| --- |
| license: cc-by-4.0 |
| task_categories: |
| - tabular-classification |
| - image-classification |
| tags: |
| - pathology |
| - ovarian-cancer |
| - HGSOC |
| - platinum-resistance |
| - virtual-mIF |
| - multimodal |
| - computational-pathology |
| pretty_name: PathSeek-MAS (HGSOC Platinum-Response Multimodal Features) |
| size_categories: |
| - n<1K |
| --- |
| |
| # PathSeek-MAS — Multimodal WSI Features for HGSOC Platinum-Response Prediction |
|
|
| Derived per-slide features supporting the PathSeek-MAS study (npj Digital Medicine). |
| The task is **platinum response prediction** in high-grade serous ovarian carcinoma (HGSOC) |
| from H&E whole-slide images (WSIs), using a dual-agent model: |
|
|
| - **Virtual Protein Agent** — *virtual multiplex immunofluorescence (mIF)*: 21 protein markers |
| predicted per patch by GigaTIME (`gigatime_csv/`). |
| - **Morphology Agent** — UNI foundation-model patch embeddings (`uni_pt/`). |
|
|
| ## Cohorts (503 WSIs) |
|
|
| | Cohort | Slides | Sensitive (label 1) | Resistant (label 0) | WSI source | |
| |---|---|---|---|---| |
| | TCGA-OV | 156 | 117 | 39 | GDC | |
| | PTRC-HGSOC | 347 | 202 | 145 | Chowdhury et al. | |
|
|
| **Label convention (both cohorts):** `label == 1` = **Sensitive**, `label == 0` = **Resistant**. |
| Ground truth: TCGA `PlatinumStatus` (Zhang et al., mmc2.xlsx); PTRC `Tumor response` |
| (`sensitive`→1, `refractory`→0). |
|
|
| ## Files |
|
|
| ``` |
| TCGA-OV/ PTRC-HGSOC/ |
| gigatime_csv/ # one CSV per slide: virtual-mIF predicted protein values per patch |
| uni_pt/ # one .pt per slide: UNI patch embeddings (dict: 'features' [N,1024], 'coords' [N,2]) |
| labels.csv # slide_id, case_id, label |
| ``` |
|
|
| ### `gigatime_csv/*.csv` schema (27 columns) |
| `patch_name, slide_id, row, col,` then **23 channels** (21 protein markers + 2 staining channels): |
| `DAPI, TRITC, Cy5, PD-1, CD14, CD4, T-bet, CD34, CD68, CD16, CD11c, CD138, CD20, CD3, CD8, |
| PD-L1, CK, Ki67, Tryptase, Actin-D, Caspase3-D, PHH3-B, Transgelin`. |
| `row, col` are the patch grid coordinates (used to place values spatially on the WSI). Note: `DAPI` and `Cy5` are staining/imaging channels, not protein markers; the remaining 21 are antibody-targeted proteins. |
| |
| ### `uni_pt/*.pt` |
| `torch.load(...)` returns a dict with `features` (`[n_patches, 1024]` float) and `coords` |
| (`[n_patches, 2]` int patch coordinates). |
| |
| ## Preprocessing used by the model |
| - Virtual-protein input: **TCGA → `log1p`**, **PTRC → `logit`**, then per-patch row-standardization. |
| - Both agents pool patches via gated attention; fused by a cross-modal gating head. |
| |
| ## Not included |
| - **Raw WSIs** (~200 GB): TCGA-OV via the NCI GDC; PTRC-HGSOC via the original study. Not re-hosted. |
| - Original third-party clinical supplementary tables — please cite the source publications. |
| |
| ## Code |
| Analysis code: https://github.com/qklee/PathSeek-MAS |
| |
| ## Citation |
| > PathSeek-MAS (npj Digital Medicine). Citation to be added upon publication. |
| |
