Concordance rates of nevoid melanoma varied between 10% and 80%. Pathologists used the software focusing option in 7%–28% of cases, which in 1 case of nevoid melanoma resulted in correcting a misdiagnosis after finding a dermal mitosis. Conclusion: Diagnostic accuracy of melanocytic lesions based on glass slides and WSI is comparable with previous publications. A large variability in diagnostic accuracy of nevoid melanoma does exist. Our results show that z-stack scanning, in general, does not increase the diagnostic accuracy of melanocytic

Shrinkage versus fragmentation response in neoadjuvantly treated oesophageal adenocarcinoma: significant prognostic relevance

Aims: No consensus exists on the clinical value of tumour regression grading (TRG) systems for therapy effects of neoadjuvant chemoradiotherapy (nCRT) in oesophageal adenocarcinoma. Existing TRG systems lack standardization and reproducibility, and do not consider the morphological heterogeneity of tumour response. Therefore, we aim to identify morphological tumour regression patterns of oesophageal adenocarcinoma after nCRT and their association with survival. Methods and results: Patients with oesophageal adenocarcinoma, who underwent nCRT followed by surgery and achieved a partial response to nCRT, were identified from two Dutch upper-gastrointestinal (GI) centres (2005–18; test cohort). Resection specimens were scored for regression patterns by two independent observers according to a pre-defined three-step flowchart. The results were validated in an external cohort (2001–17). In total, 110 patients were included in the test cohort and 115 in the validation cohort. In the test cohort, two major regression patterns were identified: fragmentation (60%) and shrinkage (40%), with an excellent interobserver agreement (κ = 0.87). Here, patients with a fragmented pattern had a significantly higher pathological stage (stages III/IV: 52 versus 16%; P < 0.001), less downstaging (48 versus 91%; P < 0.001), a higher risk of recurrence [risk ratio (RR) = 2.9, 95% confidence interval (CI) = 1.5–5.6] and poorer 5-year overall survival (30 versus 80% respectively, P = 0.001). Conclusions: The validation cohort confirmed these findings, although had more advanced cases (case-stages = III/IV 91 versus 73%, P = 0.005) and a higher prevalence of fragmented-pattern cases (80 versus 60%, P = 0.002). When combining the cohorts in multivariate analysis, the pattern of response was an independent prognostic factor [hazard ratio (HR) = 1.76, 95% CI = 1.0–3.0]. In conclusion, we established an externally validated, reproducible and clinically relevant classification of tumour response